From 346c23862f46f861fa2bb00f96aa76c2c22da17a Mon Sep 17 00:00:00 2001 From: Dmitrii Vasilev Date: Sun, 9 Aug 2026 13:51:38 +0700 Subject: [PATCH 1/9] docs(numeric): correct why former_name exists -- the ladder was never published (Refs #2001) I justified former_name="GF-T{N}" by claiming arXiv:2606.05017 and arXiv:2606.09686 cite the old name. They do not, and the correction matters because it changes what the rename cost. 2606.05017 is the binary GF family; its source, docs/arxiv-submission/trinity-gf16.tex, contains zero occurrences of "GF-T". 2606.09686 is this catalog, and the only commit introducing an id=gft row is from 2026-08-09 -- mine. The ladder has never been published under either name. So the rename retracts nothing and breaks no citation, and was cheaper than I described. former_name= stays, but for internal continuity only: research notes, prior branches and the author's CV and profile carry the old label, and this campaign's measurements against takum/tekum/posit were recorded under it. The gate's message says that now instead of citing papers that do not cite us. Two other things in the same header. It was mangled by an earlier string replacement, which joined two sentences into one, and it did not state the reason the name claims the encoding rather than the radix: a genuine ternary-radix float measures 0.331 positions per number worse at equal width, so claiming radix 3 would claim the thing this format declines. Both fixed, along with the standing warning that a gft* glob swallows gfternary -- which has already cost a deleted spec and a dropped index entry. Co-Authored-By: Claude Opus 5 --- docs/NOW.md | 12 +++++++++++- specs/numeric/formats_catalog.t27 | 21 +++++++++++++++++++-- tools/check_catalog_integrity.py | 7 +++++-- 3 files changed, 35 insertions(+), 5 deletions(-) diff --git a/docs/NOW.md b/docs/NOW.md index 81b201846a..eddf976f67 100644 --- a/docs/NOW.md +++ b/docs/NOW.md @@ -1,3 +1,13 @@ +# NOW -- correction: GF-T was never published (2026-08-09) + +Last updated: 2026-08-09 + +## numeric: fix the stated reason for former_name= (Refs #2001) + +- I justified `former_name="GF-T{N}"` by claiming arXiv:2606.05017 and arXiv:2606.09686 cite the old name. **They do not.** 2606.05017 is the binary GF family -- its source, `docs/arxiv-submission/trinity-gf16.tex`, contains zero occurrences of "GF-T". 2606.09686 is this catalog, and the only commit introducing an `id=gft` row is from 2026-08-09 +- Consequence: the rename **retracts nothing and breaks no citation**, and was cheaper than I described it. `former_name=` is kept for internal continuity -- research notes, prior branches, and the author's CV and profile carry the old label, and this campaign's measurements against takum/tekum/posit were recorded under it +- Corrected in the catalog header, in `tools/check_catalog_integrity.py`, and in the prior NOW entry rather than left standing + # NOW -- gfternary restored, and a gate so a glob cannot do that again (2026-08-09) Last updated: 2026-08-09 @@ -5,7 +15,7 @@ Last updated: 2026-08-09 ## numeric: restore gfternary.t27, alias the former name, gate both (Refs #2001) - **`specs/numeric/gfternary.t27` was deleted by my own `rm -f specs/numeric/gft*.t27`** during the TEF rename. It is a DIFFERENT object -- a 2-bit {-phi, 0, +phi} alphabet, not a float -- that merely shares a prefix with the old GF-T names. Restored from `origin/master`, byte-identical by SHA-256, and it typechecks. The same glob had already dropped it from the pack index earlier the same day: twice is a pattern -- **`former_name="GF-T{N}"` on every TEF row.** Renaming the ladder does not retract its measurements: arXiv:2606.05017 and arXiv:2606.09686 cite GF-T, and it labels every published comparison against takum / tekum / posit. The old name stays searchable, and the catalog header says why +- **`former_name="GF-T{N}"` on every TEF row -- for internal continuity, NOT for citation compatibility.** Correcting myself: the ladder has never been published under either name. arXiv:2606.05017 is the binary GF family and does not mention GF-T; arXiv:2606.09686 is this catalog, which had zero GF-T rows until 2026-08-09. The rename retracts nothing and breaks no citation. The old label survives in research notes, prior branches and the author's profile, which is reason enough to keep it searchable - New gate `tools/check_catalog_integrity.py`: every `source=` resolves, the three prefix-sharing neighbours (`gfternary`, the binary `gf*` ladder, the `tef*` ladder) are each present **on disk** and distinct, and the former name is still there. Verified red on each of those failures individually, not just green on the happy path - The catalog row alone was never enough -- `gfternary`'s row survived while its spec file did not, and nothing noticed diff --git a/specs/numeric/formats_catalog.t27 b/specs/numeric/formats_catalog.t27 index 3291eaccba..028666f959 100644 --- a/specs/numeric/formats_catalog.t27 +++ b/specs/numeric/formats_catalog.t27 @@ -271,8 +271,25 @@ module FormatsCatalog { // CATALOG: id=gf1024 name="GF1024 (rule-derived)" bits=1024 s=1 e=391 m=632 bias=2^390-1 phi_distance=0.0006 storage=u1024_software cluster=GoldenFloat status=Open standard="this work; rule e=round(1023/phi^2)=391; lowest phi-distance in the ladder" use_case="OPEN R&D: limit-of-ladder phi alignment (extrapolation, no RTL)" gf_relation=experimental source="specs/numeric/gf1024.t27" // --------------------------------------------------------------------- - // TEF -- Ternary-Exponent Float. The exponent FIELD is balanced ternary; Distinct from GFTernary (a 2-bit - // {-phi, 0, +phi} alphabet) and from the binary GF ladder above. + // TEF -- Ternary-Exponent Float. The exponent FIELD is balanced ternary; the + // RADIX is binary. A genuine ternary-radix float (scaling by 3^e, as Ternary27 + // does) measures 0.331 positions per number worse at equal width, so the name + // deliberately claims the encoding and not the radix. + // + // Distinct from GFTernary (a 2-bit {-phi, 0, +phi} alphabet, not a float at + // all) and from the binary GF ladder above. A glob of gft* matches gfternary; + // it has already cost this repository a deleted spec and a dropped pack index + // entry. Match tef[0-9]+ or gft[0-9]+, never a bare prefix. + // + // FORMER NAME: GF-T (GF-T4 .. GF-T1024), renamed 2026-08-09, carried in + // former_name= on every row. The ladder has NEVER been published under either + // name -- arXiv:2606.05017 is the binary GF family and contains no occurrence + // of "GF-T", and arXiv:2606.09686 is this catalog, which had zero GF-T rows + // until they were added on 2026-08-09. The rename therefore retracts nothing + // and breaks no citation. former_name= is for internal continuity only: + // research notes, prior branches and the author's CV and profile carry the old + // label, and this campaign's measurements against takum/tekum/posit were + // recorded under it. // // Two fields below need reading with care: // e= is a count of balanced-ternary TRITS, not bits. The bit-equivalent diff --git a/tools/check_catalog_integrity.py b/tools/check_catalog_integrity.py index 6a6ea9e204..2055c30eaa 100644 --- a/tools/check_catalog_integrity.py +++ b/tools/check_catalog_integrity.py @@ -49,9 +49,12 @@ def main(): if not tef or not gf or tef & gf: problems.append(f"COLLAPSED tef={len(tef)} gf={len(gf)} overlap={sorted(tef & gf)}") - # 4. The former name must stay searchable: renaming is not retraction. + # 4. The former name must stay searchable. Not for citation reasons -- the + # ladder has never been published under either name -- but because research + # notes, prior branches and the author's own profile still use it, and every + # measurement against takum/tekum/posit was recorded under the old label. if 'former_name="GF-T16"' not in text: - problems.append('LOST former_name="GF-T16" (arXiv cites the old name)') + problems.append('LOST former_name="GF-T16" (internal continuity)') if problems: for p in problems: From 048c93fe2674f8ff7f1d25b648a6574b3844b096 Mon Sep 17 00:00:00 2001 From: Dmitrii Vasilev Date: Sun, 9 Aug 2026 20:21:55 +0700 Subject: [PATCH 2/9] Map the whole ternary landscape, ours and the market's (Refs #2001) The distinction the map turns on: almost everything the market calls a ternary format is a ternary WEIGHT QUANTISER, not a ternary NUMBER. BitNet b1.58, TWN, TernaryBERT, PTQTP, Sherry, CAT-Q, TWLA, BitNet v2, RobuQ and PT2-LLM all put {-1, 0, +1} in the weights and keep binary floats for activations and accumulation. None of them defines a ternary number. That makes them our market rather than our competitors: they create demand for an activation format and do not supply one. Real ternary number formats are two. Ternary27 scales by 3^e; TEF scales by 2^e with only the exponent encoded in balanced ternary. That comparison is already measured -- kappa(r) = (r-1)^2/(r ln r) gives 0.721 at radix 2 and 1.214 at radix 3, so radix 3 buys 1.585x of range for 1.683x of error, a net loss of 0.331 positions per number. Ours are three objects that get confused constantly and are now listed together: the TEF ladder (ternary exponent, binary radix, nine rungs, six measured in silicon), GFTernary (a 2-bit {-phi, 0, +phi} alphabet, not a float at all), and TF3 (an 8-bit container for ternary weights whose spec exists but which is absent from the catalogue). former_name="GF-T{N}" is restored on the eight rungs that lost it in the squash merge; only tef16 had kept it. The positioning that follows is stated with its limit. The measured result -- fixed fields beat tapered ones by 2.4-6.4x in throughput per LUT on a ternary network -- points exactly at the gap those quantisers leave. But "TEF is best" does not survive a fair comparison; it sits mid-pack among fixed fields. What sells is the group boundary, not the position inside the group. The quantiser list is assembled from surveys and abstracts rather than full readings, and the file says so: any public claim of "first" or "only" needs it checked paper by paper. Co-Authored-By: Claude Opus 5 --- docs/TERNARY_LANDSCAPE.md | 66 +++++++++++++++++++++++++++++++ specs/numeric/formats_catalog.t27 | 16 ++++---- 2 files changed, 74 insertions(+), 8 deletions(-) create mode 100644 docs/TERNARY_LANDSCAPE.md diff --git a/docs/TERNARY_LANDSCAPE.md b/docs/TERNARY_LANDSCAPE.md new file mode 100644 index 0000000000..f0a96bbddb --- /dev/null +++ b/docs/TERNARY_LANDSCAPE.md @@ -0,0 +1,66 @@ +# Тернарные форматы: полная карта — наши и конкуренты + +## Различие, без которого карта бессмысленна + +**Почти всё, что рынок называет «тернарным форматом», — это тернарный КВАНТОВАТЕЛЬ +ВЕСОВ, а не тернарное ЧИСЛО.** BitNet, TWN, TernaryBERT кладут `{−1, 0, +1}` в веса +и продолжают считать активации и накопление обычными двоичными числами. + +Настоящих тернарных *числовых форматов* на рынке единицы. + +## Наши + +| формат | что это | разрядность | статус | +|---|---|---|---| +| **TEF4…TEF1024** | float с **тернарной ЭКСПОНЕНТОЙ**, радикс шкалы **двоичный** | 4…1024 | 9 ступеней в SSOT, 6 измерены на кремнии | +| прежнее имя | **GF-T4…GF-T1024** | | `former_name=` в каждой строке каталога | +| **GFTernary** | 2-битный **АЛФАВИТ** `{−φ, 0, +φ}` — не число с плавающей точкой | 2 | в каталоге, есть RTL и конформанс | +| **TF3** | 8-битный **контейнер** для тернарных весов, `[S1 E3 M4]` | 8 | спека есть, **в каталоге отсутствует** | + +⚠️ Три объекта, которые постоянно путают. `gft*` как глоб матчит `gfternary` — это +уже стоило удалённой спеки. Матчить `tef[0-9]+`. + +## Конкуренты: квантователи весов (не числовые форматы) + +| название | веса | ключевое | ссылка | +|---|---|---|---| +| **BitNet b1.58** | `{−1,0,+1}` | лидер рынка; умножение → сложение; ≥3B параметров держит уровень fp | [обзор](https://www.emergentmind.com/topics/bitnet-b1-58) | +| **TWN** | `{−1,0,+1}` × α | масштаб α обучается послойно; предполагает гауссовы веса | — | +| **TernaryBERT** | `{−1,0,+1}` | тернаризация + дистилляция знаний | [EMNLP 2020](https://aclanthology.org/2020.emnlp-main.37.pdf) | +| **PTQTP** | трит-плоскости | структурное разложение, инференс без умножений | [OpenReview](https://openreview.net/forum?id=0mqsIlMtfm) | +| **Sherry** | 1.25 бита | тернар + мелкозернистая разрежённость | [arXiv:2601.07892](https://arxiv.org/pdf/2601.07892) | +| **CAT-Q**, **TWLA**, **BitNet v2**, **RobuQ**, **PT2-LLM** | `{−1,0,+1}` | послетренировочная тернаризация, 2025–2026 | [CAT-Q](https://arxiv.org/pdf/2606.26650), [TWLA](https://arxiv.org/html/2606.13054v1) | + +**Ни один из них не определяет тернарное число.** Все они — про то, как загнать +веса в три состояния, и все оставляют активации двоичными. **Это наш рынок, а не +наши конкуренты:** они создают спрос на формат активаций, которым сами не +занимаются. + +## Конкуренты: настоящие тернарные числа + +| название | радикс шкалы | раскладка | наша оценка | +|---|---|---|---| +| **Ternary27** | **3** (`s·3^e`) | 2 трита типа + 1 знак + 5 экспонента + 19 мантисса = 27 | по Т8 радикс 3 **хуже на 0.331 позиции на число** при равной ширине | +| **TEF** (наш) | **2** (`s·2^e`) | 1 + Et тритов + M бит | тернарна только кодировка экспоненты | + +**Это единственное прямое сравнение числовых форматов в тернарном мире**, и оно +измерено: `κ(r) = (r−1)²/(r·ln r)`, `κ(2) = 0.721`, `κ(3) = 1.214`. Радикс 3 даёт +диапазон ×1.585 ценой ошибки ×1.683 — чистый убыток 0.331 позиции. + +## Что из этого следует для позиционирования + +1. **Рынок тернарных весов огромен и растёт** — BitNet и все производные. Умножения + в них нет по построению. +2. **Формата активаций для него нет.** Все перечисленные держат активации в fp16 или + int8, то есть в двоичном формате, спроектированном не под этот тракт. +3. **Наш измеренный результат бьёт ровно туда:** на тернарной сети фиксированное + поле опережает тейперное в **2.4–6.4×** по пропускной способности на площадь. +4. **Но не «TEF лучший»:** при честном сравнении он в середине группы фиксированных + полей. Продавать надо границу групп, а не место внутри группы. + +## Оговорка + +Список квантователей собран по обзорам и аннотациям, а не по прочитанным целиком +статьям — кроме BlockDialect, прочитанного полностью в другой линии работы. Перед +любой публичной заявкой о «единственном» или «первом» этот список надо проверять +статья за статьёй. diff --git a/specs/numeric/formats_catalog.t27 b/specs/numeric/formats_catalog.t27 index 028666f959..76812c77b2 100644 --- a/specs/numeric/formats_catalog.t27 +++ b/specs/numeric/formats_catalog.t27 @@ -301,15 +301,15 @@ module FormatsCatalog { // while TEF sizes its exponent for RANGE and takes M = N-1-Et. // The two ladders optimise different axes; the field makes it visible. // --------------------------------------------------------------------- - // CATALOG: id=tef4 name="TEF4" bits=4 s=1 e=2 m=1 bias=4 phi_distance=2.552 storage=u4 cluster=GoldenFloat status=Verified standard="this work; e is 2 balanced-ternary TRITS not bits (3.17 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 12 LUT 161.1 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef4.t27" - // CATALOG: id=tef8 name="TEF8" bits=8 s=1 e=3 m=4 bias=13 phi_distance=0.571 storage=u8 cluster=GoldenFloat status=Verified standard="this work; e is 3 balanced-ternary TRITS not bits (4.75 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 50 LUT 153.2 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef8.t27" + // CATALOG: id=tef4 name="TEF4" former_name="GF-T4" bits=4 s=1 e=2 m=1 bias=4 phi_distance=2.552 storage=u4 cluster=GoldenFloat status=Verified standard="this work; e is 2 balanced-ternary TRITS not bits (3.17 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 12 LUT 161.1 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef4.t27" + // CATALOG: id=tef8 name="TEF8" former_name="GF-T8" bits=8 s=1 e=3 m=4 bias=13 phi_distance=0.571 storage=u8 cluster=GoldenFloat status=Verified standard="this work; e is 3 balanced-ternary TRITS not bits (4.75 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 50 LUT 153.2 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef8.t27" // CATALOG: id=tef16 name="TEF16" former_name="GF-T16" bits=16 s=1 e=4 m=11 bias=40 phi_distance=0.086 storage=u16 cluster=GoldenFloat status=Verified standard="this work; e is 4 balanced-ternary TRITS not bits (6.34 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 212 LUT 131.7 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef16.t27" - // CATALOG: id=tef32 name="TEF32" bits=32 s=1 e=6 m=25 bias=364 phi_distance=0.238 storage=u32 cluster=GoldenFloat status=Verified standard="this work; e is 6 balanced-ternary TRITS not bits (9.51 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 1477 LUT 83.3 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef32.t27" - // CATALOG: id=tef64 name="TEF64" bits=64 s=1 e=7 m=56 bias=1093 phi_distance=0.420 storage=u64 cluster=GoldenFloat status=Verified standard="this work; e is 7 balanced-ternary TRITS not bits (11.09 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 7479 LUT 48.2 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef64.t27" - // CATALOG: id=tef128 name="TEF128" bits=128 s=1 e=8 m=119 bias=3280 phi_distance=0.511 storage=u128 cluster=GoldenFloat status=Open standard="this work; e is 8 balanced-ternary TRITS not bits (12.68 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef128.t27" - // CATALOG: id=tef256 name="TEF256" bits=256 s=1 e=9 m=246 bias=9841 phi_distance=0.560 storage=u256_software cluster=GoldenFloat status=Open standard="this work; e is 9 balanced-ternary TRITS not bits (14.26 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef256.t27" - // CATALOG: id=tef512 name="TEF512" bits=512 s=1 e=10 m=501 bias=29524 phi_distance=0.586 storage=u512_software cluster=GoldenFloat status=Open standard="this work; e is 10 balanced-ternary TRITS not bits (15.85 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef512.t27" - // CATALOG: id=tef1024 name="TEF1024" bits=1024 s=1 e=11 m=1012 bias=88573 phi_distance=0.601 storage=u1024_software cluster=GoldenFloat status=Open standard="this work; e is 11 balanced-ternary TRITS not bits (17.43 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef1024.t27" + // CATALOG: id=tef32 name="TEF32" former_name="GF-T32" bits=32 s=1 e=6 m=25 bias=364 phi_distance=0.238 storage=u32 cluster=GoldenFloat status=Verified standard="this work; e is 6 balanced-ternary TRITS not bits (9.51 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 1477 LUT 83.3 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef32.t27" + // CATALOG: id=tef64 name="TEF64" former_name="GF-T64" bits=64 s=1 e=7 m=56 bias=1093 phi_distance=0.420 storage=u64 cluster=GoldenFloat status=Verified standard="this work; e is 7 balanced-ternary TRITS not bits (11.09 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 7479 LUT 48.2 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef64.t27" + // CATALOG: id=tef128 name="TEF128" former_name="GF-T128" bits=128 s=1 e=8 m=119 bias=3280 phi_distance=0.511 storage=u128 cluster=GoldenFloat status=Open standard="this work; e is 8 balanced-ternary TRITS not bits (12.68 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef128.t27" + // CATALOG: id=tef256 name="TEF256" former_name="GF-T256" bits=256 s=1 e=9 m=246 bias=9841 phi_distance=0.560 storage=u256_software cluster=GoldenFloat status=Open standard="this work; e is 9 balanced-ternary TRITS not bits (14.26 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef256.t27" + // CATALOG: id=tef512 name="TEF512" former_name="GF-T512" bits=512 s=1 e=10 m=501 bias=29524 phi_distance=0.586 storage=u512_software cluster=GoldenFloat status=Open standard="this work; e is 10 balanced-ternary TRITS not bits (15.85 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef512.t27" + // CATALOG: id=tef1024 name="TEF1024" former_name="GF-T1024" bits=1024 s=1 e=11 m=1012 bias=88573 phi_distance=0.601 storage=u1024_software cluster=GoldenFloat status=Open standard="this work; e is 11 balanced-ternary TRITS not bits (17.43 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef1024.t27" fn gf1024() -> str { return "gf1024"; } // GF hybrids / experimental compositions (Section 12.5). From f68f61988f4f12c67945a1f36e471ff584f96fa5 Mon Sep 17 00:00:00 2001 From: Dmitrii Vasilev Date: Sun, 9 Aug 2026 20:31:20 +0700 Subject: [PATCH 3/9] feat(numeric): the ladder is TNF -- Ternary Network Float (Refs #2001) GF and this ladder are not the same lineage, and conflating them is what produced two wrong names in a row. GF is built on the golden ratio: it sizes its exponent by e = round((N-1)/phi^2), which puts e/m at 1/phi by construction. This ladder deliberately left phi in order to be a reference, and its phi-distance therefore RISES with N -- which the catalog already recorded as structural rather than as a defect, without anyone drawing the conclusion that the name was wrong. TNF says what it is built for. In a ternary network the weight is in {-1, 0, +1}, w*a is a select rather than a multiply, and the multiplier disappears -- so the decoder stops being overhead amortised against thousands of LUTs and becomes the body of a datapath measured in hundreds. That is the workload this ladder is a reference for, and the measurements in trinity-fpga/fpga/tnet are on exactly that datapath. Renamed by explicit rung list, never by glob: specs/numeric/tnf*.t27, catalog ids tnfN, modules triformat_tnfN, conformance packs, the integrity gate's neighbour check, the numeric SSOT document and the erratum. Former names ride along in former_name= -- GF-T through 2026, then TEF for one day. Neighbours verified present afterwards rather than assumed: gfternary.t27 and gf16.t27 are both still there. A gft* glob deleted the first of them once already in this campaign, and the gate that now catches it was written because of that. Gates: catalog count SSOT == fresh regen == 92, integrity CLEAN with 17 GF + 9 TNF + gfternary present and distinct, t27c clean on all nine specs. Co-Authored-By: Claude Opus 5 --- conformance/vectors/INDEX_all_formats.json | 72 +++++++-------- ...ce_v0.json => tnf1024_conformance_v0.json} | 92 +++++++++---------- ...nce_v0.json => tnf128_conformance_v0.json} | 92 +++++++++---------- ...ance_v0.json => tnf16_conformance_v0.json} | 92 +++++++++---------- ...nce_v0.json => tnf256_conformance_v0.json} | 92 +++++++++---------- ...ance_v0.json => tnf32_conformance_v0.json} | 92 +++++++++---------- ...mance_v0.json => tnf4_conformance_v0.json} | 68 +++++++------- ...nce_v0.json => tnf512_conformance_v0.json} | 92 +++++++++---------- ...ance_v0.json => tnf64_conformance_v0.json} | 92 +++++++++---------- ...mance_v0.json => tnf8_conformance_v0.json} | 92 +++++++++---------- docs/NOW.md | 13 +++ docs/NUMERIC_FORMATS_SSOT.md | 22 ++--- docs/TERNARY_LANDSCAPE.md | 6 +- specs/numeric/formats_catalog.t27 | 26 +++--- specs/numeric/{tef1024.t27 => tnf1024.t27} | 4 +- specs/numeric/{tef128.t27 => tnf128.t27} | 4 +- specs/numeric/{tef16.t27 => tnf16.t27} | 4 +- specs/numeric/{tef256.t27 => tnf256.t27} | 4 +- specs/numeric/{tef32.t27 => tnf32.t27} | 4 +- specs/numeric/{tef4.t27 => tnf4.t27} | 6 +- specs/numeric/{tef512.t27 => tnf512.t27} | 4 +- specs/numeric/{tef64.t27 => tnf64.t27} | 4 +- specs/numeric/{tef8.t27 => tnf8.t27} | 4 +- tools/check_catalog_integrity.py | 10 +- 24 files changed, 503 insertions(+), 488 deletions(-) rename conformance/vectors/{tef1024_conformance_v0.json => tnf1024_conformance_v0.json} (85%) rename conformance/vectors/{tef128_conformance_v0.json => tnf128_conformance_v0.json} (66%) rename conformance/vectors/{tef16_conformance_v0.json => tnf16_conformance_v0.json} (79%) rename conformance/vectors/{tef256_conformance_v0.json => tnf256_conformance_v0.json} (71%) rename conformance/vectors/{tef32_conformance_v0.json => tnf32_conformance_v0.json} (77%) rename conformance/vectors/{tef4_conformance_v0.json => tnf4_conformance_v0.json} (81%) rename conformance/vectors/{tef512_conformance_v0.json => tnf512_conformance_v0.json} (78%) rename conformance/vectors/{tef64_conformance_v0.json => tnf64_conformance_v0.json} (74%) rename conformance/vectors/{tef8_conformance_v0.json => tnf8_conformance_v0.json} (80%) rename specs/numeric/{tef1024.t27 => tnf1024.t27} (96%) rename specs/numeric/{tef128.t27 => tnf128.t27} (96%) rename specs/numeric/{tef16.t27 => tnf16.t27} (97%) rename specs/numeric/{tef256.t27 => tnf256.t27} (96%) rename specs/numeric/{tef32.t27 => tnf32.t27} (95%) rename specs/numeric/{tef4.t27 => tnf4.t27} (91%) rename specs/numeric/{tef512.t27 => tnf512.t27} (96%) rename specs/numeric/{tef64.t27 => tnf64.t27} (96%) rename specs/numeric/{tef8.t27 => tnf8.t27} (94%) diff --git a/conformance/vectors/INDEX_all_formats.json b/conformance/vectors/INDEX_all_formats.json index e8dda47ae7..ee82136896 100644 --- a/conformance/vectors/INDEX_all_formats.json +++ b/conformance/vectors/INDEX_all_formats.json @@ -678,85 +678,85 @@ "witnesses": 0 }, { - "id": "tef1024", - "file": "tef1024_conformance_v0.json", + "id": "tf32", + "file": "tf32_conformance_v0.json", + "kind": "bitexact", + "n_vectors": 8, + "source": "generated by gen_all_formats.py", + "sha256": "b35c334092b49dad9a944d37a91697f08f442b633142e81c69296c12bac0055d", + "witnesses": 0 + }, + { + "id": "tnf1024", + "file": "tnf1024_conformance_v0.json", "kind": "bitexact", "n_vectors": 22, "source": "generated from conformance/gft_ref.py (round-trip verified 90/90)", - "sha256": "a8cf707ee4dfab432287f6a7e7a7bb7c07054d9729606b23cc3658318bb0ca31" + "sha256": "6fd871f441c07dd42eefa59977b8b7b12e597fc087264bb610ea5bd19667fd22" }, { - "id": "tef128", - "file": "tef128_conformance_v0.json", + "id": "tnf128", + "file": "tnf128_conformance_v0.json", "kind": "bitexact", "n_vectors": 22, "source": "generated from conformance/gft_ref.py (round-trip verified 90/90)", - "sha256": "df4b8956e7ed1977eb4baefb8f790d54b73bf370142e09f2ed7032d9b742709b" + "sha256": "bf3711882fc8ffb3a93f5b326b08e200960a45d07658dff6dd7401c3ac736dd0" }, { - "id": "tef16", - "file": "tef16_conformance_v0.json", + "id": "tnf16", + "file": "tnf16_conformance_v0.json", "kind": "bitexact", "n_vectors": 22, "source": "regenerated at M=11 from conformance/gft_ref.py", - "sha256": "57944f2a2bc54573d49210f644076233c7e31421d04a8288260eb3a98625f135" + "sha256": "12a380e7c424f89d40d4672edaec97df40d944e79bb9043817a172ac76f10d02" }, { - "id": "tef256", - "file": "tef256_conformance_v0.json", + "id": "tnf256", + "file": "tnf256_conformance_v0.json", "kind": "bitexact", "n_vectors": 22, "source": "generated from conformance/gft_ref.py (round-trip verified 90/90)", - "sha256": "8a1b04d9a393b547de91b00c2ea533f43266eaf458be21840798a7c557fadf8f" + "sha256": "96cb7c3e93acba412bc98dad59c36ce95e3496827e8cb63f25f4791e4cadd0c9" }, { - "id": "tef32", - "file": "tef32_conformance_v0.json", + "id": "tnf32", + "file": "tnf32_conformance_v0.json", "kind": "bitexact", "n_vectors": 22, "source": "generated from conformance/gft_ref.py (round-trip verified 90/90)", - "sha256": "49989871fd377e2ba6e9c9c577ef21b8764d5c79091246eb4f6ed74bd79aab80" + "sha256": "c2cf13fa69f30f21b12792b02ee7cc319e28c5b675a5cd210069385ef4820cba" }, { - "id": "tef4", - "file": "tef4_conformance_v0.json", + "id": "tnf4", + "file": "tnf4_conformance_v0.json", "kind": "bitexact", "n_vectors": 16, "source": "generated from conformance/gft_ref.py (round-trip verified 90/90)", - "sha256": "2d7d3832be8c23388e90baa9ca1f15e07a4641f247a7414b0047284a805251da" + "sha256": "0894a97c5baf4c1d0967f46fa539b2329613065c9e6b22cadc2a251dab38199b" }, { - "id": "tef512", - "file": "tef512_conformance_v0.json", + "id": "tnf512", + "file": "tnf512_conformance_v0.json", "kind": "bitexact", "n_vectors": 22, "source": "generated from conformance/gft_ref.py (round-trip verified 90/90)", - "sha256": "202496c6f573d79a10a256b18c83d2ada45a6e8f044dfe6fefa1a73998d6cb1e" + "sha256": "12649482f520b6506686b1fd2dd84d67b2ad7f8e972e3afd502f9cea1f7b966a" }, { - "id": "tef64", - "file": "tef64_conformance_v0.json", + "id": "tnf64", + "file": "tnf64_conformance_v0.json", "kind": "bitexact", "n_vectors": 22, "source": "generated from conformance/gft_ref.py (round-trip verified 90/90)", - "sha256": "ca7e8c6d05207009cf13f63628bfc45c4be9bf2f90abcfe1dc10a1d14450c48c" + "sha256": "ffaa681c02de5cf5a69bcbde927dc9b4a6787e2b47abbbc1b301e89205417b20" }, { - "id": "tef8", - "file": "tef8_conformance_v0.json", + "id": "tnf8", + "file": "tnf8_conformance_v0.json", "kind": "bitexact", "n_vectors": 22, "source": "generated from conformance/gft_ref.py (round-trip verified 90/90)", - "sha256": "5509c7570c5395eed0a91b694a6cdc2a62501e00f938449ba72e1cc7a721fe0c" - }, - { - "id": "tf32", - "file": "tf32_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "b35c334092b49dad9a944d37a91697f08f442b633142e81c69296c12bac0055d", - "witnesses": 0 + "sha256": "5bdeeb8449312ca316fa7321fc74dedaf335b90648e916ddb0db155dd89aef0b" }, { "id": "unum_i", diff --git a/conformance/vectors/tef1024_conformance_v0.json b/conformance/vectors/tnf1024_conformance_v0.json similarity index 85% rename from conformance/vectors/tef1024_conformance_v0.json rename to conformance/vectors/tnf1024_conformance_v0.json index 9db9434c08..c2f49950cc 100644 --- a/conformance/vectors/tef1024_conformance_v0.json +++ b/conformance/vectors/tnf1024_conformance_v0.json @@ -1,7 +1,7 @@ { "schema": "t27-conformance/v0.1", - "format": "TEF1024", - "ssot": "specs/numeric/tef1024.t27", + "format": "TNF1024", + "ssot": "specs/numeric/tnf1024.t27", "anchor_identity": "phi^2 + 1/phi^2 = 3", "anchor_check": { "value": 3.0, @@ -20,8 +20,8 @@ "name": "pos_zero", "input_f64": 0.0, "input_f64_hex": "0x0000000000000000", - "tef1024_bits_int": 0, - "tef1024_bits_hex": "0x0", + "tnf1024_bits_int": 0, + "tnf1024_bits_hex": "0x0", "decoded_f64": 0.0, "decoded_f64_hex": "0x0000000000000000", "abs_error": 0.0, @@ -31,8 +31,8 @@ "name": "pow2_-1000", "input_f64": 9.332636185032189e-302, "input_f64_hex": "0x0170000000000000", - "tef1024_bits_int": 3843490744611757592470176842601739819265798290452016931007346801080596586502718712016767452283983191400769466016107795534729784283297096406632355479343424681185123957738219028833401923129864306719449422207749074754507658619330200663895261921238247959010276921919256810489965861467403368155113930628462446379008, - "tef1024_bits_hex": "0x156150000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3843490744611757592470176842601739819265798290452016931007346801080596586502718712016767452283983191400769466016107795534729784283297096406632355479343424681185123957738219028833401923129864306719449422207749074754507658619330200663895261921238247959010276921919256810489965861467403368155113930628462446379008, + "tnf1024_bits_hex": "0x156150000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 9.332636185032189e-302, "decoded_f64_hex": "0x0170000000000000", "abs_error": 0.0, @@ -42,8 +42,8 @@ "name": "neg_pow2_-1000", "input_f64": -9.332636185032189e-302, "input_f64_hex": "0x8170000000000000", - "tef1024_bits_int": 15348726807730579401937730063651498114420850955682778996506871995175487838054780352510110000918065496752456754327876970424892329487419760246174591040269768641362269136929610086516743977609614330364446731141189443960149302289247825078225700995851191137464709605732779897846589601530105211664576735724412791160832, - "tef1024_bits_hex": "0x556150000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 15348726807730579401937730063651498114420850955682778996506871995175487838054780352510110000918065496752456754327876970424892329487419760246174591040269768641362269136929610086516743977609614330364446731141189443960149302289247825078225700995851191137464709605732779897846589601530105211664576735724412791160832, + "tnf1024_bits_hex": "0x556150000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -9.332636185032189e-302, "decoded_f64_hex": "0x8170000000000000", "abs_error": 0.0, @@ -53,8 +53,8 @@ "name": "onehalf_2e-1000", "input_f64": 1.3998954277548283e-301, "input_f64_hex": "0x0178000000000000", - "tef1024_bits_int": 3843512689108032767224909866346744568102878588022560660335627249088550411292245750708556112986781336851943919155009147023176764116032547385223968375758297663866322415733021868858460065490655474455547988257914124193688424995145916296571223092272249524835125963729643112528325230027698592729858173225670652461056, - "tef1024_bits_hex": "0x156158000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3843512689108032767224909866346744568102878588022560660335627249088550411292245750708556112986781336851943919155009147023176764116032547385223968375758297663866322415733021868858460065490655474455547988257914124193688424995145916296571223092272249524835125963729643112528325230027698592729858173225670652461056, + "tnf1024_bits_hex": "0x156158000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.3998954277548283e-301, "decoded_f64_hex": "0x0178000000000000", "abs_error": 0.0, @@ -64,8 +64,8 @@ "name": "pow2_-500", "input_f64": 3.054936363499605e-151, "input_f64_hex": "0x20b0000000000000", - "tef1024_bits_int": 3865435240886932347203200587606488656346095860995746259287794809034421376029757403805428155082128642575222604917459283981709617018748074998245251894216407362383581952541059053891544283921032042818015472372798513935274034435045833339856432955239813783859318732305558848849334421762627942899356527836668528427008, - "tef1024_bits_hex": "0x158090000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3865435240886932347203200587606488656346095860995746259287794809034421376029757403805428155082128642575222604917459283981709617018748074998245251894216407362383581952541059053891544283921032042818015472372798513935274034435045833339856432955239813783859318732305558848849334421762627942899356527836668528427008, + "tnf1024_bits_hex": "0x158090000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 3.054936363499605e-151, "decoded_f64_hex": "0x20b0000000000000", "abs_error": 0.0, @@ -75,8 +75,8 @@ "name": "neg_pow2_-500", "input_f64": -3.054936363499605e-151, "input_f64_hex": "0xa0b0000000000000", - "tef1024_bits_int": 15370671304005754156670753808656246951501148526226508324787320003129312627581819044298770703716210947926909893229228458871872162222870738837787487455142751322560727131732450111574886338400782066463012781306238883140915678104963457754186872029852756962313751416119081936205958161825329786408819332932618873208832, - "tef1024_bits_hex": "0x558090000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 15370671304005754156670753808656246951501148526226508324787320003129312627581819044298770703716210947926909893229228458871872162222870738837787487455142751322560727131732450111574886338400782066463012781306238883140915678104963457754186872029852756962313751416119081936205958161825329786408819332932618873208832, + "tnf1024_bits_hex": "0x558090000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -3.054936363499605e-151, "decoded_f64_hex": "0xa0b0000000000000", "abs_error": 0.0, @@ -86,8 +86,8 @@ "name": "onehalf_2e-500", "input_f64": 4.582404545249407e-151, "input_f64_hex": "0x20b8000000000000", - "tef1024_bits_int": 3865457185383207521957933611351493405183176158566289988616075257042375200819284442497216815784926788026397058056360635470156596851483525976836864790631280345064780410535861893916602426281823210554114038422963563374454800810861548972532394126273815349684167774115945150887693790322923167474100770433876734509056, - "tef1024_bits_hex": "0x158098000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3865457185383207521957933611351493405183176158566289988616075257042375200819284442497216815784926788026397058056360635470156596851483525976836864790631280345064780410535861893916602426281823210554114038422963563374454800810861548972532394126273815349684167774115945150887693790322923167474100770433876734509056, + "tnf1024_bits_hex": "0x158098000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 4.582404545249407e-151, "decoded_f64_hex": "0x20b8000000000000", "abs_error": 0.0, @@ -97,8 +97,8 @@ "name": "pow2_-1", "input_f64": 0.5, "input_f64_hex": "0x3fe0000000000000", - "tef1024_bits_int": 3887335848169556752426758285121227995752232836398388128911681920972338515977742018210511536474677802847326837541008069451795490088728151632674922516259644078219643031354293398899570359990617443444384390437517854237678877499130034750465681647173376477058662459071088283131984244937262068494110639850458198310912, - "tef1024_bits_hex": "0x159fc0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3887335848169556752426758285121227995752232836398388128911681920972338515977742018210511536474677802847326837541008069451795490088728151632674922516259644078219643031354293398899570359990617443444384390437517854237678877499130034750465681647173376477058662459071088283131984244937262068494110639850458198310912, + "tnf1024_bits_hex": "0x159fc0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 0.5, "decoded_f64_hex": "0x3fe0000000000000", "abs_error": 0.0, @@ -108,8 +108,8 @@ "name": "neg_pow2_-1", "input_f64": -0.5, "input_f64_hex": "0xbfe0000000000000", - "tef1024_bits_int": 15392571911288378561894311506170986290907285501629150194411207115067229767529803658703854085108760108199014125852777244341958035292850815472217158077185988038396788210545684456582912414470367467089381699370958223443320521169047659164796120721786319655513095142884611370488607984999963912003573444946408543092736, - "tef1024_bits_hex": "0x559fc0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 15392571911288378561894311506170986290907285501629150194411207115067229767529803658703854085108760108199014125852777244341958035292850815472217158077185988038396788210545684456582912414470367467089381699370958223443320521169047659164796120721786319655513095142884611370488607984999963912003573444946408543092736, + "tnf1024_bits_hex": "0x559fc0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -0.5, "decoded_f64_hex": "0xbfe0000000000000", "abs_error": 0.0, @@ -119,8 +119,8 @@ "name": "onehalf_2e-1", "input_f64": 0.75, "input_f64_hex": "0x3fe8000000000000", - "tef1024_bits_int": 3887357792665831927181491308866232744589313133968931858239962368980292340767269056902300197177475948298501290679909420940242469921463602611266535412674517060900841489349096238924628502351408611180482956487682903676859643874945750383141642818207378042883511500881474585170343613497557293068854882447666404392960, - "tef1024_bits_hex": "0x159fc8000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3887357792665831927181491308866232744589313133968931858239962368980292340767269056902300197177475948298501290679909420940242469921463602611266535412674517060900841489349096238924628502351408611180482956487682903676859643874945750383141642818207378042883511500881474585170343613497557293068854882447666404392960, + "tnf1024_bits_hex": "0x159fc8000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 0.75, "decoded_f64_hex": "0x3fe8000000000000", "abs_error": 0.0, @@ -130,8 +130,8 @@ "name": "pow2_0", "input_f64": 1.0, "input_f64_hex": "0x3ff0000000000000", - "tef1024_bits_int": 3887379737162107101936224332611237493426393431539475587568242816988246165556796095594088857880274093749675743818810772428689449754199053589858148309089390043582039947343899078949686644712199778916581522537847953116040410250761466015817603989241379608708360542691860887208702982057852517643599125044874610475008, - "tef1024_bits_hex": "0x159fd0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3887379737162107101936224332611237493426393431539475587568242816988246165556796095594088857880274093749675743818810772428689449754199053589858148309089390043582039947343899078949686644712199778916581522537847953116040410250761466015817603989241379608708360542691860887208702982057852517643599125044874610475008, + "tnf1024_bits_hex": "0x159fd0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.0, "decoded_f64_hex": "0x3ff0000000000000", "abs_error": 0.0, @@ -141,8 +141,8 @@ "name": "neg_pow2_0", "input_f64": -1.0, "input_f64_hex": "0xbff0000000000000", - "tef1024_bits_int": 15392615800280928911403777553660995788581446096770237653067768011083137417108857736087431406514356399101363032130579947318851994958321717429400383870015734003759185126535290136633028699191949802561578831471288322321682053920679090430148043063854322787162793226505383974565326722120554361153061930140824955256832, - "tef1024_bits_hex": "0x559fd0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 15392615800280928911403777553660995788581446096770237653067768011083137417108857736087431406514356399101363032130579947318851994958321717429400383870015734003759185126535290136633028699191949802561578831471288322321682053920679090430148043063854322787162793226505383974565326722120554361153061930140824955256832, + "tnf1024_bits_hex": "0x559fd0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -1.0, "decoded_f64_hex": "0xbff0000000000000", "abs_error": 0.0, @@ -152,8 +152,8 @@ "name": "onehalf_2e0", "input_f64": 1.5, "input_f64_hex": "0x3ff8000000000000", - "tef1024_bits_int": 3887401681658382276690957356356242242263473729110019316896523264996199990346323134285877518583072239200850196957712123917136429586934504568449761205504263026263238405338701918974744787072990946652680088588013002555221176626577181648493565160275381174533209584502247189247062350618147742218343367642082816557056, - "tef1024_bits_hex": "0x159fd8000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3887401681658382276690957356356242242263473729110019316896523264996199990346323134285877518583072239200850196957712123917136429586934504568449761205504263026263238405338701918974744787072990946652680088588013002555221176626577181648493565160275381174533209584502247189247062350618147742218343367642082816557056, + "tnf1024_bits_hex": "0x159fd8000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.5, "decoded_f64_hex": "0x3ff8000000000000", "abs_error": 0.0, @@ -163,8 +163,8 @@ "name": "pow2_1", "input_f64": 2.0, "input_f64_hex": "0x4000000000000000", - "tef1024_bits_int": 3887423626154657451445690380101246991100554026680563046224803713004153815135850172977666179285870384652024650096613475405583409419669955547041374101919136008944436863333504758999802929433782114388778654638178051994401943002392897281169526331309382740358058626312633491285421719178442966793087610239291022639104, - "tef1024_bits_hex": "0x159fe0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3887423626154657451445690380101246991100554026680563046224803713004153815135850172977666179285870384652024650096613475405583409419669955547041374101919136008944436863333504758999802929433782114388778654638178051994401943002392897281169526331309382740358058626312633491285421719178442966793087610239291022639104, + "tnf1024_bits_hex": "0x159fe0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 2.0, "decoded_f64_hex": "0x4000000000000000", "abs_error": 0.0, @@ -174,8 +174,8 @@ "name": "neg_pow2_1", "input_f64": -2.0, "input_f64_hex": "0xc000000000000000", - "tef1024_bits_int": 15392659689273479260913243601151005286255606691911325111724328907099045066687911813471008727919952690003711938408382650295745954623792619386583609662845479969121582042524895816683144983913532138033775963571618421200043586672310521695499965405922325918812491310126156578642045459241144810302550415335241367420928, - "tef1024_bits_hex": "0x559fe0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 15392659689273479260913243601151005286255606691911325111724328907099045066687911813471008727919952690003711938408382650295745954623792619386583609662845479969121582042524895816683144983913532138033775963571618421200043586672310521695499965405922325918812491310126156578642045459241144810302550415335241367420928, + "tnf1024_bits_hex": "0x559fe0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -2.0, "decoded_f64_hex": "0xc000000000000000", "abs_error": 0.0, @@ -185,8 +185,8 @@ "name": "onehalf_2e1", "input_f64": 3.0, "input_f64_hex": "0x4008000000000000", - "tef1024_bits_int": 3887445570650932626200423403846251739937634324251106775553084161012107639925377211669454839988668530103199103235514826894030389252405406525632986998334008991625635321328307599024861071794573282124877220688343101433582709378208612913845487502343384306182907668123019793323781087738738191367831852836499228721152, - "tef1024_bits_hex": "0x159fe8000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3887445570650932626200423403846251739937634324251106775553084161012107639925377211669454839988668530103199103235514826894030389252405406525632986998334008991625635321328307599024861071794573282124877220688343101433582709378208612913845487502343384306182907668123019793323781087738738191367831852836499228721152, + "tnf1024_bits_hex": "0x159fe8000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 3.0, "decoded_f64_hex": "0x4008000000000000", "abs_error": 0.0, @@ -196,8 +196,8 @@ "name": "pow2_500", "input_f64": 3.273390607896142e+150, "input_f64_hex": "0x5f30000000000000", - "tef1024_bits_int": 3909324233437281856669248077615986330506691002083204915848690824942070955083834787382749560678419544924128882720162260875669282489650032181471044723962372724780497942146739104007829005503367515015147572702897392296806786066477098691778775023242945433557402353078162925568071542353077092387841722253080692523008, - "tef1024_bits_hex": "0x15bf10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3909324233437281856669248077615986330506691002083204915848690824942070955083834787382749560678419544924128882720162260875669282489650032181471044723962372724780497942146739104007829005503367515015147572702897392296806786066477098691778775023242945433557402353078162925568071542353077092387841722253080692523008, + "tnf1024_bits_hex": "0x15bf10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 3.273390607896142e+150, "decoded_f64_hex": "0x5f30000000000000", "abs_error": 0.0, @@ -207,8 +207,8 @@ "name": "neg_pow2_500", "input_f64": -3.273390607896142e+150, "input_f64_hex": "0xdf30000000000000", - "tef1024_bits_int": 15414560296556103666136801298665744625661743667313966981348216019036962206635896427876092109312501850275816171031931435765831827693772696021013280284888716684957643121338130161691171059983117538660144881636337761502448429736394723106109214097855888612011835036891686012924695282415778935897304527349031037304832, - "tef1024_bits_hex": "0x55bf10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 15414560296556103666136801298665744625661743667313966981348216019036962206635896427876092109312501850275816171031931435765831827693772696021013280284888716684957643121338130161691171059983117538660144881636337761502448429736394723106109214097855888612011835036891686012924695282415778935897304527349031037304832, + "tnf1024_bits_hex": "0x55bf10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -3.273390607896142e+150, "decoded_f64_hex": "0xdf30000000000000", "abs_error": 0.0, @@ -218,8 +218,8 @@ "name": "onehalf_2e500", "input_f64": 4.910085911844213e+150, "input_f64_hex": "0x5f38000000000000", - "tef1024_bits_int": 3909346177933557031423981101360991079343771299653748645176971272950024779873361826074538221381217690375303335859063612364116262322385483160062657620377245707461696400141541944032887147864158682751246138753062441735987552442292814324454736194276946999382251394888549227606430910913372316962585964850288898605056, - "tef1024_bits_hex": "0x15bf18000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3909346177933557031423981101360991079343771299653748645176971272950024779873361826074538221381217690375303335859063612364116262322385483160062657620377245707461696400141541944032887147864158682751246138753062441735987552442292814324454736194276946999382251394888549227606430910913372316962585964850288898605056, + "tnf1024_bits_hex": "0x15bf18000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 4.910085911844213e+150, "decoded_f64_hex": "0x5f38000000000000", "abs_error": 0.0, @@ -229,8 +229,8 @@ "name": "pow2_1000", "input_f64": 1.0715086071862673e+301, "input_f64_hex": "0x7e70000000000000", - "tef1024_bits_int": 3931268729712456611402271822620735167586988572626934244129138832895895744610873479171410263476564996098582021621513749322649115225101010773083941138835355405978955936949579129065971366294535251113713622867946831477573161882192731367739946057244511258406444163464464963927440102648301667132084319461286774571008, - "tef1024_bits_hex": "0x15de50000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3931268729712456611402271822620735167586988572626934244129138832895895744610873479171410263476564996098582021621513749322649115225101010773083941138835355405978955936949579129065971366294535251113713622867946831477573161882192731367739946057244511258406444163464464963927440102648301667132084319461286774571008, + "tnf1024_bits_hex": "0x15de50000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.0715086071862673e+301, "decoded_f64_hex": "0x7e70000000000000", "abs_error": 0.0, @@ -240,8 +240,8 @@ "name": "neg_pow2_1000", "input_f64": -1.0715086071862673e+301, "input_f64_hex": "0xfe70000000000000", - "tef1024_bits_int": 15436504792831278420869825043670493462742041237857696309628664026990786996162935119664752812110647301450269309933282924212811660429223674612626176699761699366156101116140970186749313420774285274758710931801387200683214805552110355782070385131857454436860876847277988051284063842711003510641547124557237119352832, - "tef1024_bits_hex": "0x55de50000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 15436504792831278420869825043670493462742041237857696309628664026990786996162935119664752812110647301450269309933282924212811660429223674612626176699761699366156101116140970186749313420774285274758710931801387200683214805552110355782070385131857454436860876847277988051284063842711003510641547124557237119352832, + "tnf1024_bits_hex": "0x55de50000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -1.0715086071862673e+301, "decoded_f64_hex": "0xfe70000000000000", "abs_error": 0.0, @@ -251,8 +251,8 @@ "name": "onehalf_2e1000", "input_f64": 1.607262910779401e+301, "input_f64_hex": "0x7e78000000000000", - "tef1024_bits_int": 3931290674208731786157004846365739916424068870197477973457419280903849569400400517863198924179363141549756474760415100811096095057836461751675554035250228388660154394944381969091029508655326418849812188918111880916753928258008447000415907228278512824231293205274851265965799471208596891706828562058494980653056, - "tef1024_bits_hex": "0x15de58000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf1024_bits_int": 3931290674208731786157004846365739916424068870197477973457419280903849569400400517863198924179363141549756474760415100811096095057836461751675554035250228388660154394944381969091029508655326418849812188918111880916753928258008447000415907228278512824231293205274851265965799471208596891706828562058494980653056, + "tnf1024_bits_hex": "0x15de58000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.607262910779401e+301, "decoded_f64_hex": "0x7e78000000000000", "abs_error": 0.0, diff --git a/conformance/vectors/tef128_conformance_v0.json b/conformance/vectors/tnf128_conformance_v0.json similarity index 66% rename from conformance/vectors/tef128_conformance_v0.json rename to conformance/vectors/tnf128_conformance_v0.json index 9efec19c68..8bfcf1a72f 100644 --- a/conformance/vectors/tef128_conformance_v0.json +++ b/conformance/vectors/tnf128_conformance_v0.json @@ -1,7 +1,7 @@ { "schema": "t27-conformance/v0.1", - "format": "TEF128", - "ssot": "specs/numeric/tef128.t27", + "format": "TNF128", + "ssot": "specs/numeric/tnf128.t27", "anchor_identity": "phi^2 + 1/phi^2 = 3", "anchor_check": { "value": 3.0, @@ -20,8 +20,8 @@ "name": "pos_zero", "input_f64": 0.0, "input_f64_hex": "0x0000000000000000", - "tef128_bits_int": 0, - "tef128_bits_hex": "0x0", + "tnf128_bits_int": 0, + "tnf128_bits_hex": "0x0", "decoded_f64": 0.0, "decoded_f64_hex": "0x0000000000000000", "abs_error": 0.0, @@ -31,8 +31,8 @@ "name": "pow2_-1000", "input_f64": 9.332636185032189e-302, "input_f64_hex": "0x0170000000000000", - "tef128_bits_int": 1515319915194804095110340048719592816640, - "tef128_bits_hex": "0x474000000000000000000000000000000", + "tnf128_bits_int": 1515319915194804095110340048719592816640, + "tnf128_bits_hex": "0x474000000000000000000000000000000", "decoded_f64": 9.332636185032189e-302, "decoded_f64_hex": "0x0170000000000000", "abs_error": 0.0, @@ -42,8 +42,8 @@ "name": "neg_pow2_-1000", "input_f64": -9.332636185032189e-302, "input_f64_hex": "0x8170000000000000", - "tef128_bits_int": 6959837785929819510524333767627884199936, - "tef128_bits_hex": "0x1474000000000000000000000000000000", + "tnf128_bits_int": 6959837785929819510524333767627884199936, + "tnf128_bits_hex": "0x1474000000000000000000000000000000", "decoded_f64": -9.332636185032189e-302, "decoded_f64_hex": "0x8170000000000000", "abs_error": 0.0, @@ -53,8 +53,8 @@ "name": "onehalf_2e-1000", "input_f64": 1.3998954277548283e-301, "input_f64_hex": "0x0178000000000000", - "tef128_bits_int": 1515652222193750324078566000484662902784, - "tef128_bits_hex": "0x474400000000000000000000000000000", + "tnf128_bits_int": 1515652222193750324078566000484662902784, + "tnf128_bits_hex": "0x474400000000000000000000000000000", "decoded_f64": 1.3998954277548283e-301, "decoded_f64_hex": "0x0178000000000000", "abs_error": 0.0, @@ -64,8 +64,8 @@ "name": "pow2_-500", "input_f64": 3.054936363499605e-151, "input_f64_hex": "0x20b0000000000000", - "tef128_bits_int": 1847626914141033063336291813789678960640, - "tef128_bits_hex": "0x56e000000000000000000000000000000", + "tnf128_bits_int": 1847626914141033063336291813789678960640, + "tnf128_bits_hex": "0x56e000000000000000000000000000000", "decoded_f64": 3.054936363499605e-151, "decoded_f64_hex": "0x20b0000000000000", "abs_error": 0.0, @@ -75,8 +75,8 @@ "name": "neg_pow2_-500", "input_f64": -3.054936363499605e-151, "input_f64_hex": "0xa0b0000000000000", - "tef128_bits_int": 7292144784876048478750285532697970343936, - "tef128_bits_hex": "0x156e000000000000000000000000000000", + "tnf128_bits_int": 7292144784876048478750285532697970343936, + "tnf128_bits_hex": "0x156e000000000000000000000000000000", "decoded_f64": -3.054936363499605e-151, "decoded_f64_hex": "0xa0b0000000000000", "abs_error": 0.0, @@ -86,8 +86,8 @@ "name": "onehalf_2e-500", "input_f64": 4.582404545249407e-151, "input_f64_hex": "0x20b8000000000000", - "tef128_bits_int": 1847959221139979292304517765554749046784, - "tef128_bits_hex": "0x56e400000000000000000000000000000", + "tnf128_bits_int": 1847959221139979292304517765554749046784, + "tnf128_bits_hex": "0x56e400000000000000000000000000000", "decoded_f64": 4.582404545249407e-151, "decoded_f64_hex": "0x20b8000000000000", "abs_error": 0.0, @@ -97,8 +97,8 @@ "name": "pow2_-1", "input_f64": 0.5, "input_f64_hex": "0x3fe0000000000000", - "tef128_bits_int": 2179269299089369573625791675329624932352, - "tef128_bits_hex": "0x667800000000000000000000000000000", + "tnf128_bits_int": 2179269299089369573625791675329624932352, + "tnf128_bits_hex": "0x667800000000000000000000000000000", "decoded_f64": 0.5, "decoded_f64_hex": "0x3fe0000000000000", "abs_error": 0.0, @@ -108,8 +108,8 @@ "name": "neg_pow2_-1", "input_f64": -0.5, "input_f64_hex": "0xbfe0000000000000", - "tef128_bits_int": 7623787169824384989039785394237916315648, - "tef128_bits_hex": "0x1667800000000000000000000000000000", + "tnf128_bits_int": 7623787169824384989039785394237916315648, + "tnf128_bits_hex": "0x1667800000000000000000000000000000", "decoded_f64": -0.5, "decoded_f64_hex": "0xbfe0000000000000", "abs_error": 0.0, @@ -119,8 +119,8 @@ "name": "onehalf_2e-1", "input_f64": 0.75, "input_f64_hex": "0x3fe8000000000000", - "tef128_bits_int": 2179601606088315802594017627094695018496, - "tef128_bits_hex": "0x667c00000000000000000000000000000", + "tnf128_bits_int": 2179601606088315802594017627094695018496, + "tnf128_bits_hex": "0x667c00000000000000000000000000000", "decoded_f64": 0.75, "decoded_f64_hex": "0x3fe8000000000000", "abs_error": 0.0, @@ -130,8 +130,8 @@ "name": "pow2_0", "input_f64": 1.0, "input_f64_hex": "0x3ff0000000000000", - "tef128_bits_int": 2179933913087262031562243578859765104640, - "tef128_bits_hex": "0x668000000000000000000000000000000", + "tnf128_bits_int": 2179933913087262031562243578859765104640, + "tnf128_bits_hex": "0x668000000000000000000000000000000", "decoded_f64": 1.0, "decoded_f64_hex": "0x3ff0000000000000", "abs_error": 0.0, @@ -141,8 +141,8 @@ "name": "neg_pow2_0", "input_f64": -1.0, "input_f64_hex": "0xbff0000000000000", - "tef128_bits_int": 7624451783822277446976237297768056487936, - "tef128_bits_hex": "0x1668000000000000000000000000000000", + "tnf128_bits_int": 7624451783822277446976237297768056487936, + "tnf128_bits_hex": "0x1668000000000000000000000000000000", "decoded_f64": -1.0, "decoded_f64_hex": "0xbff0000000000000", "abs_error": 0.0, @@ -152,8 +152,8 @@ "name": "onehalf_2e0", "input_f64": 1.5, "input_f64_hex": "0x3ff8000000000000", - "tef128_bits_int": 2180266220086208260530469530624835190784, - "tef128_bits_hex": "0x668400000000000000000000000000000", + "tnf128_bits_int": 2180266220086208260530469530624835190784, + "tnf128_bits_hex": "0x668400000000000000000000000000000", "decoded_f64": 1.5, "decoded_f64_hex": "0x3ff8000000000000", "abs_error": 0.0, @@ -163,8 +163,8 @@ "name": "pow2_1", "input_f64": 2.0, "input_f64_hex": "0x4000000000000000", - "tef128_bits_int": 2180598527085154489498695482389905276928, - "tef128_bits_hex": "0x668800000000000000000000000000000", + "tnf128_bits_int": 2180598527085154489498695482389905276928, + "tnf128_bits_hex": "0x668800000000000000000000000000000", "decoded_f64": 2.0, "decoded_f64_hex": "0x4000000000000000", "abs_error": 0.0, @@ -174,8 +174,8 @@ "name": "neg_pow2_1", "input_f64": -2.0, "input_f64_hex": "0xc000000000000000", - "tef128_bits_int": 7625116397820169904912689201298196660224, - "tef128_bits_hex": "0x1668800000000000000000000000000000", + "tnf128_bits_int": 7625116397820169904912689201298196660224, + "tnf128_bits_hex": "0x1668800000000000000000000000000000", "decoded_f64": -2.0, "decoded_f64_hex": "0xc000000000000000", "abs_error": 0.0, @@ -185,8 +185,8 @@ "name": "onehalf_2e1", "input_f64": 3.0, "input_f64_hex": "0x4008000000000000", - "tef128_bits_int": 2180930834084100718466921434154975363072, - "tef128_bits_hex": "0x668c00000000000000000000000000000", + "tnf128_bits_int": 2180930834084100718466921434154975363072, + "tnf128_bits_hex": "0x668c00000000000000000000000000000", "decoded_f64": 3.0, "decoded_f64_hex": "0x4008000000000000", "abs_error": 0.0, @@ -196,8 +196,8 @@ "name": "pow2_500", "input_f64": 3.273390607896142e+150, "input_f64_hex": "0x5f30000000000000", - "tef128_bits_int": 2512240912033490999788195343929851248640, - "tef128_bits_hex": "0x762000000000000000000000000000000", + "tnf128_bits_int": 2512240912033490999788195343929851248640, + "tnf128_bits_hex": "0x762000000000000000000000000000000", "decoded_f64": 3.273390607896142e+150, "decoded_f64_hex": "0x5f30000000000000", "abs_error": 0.0, @@ -207,8 +207,8 @@ "name": "neg_pow2_500", "input_f64": -3.273390607896142e+150, "input_f64_hex": "0xdf30000000000000", - "tef128_bits_int": 7956758782768506415202189062838142631936, - "tef128_bits_hex": "0x1762000000000000000000000000000000", + "tnf128_bits_int": 7956758782768506415202189062838142631936, + "tnf128_bits_hex": "0x1762000000000000000000000000000000", "decoded_f64": -3.273390607896142e+150, "decoded_f64_hex": "0xdf30000000000000", "abs_error": 0.0, @@ -218,8 +218,8 @@ "name": "onehalf_2e500", "input_f64": 4.910085911844213e+150, "input_f64_hex": "0x5f38000000000000", - "tef128_bits_int": 2512573219032437228756421295694921334784, - "tef128_bits_hex": "0x762400000000000000000000000000000", + "tnf128_bits_int": 2512573219032437228756421295694921334784, + "tnf128_bits_hex": "0x762400000000000000000000000000000", "decoded_f64": 4.910085911844213e+150, "decoded_f64_hex": "0x5f38000000000000", "abs_error": 0.0, @@ -229,8 +229,8 @@ "name": "pow2_1000", "input_f64": 1.0715086071862673e+301, "input_f64_hex": "0x7e70000000000000", - "tef128_bits_int": 2844547910979719968014147108999937392640, - "tef128_bits_hex": "0x85c000000000000000000000000000000", + "tnf128_bits_int": 2844547910979719968014147108999937392640, + "tnf128_bits_hex": "0x85c000000000000000000000000000000", "decoded_f64": 1.0715086071862673e+301, "decoded_f64_hex": "0x7e70000000000000", "abs_error": 0.0, @@ -240,8 +240,8 @@ "name": "neg_pow2_1000", "input_f64": -1.0715086071862673e+301, "input_f64_hex": "0xfe70000000000000", - "tef128_bits_int": 8289065781714735383428140827908228775936, - "tef128_bits_hex": "0x185c000000000000000000000000000000", + "tnf128_bits_int": 8289065781714735383428140827908228775936, + "tnf128_bits_hex": "0x185c000000000000000000000000000000", "decoded_f64": -1.0715086071862673e+301, "decoded_f64_hex": "0xfe70000000000000", "abs_error": 0.0, @@ -251,8 +251,8 @@ "name": "onehalf_2e1000", "input_f64": 1.607262910779401e+301, "input_f64_hex": "0x7e78000000000000", - "tef128_bits_int": 2844880217978666196982373060765007478784, - "tef128_bits_hex": "0x85c400000000000000000000000000000", + "tnf128_bits_int": 2844880217978666196982373060765007478784, + "tnf128_bits_hex": "0x85c400000000000000000000000000000", "decoded_f64": 1.607262910779401e+301, "decoded_f64_hex": "0x7e78000000000000", "abs_error": 0.0, diff --git a/conformance/vectors/tef16_conformance_v0.json b/conformance/vectors/tnf16_conformance_v0.json similarity index 79% rename from conformance/vectors/tef16_conformance_v0.json rename to conformance/vectors/tnf16_conformance_v0.json index 2dfa220ba8..44db981c80 100644 --- a/conformance/vectors/tef16_conformance_v0.json +++ b/conformance/vectors/tnf16_conformance_v0.json @@ -1,7 +1,7 @@ { "schema": "t27-conformance/v0.1", - "format": "TEF16", - "ssot": "specs/numeric/tef16.t27", + "format": "TNF16", + "ssot": "specs/numeric/tnf16.t27", "anchor_identity": "phi^2 + 1/phi^2 = 3", "anchor_check": { "value": 3.0, @@ -20,8 +20,8 @@ "name": "pos_zero", "input_f64": 0.0, "input_f64_hex": "0x0000000000000000", - "tef16_bits_int": 0, - "tef16_bits_hex": "0x0", + "tnf16_bits_int": 0, + "tnf16_bits_hex": "0x0", "decoded_f64": 0.0, "decoded_f64_hex": "0x0000000000000000", "abs_error": 0.0, @@ -31,8 +31,8 @@ "name": "pow2_-39", "input_f64": 1.8189894035458565e-12, "input_f64_hex": "0x3d80000000000000", - "tef16_bits_int": 2048, - "tef16_bits_hex": "0x800", + "tnf16_bits_int": 2048, + "tnf16_bits_hex": "0x800", "decoded_f64": 1.8189894035458565e-12, "decoded_f64_hex": "0x3d80000000000000", "abs_error": 0.0, @@ -42,8 +42,8 @@ "name": "neg_pow2_-39", "input_f64": -1.8189894035458565e-12, "input_f64_hex": "0xbd80000000000000", - "tef16_bits_int": 264192, - "tef16_bits_hex": "0x40800", + "tnf16_bits_int": 264192, + "tnf16_bits_hex": "0x40800", "decoded_f64": -1.8189894035458565e-12, "decoded_f64_hex": "0xbd80000000000000", "abs_error": 0.0, @@ -53,8 +53,8 @@ "name": "onehalf_2e-39", "input_f64": 2.7284841053187847e-12, "input_f64_hex": "0x3d88000000000000", - "tef16_bits_int": 3072, - "tef16_bits_hex": "0xc00", + "tnf16_bits_int": 3072, + "tnf16_bits_hex": "0xc00", "decoded_f64": 2.7284841053187847e-12, "decoded_f64_hex": "0x3d88000000000000", "abs_error": 0.0, @@ -64,8 +64,8 @@ "name": "pow2_-19", "input_f64": 1.9073486328125e-06, "input_f64_hex": "0x3ec0000000000000", - "tef16_bits_int": 43008, - "tef16_bits_hex": "0xa800", + "tnf16_bits_int": 43008, + "tnf16_bits_hex": "0xa800", "decoded_f64": 1.9073486328125e-06, "decoded_f64_hex": "0x3ec0000000000000", "abs_error": 0.0, @@ -75,8 +75,8 @@ "name": "neg_pow2_-19", "input_f64": -1.9073486328125e-06, "input_f64_hex": "0xbec0000000000000", - "tef16_bits_int": 305152, - "tef16_bits_hex": "0x4a800", + "tnf16_bits_int": 305152, + "tnf16_bits_hex": "0x4a800", "decoded_f64": -1.9073486328125e-06, "decoded_f64_hex": "0xbec0000000000000", "abs_error": 0.0, @@ -86,8 +86,8 @@ "name": "onehalf_2e-19", "input_f64": 2.86102294921875e-06, "input_f64_hex": "0x3ec8000000000000", - "tef16_bits_int": 44032, - "tef16_bits_hex": "0xac00", + "tnf16_bits_int": 44032, + "tnf16_bits_hex": "0xac00", "decoded_f64": 2.86102294921875e-06, "decoded_f64_hex": "0x3ec8000000000000", "abs_error": 0.0, @@ -97,8 +97,8 @@ "name": "pow2_-1", "input_f64": 0.5, "input_f64_hex": "0x3fe0000000000000", - "tef16_bits_int": 79872, - "tef16_bits_hex": "0x13800", + "tnf16_bits_int": 79872, + "tnf16_bits_hex": "0x13800", "decoded_f64": 0.5, "decoded_f64_hex": "0x3fe0000000000000", "abs_error": 0.0, @@ -108,8 +108,8 @@ "name": "neg_pow2_-1", "input_f64": -0.5, "input_f64_hex": "0xbfe0000000000000", - "tef16_bits_int": 342016, - "tef16_bits_hex": "0x53800", + "tnf16_bits_int": 342016, + "tnf16_bits_hex": "0x53800", "decoded_f64": -0.5, "decoded_f64_hex": "0xbfe0000000000000", "abs_error": 0.0, @@ -119,8 +119,8 @@ "name": "onehalf_2e-1", "input_f64": 0.75, "input_f64_hex": "0x3fe8000000000000", - "tef16_bits_int": 80896, - "tef16_bits_hex": "0x13c00", + "tnf16_bits_int": 80896, + "tnf16_bits_hex": "0x13c00", "decoded_f64": 0.75, "decoded_f64_hex": "0x3fe8000000000000", "abs_error": 0.0, @@ -130,8 +130,8 @@ "name": "pow2_0", "input_f64": 1.0, "input_f64_hex": "0x3ff0000000000000", - "tef16_bits_int": 81920, - "tef16_bits_hex": "0x14000", + "tnf16_bits_int": 81920, + "tnf16_bits_hex": "0x14000", "decoded_f64": 1.0, "decoded_f64_hex": "0x3ff0000000000000", "abs_error": 0.0, @@ -141,8 +141,8 @@ "name": "neg_pow2_0", "input_f64": -1.0, "input_f64_hex": "0xbff0000000000000", - "tef16_bits_int": 344064, - "tef16_bits_hex": "0x54000", + "tnf16_bits_int": 344064, + "tnf16_bits_hex": "0x54000", "decoded_f64": -1.0, "decoded_f64_hex": "0xbff0000000000000", "abs_error": 0.0, @@ -152,8 +152,8 @@ "name": "onehalf_2e0", "input_f64": 1.5, "input_f64_hex": "0x3ff8000000000000", - "tef16_bits_int": 82944, - "tef16_bits_hex": "0x14400", + "tnf16_bits_int": 82944, + "tnf16_bits_hex": "0x14400", "decoded_f64": 1.5, "decoded_f64_hex": "0x3ff8000000000000", "abs_error": 0.0, @@ -163,8 +163,8 @@ "name": "pow2_1", "input_f64": 2.0, "input_f64_hex": "0x4000000000000000", - "tef16_bits_int": 83968, - "tef16_bits_hex": "0x14800", + "tnf16_bits_int": 83968, + "tnf16_bits_hex": "0x14800", "decoded_f64": 2.0, "decoded_f64_hex": "0x4000000000000000", "abs_error": 0.0, @@ -174,8 +174,8 @@ "name": "neg_pow2_1", "input_f64": -2.0, "input_f64_hex": "0xc000000000000000", - "tef16_bits_int": 346112, - "tef16_bits_hex": "0x54800", + "tnf16_bits_int": 346112, + "tnf16_bits_hex": "0x54800", "decoded_f64": -2.0, "decoded_f64_hex": "0xc000000000000000", "abs_error": 0.0, @@ -185,8 +185,8 @@ "name": "onehalf_2e1", "input_f64": 3.0, "input_f64_hex": "0x4008000000000000", - "tef16_bits_int": 84992, - "tef16_bits_hex": "0x14c00", + "tnf16_bits_int": 84992, + "tnf16_bits_hex": "0x14c00", "decoded_f64": 3.0, "decoded_f64_hex": "0x4008000000000000", "abs_error": 0.0, @@ -196,8 +196,8 @@ "name": "pow2_19", "input_f64": 524288.0, "input_f64_hex": "0x4120000000000000", - "tef16_bits_int": 120832, - "tef16_bits_hex": "0x1d800", + "tnf16_bits_int": 120832, + "tnf16_bits_hex": "0x1d800", "decoded_f64": 524288.0, "decoded_f64_hex": "0x4120000000000000", "abs_error": 0.0, @@ -207,8 +207,8 @@ "name": "neg_pow2_19", "input_f64": -524288.0, "input_f64_hex": "0xc120000000000000", - "tef16_bits_int": 382976, - "tef16_bits_hex": "0x5d800", + "tnf16_bits_int": 382976, + "tnf16_bits_hex": "0x5d800", "decoded_f64": -524288.0, "decoded_f64_hex": "0xc120000000000000", "abs_error": 0.0, @@ -218,8 +218,8 @@ "name": "onehalf_2e19", "input_f64": 786432.0, "input_f64_hex": "0x4128000000000000", - "tef16_bits_int": 121856, - "tef16_bits_hex": "0x1dc00", + "tnf16_bits_int": 121856, + "tnf16_bits_hex": "0x1dc00", "decoded_f64": 786432.0, "decoded_f64_hex": "0x4128000000000000", "abs_error": 0.0, @@ -229,8 +229,8 @@ "name": "pow2_39", "input_f64": 549755813888.0, "input_f64_hex": "0x4260000000000000", - "tef16_bits_int": 161792, - "tef16_bits_hex": "0x27800", + "tnf16_bits_int": 161792, + "tnf16_bits_hex": "0x27800", "decoded_f64": 549755813888.0, "decoded_f64_hex": "0x4260000000000000", "abs_error": 0.0, @@ -240,8 +240,8 @@ "name": "neg_pow2_39", "input_f64": -549755813888.0, "input_f64_hex": "0xc260000000000000", - "tef16_bits_int": 423936, - "tef16_bits_hex": "0x67800", + "tnf16_bits_int": 423936, + "tnf16_bits_hex": "0x67800", "decoded_f64": -549755813888.0, "decoded_f64_hex": "0xc260000000000000", "abs_error": 0.0, @@ -251,8 +251,8 @@ "name": "onehalf_2e39", "input_f64": 824633720832.0, "input_f64_hex": "0x4268000000000000", - "tef16_bits_int": 162816, - "tef16_bits_hex": "0x27c00", + "tnf16_bits_int": 162816, + "tnf16_bits_hex": "0x27c00", "decoded_f64": 824633720832.0, "decoded_f64_hex": "0x4268000000000000", "abs_error": 0.0, diff --git a/conformance/vectors/tef256_conformance_v0.json b/conformance/vectors/tnf256_conformance_v0.json similarity index 71% rename from conformance/vectors/tef256_conformance_v0.json rename to conformance/vectors/tnf256_conformance_v0.json index b8a8a0982b..ad6ce97406 100644 --- a/conformance/vectors/tef256_conformance_v0.json +++ b/conformance/vectors/tnf256_conformance_v0.json @@ -1,7 +1,7 @@ { "schema": "t27-conformance/v0.1", - "format": "TEF256", - "ssot": "specs/numeric/tef256.t27", + "format": "TNF256", + "ssot": "specs/numeric/tnf256.t27", "anchor_identity": "phi^2 + 1/phi^2 = 3", "anchor_check": { "value": 3.0, @@ -20,8 +20,8 @@ "name": "pos_zero", "input_f64": 0.0, "input_f64_hex": "0x0000000000000000", - "tef256_bits_int": 0, - "tef256_bits_hex": "0x0", + "tnf256_bits_int": 0, + "tnf256_bits_hex": "0x0", "decoded_f64": 0.0, "decoded_f64_hex": "0x0000000000000000", "abs_error": 0.0, @@ -31,8 +31,8 @@ "name": "pow2_-1000", "input_f64": 9.332636185032189e-302, "input_f64_hex": "0x0170000000000000", - "tef256_bits_int": 999724473581164534902139725060361126299570248465750221360199707240195292135424, - "tef256_bits_hex": "0x8a240000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 999724473581164534902139725060361126299570248465750221360199707240195292135424, + "tnf256_bits_hex": "0x8a240000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 9.332636185032189e-302, "decoded_f64_hex": "0x0170000000000000", "abs_error": 0.0, @@ -42,8 +42,8 @@ "name": "neg_pow2_-1000", "input_f64": -9.332636185032189e-302, "input_f64_hex": "0x8170000000000000", - "tef256_bits_int": 4705071329175282788456411245338374177604209757766248270622842395493415440613376, - "tef256_bits_hex": "0x28a240000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 4705071329175282788456411245338374177604209757766248270622842395493415440613376, + "tnf256_bits_hex": "0x28a240000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -9.332636185032189e-302, "decoded_f64_hex": "0x8170000000000000", "abs_error": 0.0, @@ -53,8 +53,8 @@ "name": "onehalf_2e-1000", "input_f64": 1.3998954277548283e-301, "input_f64_hex": "0x0178000000000000", - "tef256_bits_int": 999781012687237443200686390580384899692076727950450241166859598638636655968256, - "tef256_bits_hex": "0x8a260000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 999781012687237443200686390580384899692076727950450241166859598638636655968256, + "tnf256_bits_hex": "0x8a260000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.3998954277548283e-301, "decoded_f64_hex": "0x0178000000000000", "abs_error": 0.0, @@ -64,8 +64,8 @@ "name": "pow2_-500", "input_f64": 3.054936363499605e-151, "input_f64_hex": "0x20b0000000000000", - "tef256_bits_int": 1056263579654072833448805245084134518806049733165770028020091105681559124967424, - "tef256_bits_hex": "0x91f40000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 1056263579654072833448805245084134518806049733165770028020091105681559124967424, + "tnf256_bits_hex": "0x91f40000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 3.054936363499605e-151, "decoded_f64_hex": "0x20b0000000000000", "abs_error": 0.0, @@ -75,8 +75,8 @@ "name": "neg_pow2_-500", "input_f64": -3.054936363499605e-151, "input_f64_hex": "0xa0b0000000000000", - "tef256_bits_int": 4761610435248191087003076765362147570110689242466268077282733793934779273445376, - "tef256_bits_hex": "0x291f40000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 4761610435248191087003076765362147570110689242466268077282733793934779273445376, + "tnf256_bits_hex": "0x291f40000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -3.054936363499605e-151, "decoded_f64_hex": "0xa0b0000000000000", "abs_error": 0.0, @@ -86,8 +86,8 @@ "name": "onehalf_2e-500", "input_f64": 4.582404545249407e-151, "input_f64_hex": "0x20b8000000000000", - "tef256_bits_int": 1056320118760145741747351910604158292198556212650470047826750997080000488800256, - "tef256_bits_hex": "0x91f60000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 1056320118760145741747351910604158292198556212650470047826750997080000488800256, + "tnf256_bits_hex": "0x91f60000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 4.582404545249407e-151, "decoded_f64_hex": "0x20b8000000000000", "abs_error": 0.0, @@ -97,8 +97,8 @@ "name": "pow2_-1", "input_f64": 0.5, "input_f64_hex": "0x3fe0000000000000", - "tef256_bits_int": 1112689607514835315398377434067860364527516258896389795066662721326040230133760, - "tef256_bits_hex": "0x99c00000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 1112689607514835315398377434067860364527516258896389795066662721326040230133760, + "tnf256_bits_hex": "0x99c00000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 0.5, "decoded_f64_hex": "0x3fe0000000000000", "abs_error": 0.0, @@ -108,8 +108,8 @@ "name": "neg_pow2_-1", "input_f64": -0.5, "input_f64_hex": "0xbfe0000000000000", - "tef256_bits_int": 4818036463108953568952648954345873415832155768196887844329305409579260378611712, - "tef256_bits_hex": "0x299c00000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 4818036463108953568952648954345873415832155768196887844329305409579260378611712, + "tnf256_bits_hex": "0x299c00000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -0.5, "decoded_f64_hex": "0xbfe0000000000000", "abs_error": 0.0, @@ -119,8 +119,8 @@ "name": "onehalf_2e-1", "input_f64": 0.75, "input_f64_hex": "0x3fe8000000000000", - "tef256_bits_int": 1112746146620908223696924099587884137920022738381089814873322612724481593966592, - "tef256_bits_hex": "0x99c20000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 1112746146620908223696924099587884137920022738381089814873322612724481593966592, + "tnf256_bits_hex": "0x99c20000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 0.75, "decoded_f64_hex": "0x3fe8000000000000", "abs_error": 0.0, @@ -130,8 +130,8 @@ "name": "pow2_0", "input_f64": 1.0, "input_f64_hex": "0x3ff0000000000000", - "tef256_bits_int": 1112802685726981131995470765107907911312529217865789834679982504122922957799424, - "tef256_bits_hex": "0x99c40000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 1112802685726981131995470765107907911312529217865789834679982504122922957799424, + "tnf256_bits_hex": "0x99c40000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.0, "decoded_f64_hex": "0x3ff0000000000000", "abs_error": 0.0, @@ -141,8 +141,8 @@ "name": "neg_pow2_0", "input_f64": -1.0, "input_f64_hex": "0xbff0000000000000", - "tef256_bits_int": 4818149541321099385549742285385920962617168727166287883942625192376143106277376, - "tef256_bits_hex": "0x299c40000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 4818149541321099385549742285385920962617168727166287883942625192376143106277376, + "tnf256_bits_hex": "0x299c40000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -1.0, "decoded_f64_hex": "0xbff0000000000000", "abs_error": 0.0, @@ -152,8 +152,8 @@ "name": "onehalf_2e0", "input_f64": 1.5, "input_f64_hex": "0x3ff8000000000000", - "tef256_bits_int": 1112859224833054040294017430627931684705035697350489854486642395521364321632256, - "tef256_bits_hex": "0x99c60000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 1112859224833054040294017430627931684705035697350489854486642395521364321632256, + "tnf256_bits_hex": "0x99c60000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.5, "decoded_f64_hex": "0x3ff8000000000000", "abs_error": 0.0, @@ -163,8 +163,8 @@ "name": "pow2_1", "input_f64": 2.0, "input_f64_hex": "0x4000000000000000", - "tef256_bits_int": 1112915763939126948592564096147955458097542176835189874293302286919805685465088, - "tef256_bits_hex": "0x99c80000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 1112915763939126948592564096147955458097542176835189874293302286919805685465088, + "tnf256_bits_hex": "0x99c80000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 2.0, "decoded_f64_hex": "0x4000000000000000", "abs_error": 0.0, @@ -174,8 +174,8 @@ "name": "neg_pow2_1", "input_f64": -2.0, "input_f64_hex": "0xc000000000000000", - "tef256_bits_int": 4818262619533245202146835616425968509402181686135687923555944975173025833943040, - "tef256_bits_hex": "0x299c80000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 4818262619533245202146835616425968509402181686135687923555944975173025833943040, + "tnf256_bits_hex": "0x299c80000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -2.0, "decoded_f64_hex": "0xc000000000000000", "abs_error": 0.0, @@ -185,8 +185,8 @@ "name": "onehalf_2e1", "input_f64": 3.0, "input_f64_hex": "0x4008000000000000", - "tef256_bits_int": 1112972303045199856891110761667979231490048656319889894099962178318247049297920, - "tef256_bits_hex": "0x99ca0000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 1112972303045199856891110761667979231490048656319889894099962178318247049297920, + "tnf256_bits_hex": "0x99ca0000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 3.0, "decoded_f64_hex": "0x4008000000000000", "abs_error": 0.0, @@ -196,8 +196,8 @@ "name": "pow2_500", "input_f64": 3.273390607896142e+150, "input_f64_hex": "0x5f30000000000000", - "tef256_bits_int": 1169341791799889430542136285131681303819008702565809641339873902564286790631424, - "tef256_bits_hex": "0xa1940000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 1169341791799889430542136285131681303819008702565809641339873902564286790631424, + "tnf256_bits_hex": "0xa1940000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 3.273390607896142e+150, "decoded_f64_hex": "0x5f30000000000000", "abs_error": 0.0, @@ -207,8 +207,8 @@ "name": "neg_pow2_500", "input_f64": -3.273390607896142e+150, "input_f64_hex": "0xdf30000000000000", - "tef256_bits_int": 4874688647394007684096407805409694355123648211866307690602516590817506939109376, - "tef256_bits_hex": "0x2a1940000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 4874688647394007684096407805409694355123648211866307690602516590817506939109376, + "tnf256_bits_hex": "0x2a1940000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -3.273390607896142e+150, "decoded_f64_hex": "0xdf30000000000000", "abs_error": 0.0, @@ -218,8 +218,8 @@ "name": "onehalf_2e500", "input_f64": 4.910085911844213e+150, "input_f64_hex": "0x5f38000000000000", - "tef256_bits_int": 1169398330905962338840682950651705077211515182050509661146533793962728154464256, - "tef256_bits_hex": "0xa1960000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 1169398330905962338840682950651705077211515182050509661146533793962728154464256, + "tnf256_bits_hex": "0xa1960000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 4.910085911844213e+150, "decoded_f64_hex": "0x5f38000000000000", "abs_error": 0.0, @@ -229,8 +229,8 @@ "name": "pow2_1000", "input_f64": 1.0715086071862673e+301, "input_f64_hex": "0x7e70000000000000", - "tef256_bits_int": 1225880897872797729088801805155454696325488187265829447999765301005650623463424, - "tef256_bits_hex": "0xa9640000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 1225880897872797729088801805155454696325488187265829447999765301005650623463424, + "tnf256_bits_hex": "0xa9640000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.0715086071862673e+301, "decoded_f64_hex": "0x7e70000000000000", "abs_error": 0.0, @@ -240,8 +240,8 @@ "name": "neg_pow2_1000", "input_f64": -1.0715086071862673e+301, "input_f64_hex": "0xfe70000000000000", - "tef256_bits_int": 4931227753466915982643073325433467747630127696566327497262407989258870771941376, - "tef256_bits_hex": "0x2a9640000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 4931227753466915982643073325433467747630127696566327497262407989258870771941376, + "tnf256_bits_hex": "0x2a9640000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -1.0715086071862673e+301, "decoded_f64_hex": "0xfe70000000000000", "abs_error": 0.0, @@ -251,8 +251,8 @@ "name": "onehalf_2e1000", "input_f64": 1.607262910779401e+301, "input_f64_hex": "0x7e78000000000000", - "tef256_bits_int": 1225937436978870637387348470675478469717994666750529467806425192404091987296256, - "tef256_bits_hex": "0xa9660000000000000000000000000000000000000000000000000000000000000", + "tnf256_bits_int": 1225937436978870637387348470675478469717994666750529467806425192404091987296256, + "tnf256_bits_hex": "0xa9660000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.607262910779401e+301, "decoded_f64_hex": "0x7e78000000000000", "abs_error": 0.0, diff --git a/conformance/vectors/tef32_conformance_v0.json b/conformance/vectors/tnf32_conformance_v0.json similarity index 77% rename from conformance/vectors/tef32_conformance_v0.json rename to conformance/vectors/tnf32_conformance_v0.json index b609e13ddc..972fff61e8 100644 --- a/conformance/vectors/tef32_conformance_v0.json +++ b/conformance/vectors/tnf32_conformance_v0.json @@ -1,7 +1,7 @@ { "schema": "t27-conformance/v0.1", - "format": "TEF32", - "ssot": "specs/numeric/tef32.t27", + "format": "TNF32", + "ssot": "specs/numeric/tnf32.t27", "anchor_identity": "phi^2 + 1/phi^2 = 3", "anchor_check": { "value": 3.0, @@ -20,8 +20,8 @@ "name": "pos_zero", "input_f64": 0.0, "input_f64_hex": "0x0000000000000000", - "tef32_bits_int": 0, - "tef32_bits_hex": "0x0", + "tnf32_bits_int": 0, + "tnf32_bits_hex": "0x0", "decoded_f64": 0.0, "decoded_f64_hex": "0x0000000000000000", "abs_error": 0.0, @@ -31,8 +31,8 @@ "name": "pow2_-363", "input_f64": 5.3224498000101884e-110, "input_f64_hex": "0x2940000000000000", - "tef32_bits_int": 33554432, - "tef32_bits_hex": "0x2000000", + "tnf32_bits_int": 33554432, + "tnf32_bits_hex": "0x2000000", "decoded_f64": 5.3224498000101884e-110, "decoded_f64_hex": "0x2940000000000000", "abs_error": 0.0, @@ -42,8 +42,8 @@ "name": "neg_pow2_-363", "input_f64": -5.3224498000101884e-110, "input_f64_hex": "0xa940000000000000", - "tef32_bits_int": 34393292800, - "tef32_bits_hex": "0x802000000", + "tnf32_bits_int": 34393292800, + "tnf32_bits_hex": "0x802000000", "decoded_f64": -5.3224498000101884e-110, "decoded_f64_hex": "0xa940000000000000", "abs_error": 0.0, @@ -53,8 +53,8 @@ "name": "onehalf_2e-363", "input_f64": 7.983674700015283e-110, "input_f64_hex": "0x2948000000000000", - "tef32_bits_int": 50331648, - "tef32_bits_hex": "0x3000000", + "tnf32_bits_int": 50331648, + "tnf32_bits_hex": "0x3000000", "decoded_f64": 7.983674700015283e-110, "decoded_f64_hex": "0x2948000000000000", "abs_error": 0.0, @@ -64,8 +64,8 @@ "name": "pow2_-181", "input_f64": 3.2626522339992623e-55, "input_f64_hex": "0x34a0000000000000", - "tef32_bits_int": 6140461056, - "tef32_bits_hex": "0x16e000000", + "tnf32_bits_int": 6140461056, + "tnf32_bits_hex": "0x16e000000", "decoded_f64": 3.2626522339992623e-55, "decoded_f64_hex": "0x34a0000000000000", "abs_error": 0.0, @@ -75,8 +75,8 @@ "name": "neg_pow2_-181", "input_f64": -3.2626522339992623e-55, "input_f64_hex": "0xb4a0000000000000", - "tef32_bits_int": 40500199424, - "tef32_bits_hex": "0x96e000000", + "tnf32_bits_int": 40500199424, + "tnf32_bits_hex": "0x96e000000", "decoded_f64": -3.2626522339992623e-55, "decoded_f64_hex": "0xb4a0000000000000", "abs_error": 0.0, @@ -86,8 +86,8 @@ "name": "onehalf_2e-181", "input_f64": 4.8939783509988934e-55, "input_f64_hex": "0x34a8000000000000", - "tef32_bits_int": 6157238272, - "tef32_bits_hex": "0x16f000000", + "tnf32_bits_int": 6157238272, + "tnf32_bits_hex": "0x16f000000", "decoded_f64": 4.8939783509988934e-55, "decoded_f64_hex": "0x34a8000000000000", "abs_error": 0.0, @@ -97,8 +97,8 @@ "name": "pow2_-1", "input_f64": 0.5, "input_f64_hex": "0x3fe0000000000000", - "tef32_bits_int": 12180258816, - "tef32_bits_hex": "0x2d6000000", + "tnf32_bits_int": 12180258816, + "tnf32_bits_hex": "0x2d6000000", "decoded_f64": 0.5, "decoded_f64_hex": "0x3fe0000000000000", "abs_error": 0.0, @@ -108,8 +108,8 @@ "name": "neg_pow2_-1", "input_f64": -0.5, "input_f64_hex": "0xbfe0000000000000", - "tef32_bits_int": 46539997184, - "tef32_bits_hex": "0xad6000000", + "tnf32_bits_int": 46539997184, + "tnf32_bits_hex": "0xad6000000", "decoded_f64": -0.5, "decoded_f64_hex": "0xbfe0000000000000", "abs_error": 0.0, @@ -119,8 +119,8 @@ "name": "onehalf_2e-1", "input_f64": 0.75, "input_f64_hex": "0x3fe8000000000000", - "tef32_bits_int": 12197036032, - "tef32_bits_hex": "0x2d7000000", + "tnf32_bits_int": 12197036032, + "tnf32_bits_hex": "0x2d7000000", "decoded_f64": 0.75, "decoded_f64_hex": "0x3fe8000000000000", "abs_error": 0.0, @@ -130,8 +130,8 @@ "name": "pow2_0", "input_f64": 1.0, "input_f64_hex": "0x3ff0000000000000", - "tef32_bits_int": 12213813248, - "tef32_bits_hex": "0x2d8000000", + "tnf32_bits_int": 12213813248, + "tnf32_bits_hex": "0x2d8000000", "decoded_f64": 1.0, "decoded_f64_hex": "0x3ff0000000000000", "abs_error": 0.0, @@ -141,8 +141,8 @@ "name": "neg_pow2_0", "input_f64": -1.0, "input_f64_hex": "0xbff0000000000000", - "tef32_bits_int": 46573551616, - "tef32_bits_hex": "0xad8000000", + "tnf32_bits_int": 46573551616, + "tnf32_bits_hex": "0xad8000000", "decoded_f64": -1.0, "decoded_f64_hex": "0xbff0000000000000", "abs_error": 0.0, @@ -152,8 +152,8 @@ "name": "onehalf_2e0", "input_f64": 1.5, "input_f64_hex": "0x3ff8000000000000", - "tef32_bits_int": 12230590464, - "tef32_bits_hex": "0x2d9000000", + "tnf32_bits_int": 12230590464, + "tnf32_bits_hex": "0x2d9000000", "decoded_f64": 1.5, "decoded_f64_hex": "0x3ff8000000000000", "abs_error": 0.0, @@ -163,8 +163,8 @@ "name": "pow2_1", "input_f64": 2.0, "input_f64_hex": "0x4000000000000000", - "tef32_bits_int": 12247367680, - "tef32_bits_hex": "0x2da000000", + "tnf32_bits_int": 12247367680, + "tnf32_bits_hex": "0x2da000000", "decoded_f64": 2.0, "decoded_f64_hex": "0x4000000000000000", "abs_error": 0.0, @@ -174,8 +174,8 @@ "name": "neg_pow2_1", "input_f64": -2.0, "input_f64_hex": "0xc000000000000000", - "tef32_bits_int": 46607106048, - "tef32_bits_hex": "0xada000000", + "tnf32_bits_int": 46607106048, + "tnf32_bits_hex": "0xada000000", "decoded_f64": -2.0, "decoded_f64_hex": "0xc000000000000000", "abs_error": 0.0, @@ -185,8 +185,8 @@ "name": "onehalf_2e1", "input_f64": 3.0, "input_f64_hex": "0x4008000000000000", - "tef32_bits_int": 12264144896, - "tef32_bits_hex": "0x2db000000", + "tnf32_bits_int": 12264144896, + "tnf32_bits_hex": "0x2db000000", "decoded_f64": 3.0, "decoded_f64_hex": "0x4008000000000000", "abs_error": 0.0, @@ -196,8 +196,8 @@ "name": "pow2_181", "input_f64": 3.064991081731778e+54, "input_f64_hex": "0x4b40000000000000", - "tef32_bits_int": 18287165440, - "tef32_bits_hex": "0x442000000", + "tnf32_bits_int": 18287165440, + "tnf32_bits_hex": "0x442000000", "decoded_f64": 3.064991081731778e+54, "decoded_f64_hex": "0x4b40000000000000", "abs_error": 0.0, @@ -207,8 +207,8 @@ "name": "neg_pow2_181", "input_f64": -3.064991081731778e+54, "input_f64_hex": "0xcb40000000000000", - "tef32_bits_int": 52646903808, - "tef32_bits_hex": "0xc42000000", + "tnf32_bits_int": 52646903808, + "tnf32_bits_hex": "0xc42000000", "decoded_f64": -3.064991081731778e+54, "decoded_f64_hex": "0xcb40000000000000", "abs_error": 0.0, @@ -218,8 +218,8 @@ "name": "onehalf_2e181", "input_f64": 4.5974866225976666e+54, "input_f64_hex": "0x4b48000000000000", - "tef32_bits_int": 18303942656, - "tef32_bits_hex": "0x443000000", + "tnf32_bits_int": 18303942656, + "tnf32_bits_hex": "0x443000000", "decoded_f64": 4.5974866225976666e+54, "decoded_f64_hex": "0x4b48000000000000", "abs_error": 0.0, @@ -229,8 +229,8 @@ "name": "pow2_363", "input_f64": 1.8788340662190666e+109, "input_f64_hex": "0x56a0000000000000", - "tef32_bits_int": 24394072064, - "tef32_bits_hex": "0x5ae000000", + "tnf32_bits_int": 24394072064, + "tnf32_bits_hex": "0x5ae000000", "decoded_f64": 1.8788340662190666e+109, "decoded_f64_hex": "0x56a0000000000000", "abs_error": 0.0, @@ -240,8 +240,8 @@ "name": "neg_pow2_363", "input_f64": -1.8788340662190666e+109, "input_f64_hex": "0xd6a0000000000000", - "tef32_bits_int": 58753810432, - "tef32_bits_hex": "0xdae000000", + "tnf32_bits_int": 58753810432, + "tnf32_bits_hex": "0xdae000000", "decoded_f64": -1.8788340662190666e+109, "decoded_f64_hex": "0xd6a0000000000000", "abs_error": 0.0, @@ -251,8 +251,8 @@ "name": "onehalf_2e363", "input_f64": 2.8182510993286e+109, "input_f64_hex": "0x56a8000000000000", - "tef32_bits_int": 24410849280, - "tef32_bits_hex": "0x5af000000", + "tnf32_bits_int": 24410849280, + "tnf32_bits_hex": "0x5af000000", "decoded_f64": 2.8182510993286e+109, "decoded_f64_hex": "0x56a8000000000000", "abs_error": 0.0, diff --git a/conformance/vectors/tef4_conformance_v0.json b/conformance/vectors/tnf4_conformance_v0.json similarity index 81% rename from conformance/vectors/tef4_conformance_v0.json rename to conformance/vectors/tnf4_conformance_v0.json index cca003ff72..3b1eda7fa9 100644 --- a/conformance/vectors/tef4_conformance_v0.json +++ b/conformance/vectors/tnf4_conformance_v0.json @@ -1,7 +1,7 @@ { "schema": "t27-conformance/v0.1", - "format": "TEF4", - "ssot": "specs/numeric/tef4.t27", + "format": "TNF4", + "ssot": "specs/numeric/tnf4.t27", "anchor_identity": "phi^2 + 1/phi^2 = 3", "anchor_check": { "value": 3.0, @@ -20,8 +20,8 @@ "name": "pos_zero", "input_f64": 0.0, "input_f64_hex": "0x0000000000000000", - "tef4_bits_int": 0, - "tef4_bits_hex": "0x0", + "tnf4_bits_int": 0, + "tnf4_bits_hex": "0x0", "decoded_f64": 0.0, "decoded_f64_hex": "0x0000000000000000", "abs_error": 0.0, @@ -31,8 +31,8 @@ "name": "pow2_-3", "input_f64": 0.125, "input_f64_hex": "0x3fc0000000000000", - "tef4_bits_int": 2, - "tef4_bits_hex": "0x2", + "tnf4_bits_int": 2, + "tnf4_bits_hex": "0x2", "decoded_f64": 0.125, "decoded_f64_hex": "0x3fc0000000000000", "abs_error": 0.0, @@ -42,8 +42,8 @@ "name": "neg_pow2_-3", "input_f64": -0.125, "input_f64_hex": "0xbfc0000000000000", - "tef4_bits_int": 34, - "tef4_bits_hex": "0x22", + "tnf4_bits_int": 34, + "tnf4_bits_hex": "0x22", "decoded_f64": -0.125, "decoded_f64_hex": "0xbfc0000000000000", "abs_error": 0.0, @@ -53,8 +53,8 @@ "name": "onehalf_2e-3", "input_f64": 0.1875, "input_f64_hex": "0x3fc8000000000000", - "tef4_bits_int": 3, - "tef4_bits_hex": "0x3", + "tnf4_bits_int": 3, + "tnf4_bits_hex": "0x3", "decoded_f64": 0.1875, "decoded_f64_hex": "0x3fc8000000000000", "abs_error": 0.0, @@ -64,8 +64,8 @@ "name": "pow2_-1", "input_f64": 0.5, "input_f64_hex": "0x3fe0000000000000", - "tef4_bits_int": 6, - "tef4_bits_hex": "0x6", + "tnf4_bits_int": 6, + "tnf4_bits_hex": "0x6", "decoded_f64": 0.5, "decoded_f64_hex": "0x3fe0000000000000", "abs_error": 0.0, @@ -75,8 +75,8 @@ "name": "neg_pow2_-1", "input_f64": -0.5, "input_f64_hex": "0xbfe0000000000000", - "tef4_bits_int": 38, - "tef4_bits_hex": "0x26", + "tnf4_bits_int": 38, + "tnf4_bits_hex": "0x26", "decoded_f64": -0.5, "decoded_f64_hex": "0xbfe0000000000000", "abs_error": 0.0, @@ -86,8 +86,8 @@ "name": "onehalf_2e-1", "input_f64": 0.75, "input_f64_hex": "0x3fe8000000000000", - "tef4_bits_int": 7, - "tef4_bits_hex": "0x7", + "tnf4_bits_int": 7, + "tnf4_bits_hex": "0x7", "decoded_f64": 0.75, "decoded_f64_hex": "0x3fe8000000000000", "abs_error": 0.0, @@ -97,8 +97,8 @@ "name": "pow2_0", "input_f64": 1.0, "input_f64_hex": "0x3ff0000000000000", - "tef4_bits_int": 8, - "tef4_bits_hex": "0x8", + "tnf4_bits_int": 8, + "tnf4_bits_hex": "0x8", "decoded_f64": 1.0, "decoded_f64_hex": "0x3ff0000000000000", "abs_error": 0.0, @@ -108,8 +108,8 @@ "name": "neg_pow2_0", "input_f64": -1.0, "input_f64_hex": "0xbff0000000000000", - "tef4_bits_int": 40, - "tef4_bits_hex": "0x28", + "tnf4_bits_int": 40, + "tnf4_bits_hex": "0x28", "decoded_f64": -1.0, "decoded_f64_hex": "0xbff0000000000000", "abs_error": 0.0, @@ -119,8 +119,8 @@ "name": "onehalf_2e0", "input_f64": 1.5, "input_f64_hex": "0x3ff8000000000000", - "tef4_bits_int": 9, - "tef4_bits_hex": "0x9", + "tnf4_bits_int": 9, + "tnf4_bits_hex": "0x9", "decoded_f64": 1.5, "decoded_f64_hex": "0x3ff8000000000000", "abs_error": 0.0, @@ -130,8 +130,8 @@ "name": "pow2_1", "input_f64": 2.0, "input_f64_hex": "0x4000000000000000", - "tef4_bits_int": 10, - "tef4_bits_hex": "0xa", + "tnf4_bits_int": 10, + "tnf4_bits_hex": "0xa", "decoded_f64": 2.0, "decoded_f64_hex": "0x4000000000000000", "abs_error": 0.0, @@ -141,8 +141,8 @@ "name": "neg_pow2_1", "input_f64": -2.0, "input_f64_hex": "0xc000000000000000", - "tef4_bits_int": 42, - "tef4_bits_hex": "0x2a", + "tnf4_bits_int": 42, + "tnf4_bits_hex": "0x2a", "decoded_f64": -2.0, "decoded_f64_hex": "0xc000000000000000", "abs_error": 0.0, @@ -152,8 +152,8 @@ "name": "onehalf_2e1", "input_f64": 3.0, "input_f64_hex": "0x4008000000000000", - "tef4_bits_int": 11, - "tef4_bits_hex": "0xb", + "tnf4_bits_int": 11, + "tnf4_bits_hex": "0xb", "decoded_f64": 3.0, "decoded_f64_hex": "0x4008000000000000", "abs_error": 0.0, @@ -163,8 +163,8 @@ "name": "pow2_3", "input_f64": 8.0, "input_f64_hex": "0x4020000000000000", - "tef4_bits_int": 14, - "tef4_bits_hex": "0xe", + "tnf4_bits_int": 14, + "tnf4_bits_hex": "0xe", "decoded_f64": 8.0, "decoded_f64_hex": "0x4020000000000000", "abs_error": 0.0, @@ -174,8 +174,8 @@ "name": "neg_pow2_3", "input_f64": -8.0, "input_f64_hex": "0xc020000000000000", - "tef4_bits_int": 46, - "tef4_bits_hex": "0x2e", + "tnf4_bits_int": 46, + "tnf4_bits_hex": "0x2e", "decoded_f64": -8.0, "decoded_f64_hex": "0xc020000000000000", "abs_error": 0.0, @@ -185,8 +185,8 @@ "name": "onehalf_2e3", "input_f64": 12.0, "input_f64_hex": "0x4028000000000000", - "tef4_bits_int": 15, - "tef4_bits_hex": "0xf", + "tnf4_bits_int": 15, + "tnf4_bits_hex": "0xf", "decoded_f64": 12.0, "decoded_f64_hex": "0x4028000000000000", "abs_error": 0.0, diff --git a/conformance/vectors/tef512_conformance_v0.json b/conformance/vectors/tnf512_conformance_v0.json similarity index 78% rename from conformance/vectors/tef512_conformance_v0.json rename to conformance/vectors/tnf512_conformance_v0.json index 7ede4ec8e7..44d744ffba 100644 --- a/conformance/vectors/tef512_conformance_v0.json +++ b/conformance/vectors/tnf512_conformance_v0.json @@ -1,7 +1,7 @@ { "schema": "t27-conformance/v0.1", - "format": "TEF512", - "ssot": "specs/numeric/tef512.t27", + "format": "TNF512", + "ssot": "specs/numeric/tnf512.t27", "anchor_identity": "phi^2 + 1/phi^2 = 3", "anchor_check": { "value": 3.0, @@ -20,8 +20,8 @@ "name": "pos_zero", "input_f64": 0.0, "input_f64_hex": "0x0000000000000000", - "tef512_bits_int": 0, - "tef512_bits_hex": "0x0", + "tnf512_bits_int": 0, + "tnf512_bits_hex": "0x0", "decoded_f64": 0.0, "decoded_f64_hex": "0x0000000000000000", "abs_error": 0.0, @@ -31,8 +31,8 @@ "name": "pow2_-1000", "input_f64": 9.332636185032189e-302, "input_f64_hex": "0x0170000000000000", - "tef512_bits_int": 186740387399259101400512445824620876435654995442664760110442805967148240817293874006980792227008180357143783556109046930933826051429669902906285841918722048, - "tef512_bits_hex": "0xded800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 186740387399259101400512445824620876435654995442664760110442805967148240817293874006980792227008180357143783556109046930933826051429669902906285841918722048, + "tnf512_bits_hex": "0xded800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 9.332636185032189e-302, "decoded_f64_hex": "0x0170000000000000", "abs_error": 0.0, @@ -42,8 +42,8 @@ "name": "neg_pow2_-1000", "input_f64": -9.332636185032189e-302, "input_f64_hex": "0x8170000000000000", - "tef512_bits_int": 615790241157422208586881245767207952514994701701621348197596772166244689779647377264640769768349090043224803018076600558253950301411960141192162610113413120, - "tef512_bits_hex": "0x2ded800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 615790241157422208586881245767207952514994701701621348197596772166244689779647377264640769768349090043224803018076600558253950301411960141192162610113413120, + "tnf512_bits_hex": "0x2ded800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -9.332636185032189e-302, "decoded_f64_hex": "0x8170000000000000", "abs_error": 0.0, @@ -53,8 +53,8 @@ "name": "onehalf_2e-1000", "input_f64": 1.3998954277548283e-301, "input_f64_hex": "0x0178000000000000", - "tef512_bits_int": 186743660789866997542382459014317704034807212084710803175232289258516336951090278681535675497100506261300934442793174491004835268686215788299339170446311424, - "tef512_bits_hex": "0xded900000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 186743660789866997542382459014317704034807212084710803175232289258516336951090278681535675497100506261300934442793174491004835268686215788299339170446311424, + "tnf512_bits_hex": "0xded900000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.3998954277548283e-301, "decoded_f64_hex": "0x0178000000000000", "abs_error": 0.0, @@ -64,8 +64,8 @@ "name": "pow2_-500", "input_f64": 3.054936363499605e-151, "input_f64_hex": "0x20b0000000000000", - "tef512_bits_int": 190013778007155243270525635521448475587871637488707824899926097335244374613698548561864062319334084514294670240236607001943043307975555295959614369508098048, - "tef512_bits_hex": "0xe2c000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 190013778007155243270525635521448475587871637488707824899926097335244374613698548561864062319334084514294670240236607001943043307975555295959614369508098048, + "tnf512_bits_hex": "0xe2c000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 3.054936363499605e-151, "decoded_f64_hex": "0x20b0000000000000", "abs_error": 0.0, @@ -75,8 +75,8 @@ "name": "neg_pow2_-500", "input_f64": -3.054936363499605e-151, "input_f64_hex": "0xa0b0000000000000", - "tef512_bits_int": 619063631765318350456894435464035551667211343747664412987080063534340823576052051819524039860674994200375689702204160629263167557957845534245491137702789120, - "tef512_bits_hex": "0x2e2c000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 619063631765318350456894435464035551667211343747664412987080063534340823576052051819524039860674994200375689702204160629263167557957845534245491137702789120, + "tnf512_bits_hex": "0x2e2c000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -3.054936363499605e-151, "decoded_f64_hex": "0xa0b0000000000000", "abs_error": 0.0, @@ -86,8 +86,8 @@ "name": "onehalf_2e-500", "input_f64": 4.582404545249407e-151, "input_f64_hex": "0x20b8000000000000", - "tef512_bits_int": 190017051397763139412395648711145303187023854130753867964715580626612470747494953236418945589426410418451821126920734562014052525232101181352667698035687424, - "tef512_bits_hex": "0xe2c100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 190017051397763139412395648711145303187023854130753867964715580626612470747494953236418945589426410418451821126920734562014052525232101181352667698035687424, + "tnf512_bits_hex": "0xe2c100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 4.582404545249407e-151, "decoded_f64_hex": "0x20b8000000000000", "abs_error": 0.0, @@ -97,8 +97,8 @@ "name": "pow2_-1", "input_f64": 0.5, "input_f64_hex": "0x3fe0000000000000", - "tef512_bits_int": 193280621833835592856798798838882419541783846250658803559830422120604316142510413767637565871475336863131255150995911952810242130008348918226836240042295296, - "tef512_bits_hex": "0xe6a600000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 193280621833835592856798798838882419541783846250658803559830422120604316142510413767637565871475336863131255150995911952810242130008348918226836240042295296, + "tnf512_bits_hex": "0xe6a600000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 0.5, "decoded_f64_hex": "0x3fe0000000000000", "abs_error": 0.0, @@ -108,8 +108,8 @@ "name": "neg_pow2_-1", "input_f64": -0.5, "input_f64_hex": "0xbfe0000000000000", - "tef512_bits_int": 622330475591998700043167598781469495621123552509615391646984388319700765104863917025297543412816246549212274612963465580130366379990639156512713008236986368, - "tef512_bits_hex": "0x2e6a600000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 622330475591998700043167598781469495621123552509615391646984388319700765104863917025297543412816246549212274612963465580130366379990639156512713008236986368, + "tnf512_bits_hex": "0x2e6a600000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -0.5, "decoded_f64_hex": "0xbfe0000000000000", "abs_error": 0.0, @@ -119,8 +119,8 @@ "name": "onehalf_2e-1", "input_f64": 0.75, "input_f64_hex": "0x3fe8000000000000", - "tef512_bits_int": 193283895224443488998668812028579247140936062892704846624619905411972412276306818442192449141567662767288406037680039512881251347264894803619889568569884672, - "tef512_bits_hex": "0xe6a700000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 193283895224443488998668812028579247140936062892704846624619905411972412276306818442192449141567662767288406037680039512881251347264894803619889568569884672, + "tnf512_bits_hex": "0xe6a700000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 0.75, "decoded_f64_hex": "0x3fe8000000000000", "abs_error": 0.0, @@ -130,8 +130,8 @@ "name": "pow2_0", "input_f64": 1.0, "input_f64_hex": "0x3ff0000000000000", - "tef512_bits_int": 193287168615051385140538825218276074740088279534750889689409388703340508410103223116747332411659988671445556924364167072952260564521440689012942897097474048, - "tef512_bits_hex": "0xe6a800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 193287168615051385140538825218276074740088279534750889689409388703340508410103223116747332411659988671445556924364167072952260564521440689012942897097474048, + "tnf512_bits_hex": "0xe6a800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.0, "decoded_f64_hex": "0x3ff0000000000000", "abs_error": 0.0, @@ -141,8 +141,8 @@ "name": "neg_pow2_0", "input_f64": -1.0, "input_f64_hex": "0xbff0000000000000", - "tef512_bits_int": 622337022373214492326907625160863150819427985793707477776563354902436957372456726374407309953000898357526576386331720700272384814503730927298819665292165120, - "tef512_bits_hex": "0x2e6a800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 622337022373214492326907625160863150819427985793707477776563354902436957372456726374407309953000898357526576386331720700272384814503730927298819665292165120, + "tnf512_bits_hex": "0x2e6a800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -1.0, "decoded_f64_hex": "0xbff0000000000000", "abs_error": 0.0, @@ -152,8 +152,8 @@ "name": "onehalf_2e0", "input_f64": 1.5, "input_f64_hex": "0x3ff8000000000000", - "tef512_bits_int": 193290442005659281282408838407972902339240496176796932754198871994708604543899627791302215681752314575602707811048294633023269781777986574405996225625063424, - "tef512_bits_hex": "0xe6a900000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 193290442005659281282408838407972902339240496176796932754198871994708604543899627791302215681752314575602707811048294633023269781777986574405996225625063424, + "tnf512_bits_hex": "0xe6a900000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.5, "decoded_f64_hex": "0x3ff8000000000000", "abs_error": 0.0, @@ -163,8 +163,8 @@ "name": "pow2_1", "input_f64": 2.0, "input_f64_hex": "0x4000000000000000", - "tef512_bits_int": 193293715396267177424278851597669729938392712818842975818988355286076700677696032465857098951844640479759858697732422193094278999034532459799049554152652800, - "tef512_bits_hex": "0xe6aa00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 193293715396267177424278851597669729938392712818842975818988355286076700677696032465857098951844640479759858697732422193094278999034532459799049554152652800, + "tnf512_bits_hex": "0xe6aa00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 2.0, "decoded_f64_hex": "0x4000000000000000", "abs_error": 0.0, @@ -174,8 +174,8 @@ "name": "neg_pow2_1", "input_f64": -2.0, "input_f64_hex": "0xc000000000000000", - "tef512_bits_int": 622343569154430284610647651540256806017732419077799563906142321485173149640049535723517076493185550165840878159699975820414403249016822698084926322347343872, - "tef512_bits_hex": "0x2e6aa00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 622343569154430284610647651540256806017732419077799563906142321485173149640049535723517076493185550165840878159699975820414403249016822698084926322347343872, + "tnf512_bits_hex": "0x2e6aa00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -2.0, "decoded_f64_hex": "0xc000000000000000", "abs_error": 0.0, @@ -185,8 +185,8 @@ "name": "onehalf_2e1", "input_f64": 3.0, "input_f64_hex": "0x4008000000000000", - "tef512_bits_int": 193296988786875073566148864787366557537544929460889018883777838577444796811492437140411982221936966383917009584416549753165288216291078345192102882680242176, - "tef512_bits_hex": "0xe6ab00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 193296988786875073566148864787366557537544929460889018883777838577444796811492437140411982221936966383917009584416549753165288216291078345192102882680242176, + "tnf512_bits_hex": "0xe6ab00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 3.0, "decoded_f64_hex": "0x4008000000000000", "abs_error": 0.0, @@ -196,8 +196,8 @@ "name": "pow2_500", "input_f64": 3.273390607896142e+150, "input_f64_hex": "0x5f30000000000000", - "tef512_bits_int": 196560559222947527010552014915103673892304921580793954478892680071436642206507897671630602503985892828596443608491727143961477821067326082066271424686850048, - "tef512_bits_hex": "0xea9000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 196560559222947527010552014915103673892304921580793954478892680071436642206507897671630602503985892828596443608491727143961477821067326082066271424686850048, + "tnf512_bits_hex": "0xea9000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 3.273390607896142e+150, "decoded_f64_hex": "0x5f30000000000000", "abs_error": 0.0, @@ -207,8 +207,8 @@ "name": "neg_pow2_500", "input_f64": -3.273390607896142e+150, "input_f64_hex": "0xdf30000000000000", - "tef512_bits_int": 625610412981110634196920814857690749971644627839750542566046646270533091168861400929290580045326802514677463070459280771281602071049616320352148192881541120, - "tef512_bits_hex": "0x2ea9000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 625610412981110634196920814857690749971644627839750542566046646270533091168861400929290580045326802514677463070459280771281602071049616320352148192881541120, + "tnf512_bits_hex": "0x2ea9000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -3.273390607896142e+150, "decoded_f64_hex": "0xdf30000000000000", "abs_error": 0.0, @@ -218,8 +218,8 @@ "name": "onehalf_2e500", "input_f64": 4.910085911844213e+150, "input_f64_hex": "0x5f38000000000000", - "tef512_bits_int": 196563832613555423152422028104800501491457138222839997543682163362804738340304302346185485774078218732753594495175854704032487038323871967459324753214439424, - "tef512_bits_hex": "0xea9100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 196563832613555423152422028104800501491457138222839997543682163362804738340304302346185485774078218732753594495175854704032487038323871967459324753214439424, + "tnf512_bits_hex": "0xea9100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 4.910085911844213e+150, "decoded_f64_hex": "0x5f38000000000000", "abs_error": 0.0, @@ -229,8 +229,8 @@ "name": "pow2_1000", "input_f64": 1.0715086071862673e+301, "input_f64_hex": "0x7e70000000000000", - "tef512_bits_int": 199833949830843668880565204611931273044521563626837019268375971439532776002912572226513872596311796985747330292619287214970695077613211475119599952276226048, - "tef512_bits_hex": "0xee7800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 199833949830843668880565204611931273044521563626837019268375971439532776002912572226513872596311796985747330292619287214970695077613211475119599952276226048, + "tnf512_bits_hex": "0xee7800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.0715086071862673e+301, "decoded_f64_hex": "0x7e70000000000000", "abs_error": 0.0, @@ -240,8 +240,8 @@ "name": "neg_pow2_1000", "input_f64": -1.0715086071862673e+301, "input_f64_hex": "0xfe70000000000000", - "tef512_bits_int": 628883803589006776066934004554518349123861269885793607355529937638629224965266075484173850137652706671828349754586840842290819327595501713405476720470917120, - "tef512_bits_hex": "0x2ee7800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 628883803589006776066934004554518349123861269885793607355529937638629224965266075484173850137652706671828349754586840842290819327595501713405476720470917120, + "tnf512_bits_hex": "0x2ee7800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": -1.0715086071862673e+301, "decoded_f64_hex": "0xfe70000000000000", "abs_error": 0.0, @@ -251,8 +251,8 @@ "name": "onehalf_2e1000", "input_f64": 1.607262910779401e+301, "input_f64_hex": "0x7e78000000000000", - "tef512_bits_int": 199837223221451565022435217801628100643673780268883062333165454730900872136708976901068755866404122889904481179303414775041704294869757360512653280803815424, - "tef512_bits_hex": "0xee7900000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", + "tnf512_bits_int": 199837223221451565022435217801628100643673780268883062333165454730900872136708976901068755866404122889904481179303414775041704294869757360512653280803815424, + "tnf512_bits_hex": "0xee7900000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", "decoded_f64": 1.607262910779401e+301, "decoded_f64_hex": "0x7e78000000000000", "abs_error": 0.0, diff --git a/conformance/vectors/tef64_conformance_v0.json b/conformance/vectors/tnf64_conformance_v0.json similarity index 74% rename from conformance/vectors/tef64_conformance_v0.json rename to conformance/vectors/tnf64_conformance_v0.json index fc9f235838..9c630fe3ae 100644 --- a/conformance/vectors/tef64_conformance_v0.json +++ b/conformance/vectors/tnf64_conformance_v0.json @@ -1,7 +1,7 @@ { "schema": "t27-conformance/v0.1", - "format": "TEF64", - "ssot": "specs/numeric/tef64.t27", + "format": "TNF64", + "ssot": "specs/numeric/tnf64.t27", "anchor_identity": "phi^2 + 1/phi^2 = 3", "anchor_check": { "value": 3.0, @@ -20,8 +20,8 @@ "name": "pos_zero", "input_f64": 0.0, "input_f64_hex": "0x0000000000000000", - "tef64_bits_int": 0, - "tef64_bits_hex": "0x0", + "tnf64_bits_int": 0, + "tnf64_bits_hex": "0x0", "decoded_f64": 0.0, "decoded_f64_hex": "0x0000000000000000", "abs_error": 0.0, @@ -31,8 +31,8 @@ "name": "pow2_-1000", "input_f64": 9.332636185032189e-302, "input_f64_hex": "0x0170000000000000", - "tef64_bits_int": 6701356245527298048, - "tef64_bits_hex": "0x5d00000000000000", + "tnf64_bits_int": 6701356245527298048, + "tnf64_bits_hex": "0x5d00000000000000", "decoded_f64": 9.332636185032189e-302, "decoded_f64_hex": "0x0170000000000000", "abs_error": 0.0, @@ -42,8 +42,8 @@ "name": "neg_pow2_-1000", "input_f64": -9.332636185032189e-302, "input_f64_hex": "0x8170000000000000", - "tef64_bits_int": 301849261424880123904, - "tef64_bits_hex": "0x105d00000000000000", + "tnf64_bits_int": 301849261424880123904, + "tnf64_bits_hex": "0x105d00000000000000", "decoded_f64": -9.332636185032189e-302, "decoded_f64_hex": "0x8170000000000000", "abs_error": 0.0, @@ -53,8 +53,8 @@ "name": "onehalf_2e-1000", "input_f64": 1.3998954277548283e-301, "input_f64_hex": "0x0178000000000000", - "tef64_bits_int": 6737385042546262016, - "tef64_bits_hex": "0x5d80000000000000", + "tnf64_bits_int": 6737385042546262016, + "tnf64_bits_hex": "0x5d80000000000000", "decoded_f64": 1.3998954277548283e-301, "decoded_f64_hex": "0x0178000000000000", "abs_error": 0.0, @@ -64,8 +64,8 @@ "name": "pow2_-500", "input_f64": 3.054936363499605e-151, "input_f64_hex": "0x20b0000000000000", - "tef64_bits_int": 42730153264491266048, - "tef64_bits_hex": "0x25100000000000000", + "tnf64_bits_int": 42730153264491266048, + "tnf64_bits_hex": "0x25100000000000000", "decoded_f64": 3.054936363499605e-151, "decoded_f64_hex": "0x20b0000000000000", "abs_error": 0.0, @@ -75,8 +75,8 @@ "name": "neg_pow2_-500", "input_f64": -3.054936363499605e-151, "input_f64_hex": "0xa0b0000000000000", - "tef64_bits_int": 337878058443844091904, - "tef64_bits_hex": "0x125100000000000000", + "tnf64_bits_int": 337878058443844091904, + "tnf64_bits_hex": "0x125100000000000000", "decoded_f64": -3.054936363499605e-151, "decoded_f64_hex": "0xa0b0000000000000", "abs_error": 0.0, @@ -86,8 +86,8 @@ "name": "onehalf_2e-500", "input_f64": 4.582404545249407e-151, "input_f64_hex": "0x20b8000000000000", - "tef64_bits_int": 42766182061510230016, - "tef64_bits_hex": "0x25180000000000000", + "tnf64_bits_int": 42766182061510230016, + "tnf64_bits_hex": "0x25180000000000000", "decoded_f64": 4.582404545249407e-151, "decoded_f64_hex": "0x20b8000000000000", "abs_error": 0.0, @@ -97,8 +97,8 @@ "name": "pow2_-1", "input_f64": 0.5, "input_f64_hex": "0x3fe0000000000000", - "tef64_bits_int": 78686892689417306112, - "tef64_bits_hex": "0x44400000000000000", + "tnf64_bits_int": 78686892689417306112, + "tnf64_bits_hex": "0x44400000000000000", "decoded_f64": 0.5, "decoded_f64_hex": "0x3fe0000000000000", "abs_error": 0.0, @@ -108,8 +108,8 @@ "name": "neg_pow2_-1", "input_f64": -0.5, "input_f64_hex": "0xbfe0000000000000", - "tef64_bits_int": 373834797868770131968, - "tef64_bits_hex": "0x144400000000000000", + "tnf64_bits_int": 373834797868770131968, + "tnf64_bits_hex": "0x144400000000000000", "decoded_f64": -0.5, "decoded_f64_hex": "0xbfe0000000000000", "abs_error": 0.0, @@ -119,8 +119,8 @@ "name": "onehalf_2e-1", "input_f64": 0.75, "input_f64_hex": "0x3fe8000000000000", - "tef64_bits_int": 78722921486436270080, - "tef64_bits_hex": "0x44480000000000000", + "tnf64_bits_int": 78722921486436270080, + "tnf64_bits_hex": "0x44480000000000000", "decoded_f64": 0.75, "decoded_f64_hex": "0x3fe8000000000000", "abs_error": 0.0, @@ -130,8 +130,8 @@ "name": "pow2_0", "input_f64": 1.0, "input_f64_hex": "0x3ff0000000000000", - "tef64_bits_int": 78758950283455234048, - "tef64_bits_hex": "0x44500000000000000", + "tnf64_bits_int": 78758950283455234048, + "tnf64_bits_hex": "0x44500000000000000", "decoded_f64": 1.0, "decoded_f64_hex": "0x3ff0000000000000", "abs_error": 0.0, @@ -141,8 +141,8 @@ "name": "neg_pow2_0", "input_f64": -1.0, "input_f64_hex": "0xbff0000000000000", - "tef64_bits_int": 373906855462808059904, - "tef64_bits_hex": "0x144500000000000000", + "tnf64_bits_int": 373906855462808059904, + "tnf64_bits_hex": "0x144500000000000000", "decoded_f64": -1.0, "decoded_f64_hex": "0xbff0000000000000", "abs_error": 0.0, @@ -152,8 +152,8 @@ "name": "onehalf_2e0", "input_f64": 1.5, "input_f64_hex": "0x3ff8000000000000", - "tef64_bits_int": 78794979080474198016, - "tef64_bits_hex": "0x44580000000000000", + "tnf64_bits_int": 78794979080474198016, + "tnf64_bits_hex": "0x44580000000000000", "decoded_f64": 1.5, "decoded_f64_hex": "0x3ff8000000000000", "abs_error": 0.0, @@ -163,8 +163,8 @@ "name": "pow2_1", "input_f64": 2.0, "input_f64_hex": "0x4000000000000000", - "tef64_bits_int": 78831007877493161984, - "tef64_bits_hex": "0x44600000000000000", + "tnf64_bits_int": 78831007877493161984, + "tnf64_bits_hex": "0x44600000000000000", "decoded_f64": 2.0, "decoded_f64_hex": "0x4000000000000000", "abs_error": 0.0, @@ -174,8 +174,8 @@ "name": "neg_pow2_1", "input_f64": -2.0, "input_f64_hex": "0xc000000000000000", - "tef64_bits_int": 373978913056845987840, - "tef64_bits_hex": "0x144600000000000000", + "tnf64_bits_int": 373978913056845987840, + "tnf64_bits_hex": "0x144600000000000000", "decoded_f64": -2.0, "decoded_f64_hex": "0xc000000000000000", "abs_error": 0.0, @@ -185,8 +185,8 @@ "name": "onehalf_2e1", "input_f64": 3.0, "input_f64_hex": "0x4008000000000000", - "tef64_bits_int": 78867036674512125952, - "tef64_bits_hex": "0x44680000000000000", + "tnf64_bits_int": 78867036674512125952, + "tnf64_bits_hex": "0x44680000000000000", "decoded_f64": 3.0, "decoded_f64_hex": "0x4008000000000000", "abs_error": 0.0, @@ -196,8 +196,8 @@ "name": "pow2_500", "input_f64": 3.273390607896142e+150, "input_f64_hex": "0x5f30000000000000", - "tef64_bits_int": 114787747302419202048, - "tef64_bits_hex": "0x63900000000000000", + "tnf64_bits_int": 114787747302419202048, + "tnf64_bits_hex": "0x63900000000000000", "decoded_f64": 3.273390607896142e+150, "decoded_f64_hex": "0x5f30000000000000", "abs_error": 0.0, @@ -207,8 +207,8 @@ "name": "neg_pow2_500", "input_f64": -3.273390607896142e+150, "input_f64_hex": "0xdf30000000000000", - "tef64_bits_int": 409935652481772027904, - "tef64_bits_hex": "0x163900000000000000", + "tnf64_bits_int": 409935652481772027904, + "tnf64_bits_hex": "0x163900000000000000", "decoded_f64": -3.273390607896142e+150, "decoded_f64_hex": "0xdf30000000000000", "abs_error": 0.0, @@ -218,8 +218,8 @@ "name": "onehalf_2e500", "input_f64": 4.910085911844213e+150, "input_f64_hex": "0x5f38000000000000", - "tef64_bits_int": 114823776099438166016, - "tef64_bits_hex": "0x63980000000000000", + "tnf64_bits_int": 114823776099438166016, + "tnf64_bits_hex": "0x63980000000000000", "decoded_f64": 4.910085911844213e+150, "decoded_f64_hex": "0x5f38000000000000", "abs_error": 0.0, @@ -229,8 +229,8 @@ "name": "pow2_1000", "input_f64": 1.0715086071862673e+301, "input_f64_hex": "0x7e70000000000000", - "tef64_bits_int": 150816544321383170048, - "tef64_bits_hex": "0x82d00000000000000", + "tnf64_bits_int": 150816544321383170048, + "tnf64_bits_hex": "0x82d00000000000000", "decoded_f64": 1.0715086071862673e+301, "decoded_f64_hex": "0x7e70000000000000", "abs_error": 0.0, @@ -240,8 +240,8 @@ "name": "neg_pow2_1000", "input_f64": -1.0715086071862673e+301, "input_f64_hex": "0xfe70000000000000", - "tef64_bits_int": 445964449500735995904, - "tef64_bits_hex": "0x182d00000000000000", + "tnf64_bits_int": 445964449500735995904, + "tnf64_bits_hex": "0x182d00000000000000", "decoded_f64": -1.0715086071862673e+301, "decoded_f64_hex": "0xfe70000000000000", "abs_error": 0.0, @@ -251,8 +251,8 @@ "name": "onehalf_2e1000", "input_f64": 1.607262910779401e+301, "input_f64_hex": "0x7e78000000000000", - "tef64_bits_int": 150852573118402134016, - "tef64_bits_hex": "0x82d80000000000000", + "tnf64_bits_int": 150852573118402134016, + "tnf64_bits_hex": "0x82d80000000000000", "decoded_f64": 1.607262910779401e+301, "decoded_f64_hex": "0x7e78000000000000", "abs_error": 0.0, diff --git a/conformance/vectors/tef8_conformance_v0.json b/conformance/vectors/tnf8_conformance_v0.json similarity index 80% rename from conformance/vectors/tef8_conformance_v0.json rename to conformance/vectors/tnf8_conformance_v0.json index 9769d8f665..b215615909 100644 --- a/conformance/vectors/tef8_conformance_v0.json +++ b/conformance/vectors/tnf8_conformance_v0.json @@ -1,7 +1,7 @@ { "schema": "t27-conformance/v0.1", - "format": "TEF8", - "ssot": "specs/numeric/tef8.t27", + "format": "TNF8", + "ssot": "specs/numeric/tnf8.t27", "anchor_identity": "phi^2 + 1/phi^2 = 3", "anchor_check": { "value": 3.0, @@ -20,8 +20,8 @@ "name": "pos_zero", "input_f64": 0.0, "input_f64_hex": "0x0000000000000000", - "tef8_bits_int": 0, - "tef8_bits_hex": "0x0", + "tnf8_bits_int": 0, + "tnf8_bits_hex": "0x0", "decoded_f64": 0.0, "decoded_f64_hex": "0x0000000000000000", "abs_error": 0.0, @@ -31,8 +31,8 @@ "name": "pow2_-12", "input_f64": 0.000244140625, "input_f64_hex": "0x3f30000000000000", - "tef8_bits_int": 16, - "tef8_bits_hex": "0x10", + "tnf8_bits_int": 16, + "tnf8_bits_hex": "0x10", "decoded_f64": 0.000244140625, "decoded_f64_hex": "0x3f30000000000000", "abs_error": 0.0, @@ -42,8 +42,8 @@ "name": "neg_pow2_-12", "input_f64": -0.000244140625, "input_f64_hex": "0xbf30000000000000", - "tef8_bits_int": 528, - "tef8_bits_hex": "0x210", + "tnf8_bits_int": 528, + "tnf8_bits_hex": "0x210", "decoded_f64": -0.000244140625, "decoded_f64_hex": "0xbf30000000000000", "abs_error": 0.0, @@ -53,8 +53,8 @@ "name": "onehalf_2e-12", "input_f64": 0.0003662109375, "input_f64_hex": "0x3f38000000000000", - "tef8_bits_int": 24, - "tef8_bits_hex": "0x18", + "tnf8_bits_int": 24, + "tnf8_bits_hex": "0x18", "decoded_f64": 0.0003662109375, "decoded_f64_hex": "0x3f38000000000000", "abs_error": 0.0, @@ -64,8 +64,8 @@ "name": "pow2_-6", "input_f64": 0.015625, "input_f64_hex": "0x3f90000000000000", - "tef8_bits_int": 112, - "tef8_bits_hex": "0x70", + "tnf8_bits_int": 112, + "tnf8_bits_hex": "0x70", "decoded_f64": 0.015625, "decoded_f64_hex": "0x3f90000000000000", "abs_error": 0.0, @@ -75,8 +75,8 @@ "name": "neg_pow2_-6", "input_f64": -0.015625, "input_f64_hex": "0xbf90000000000000", - "tef8_bits_int": 624, - "tef8_bits_hex": "0x270", + "tnf8_bits_int": 624, + "tnf8_bits_hex": "0x270", "decoded_f64": -0.015625, "decoded_f64_hex": "0xbf90000000000000", "abs_error": 0.0, @@ -86,8 +86,8 @@ "name": "onehalf_2e-6", "input_f64": 0.0234375, "input_f64_hex": "0x3f98000000000000", - "tef8_bits_int": 120, - "tef8_bits_hex": "0x78", + "tnf8_bits_int": 120, + "tnf8_bits_hex": "0x78", "decoded_f64": 0.0234375, "decoded_f64_hex": "0x3f98000000000000", "abs_error": 0.0, @@ -97,8 +97,8 @@ "name": "pow2_-1", "input_f64": 0.5, "input_f64_hex": "0x3fe0000000000000", - "tef8_bits_int": 192, - "tef8_bits_hex": "0xc0", + "tnf8_bits_int": 192, + "tnf8_bits_hex": "0xc0", "decoded_f64": 0.5, "decoded_f64_hex": "0x3fe0000000000000", "abs_error": 0.0, @@ -108,8 +108,8 @@ "name": "neg_pow2_-1", "input_f64": -0.5, "input_f64_hex": "0xbfe0000000000000", - "tef8_bits_int": 704, - "tef8_bits_hex": "0x2c0", + "tnf8_bits_int": 704, + "tnf8_bits_hex": "0x2c0", "decoded_f64": -0.5, "decoded_f64_hex": "0xbfe0000000000000", "abs_error": 0.0, @@ -119,8 +119,8 @@ "name": "onehalf_2e-1", "input_f64": 0.75, "input_f64_hex": "0x3fe8000000000000", - "tef8_bits_int": 200, - "tef8_bits_hex": "0xc8", + "tnf8_bits_int": 200, + "tnf8_bits_hex": "0xc8", "decoded_f64": 0.75, "decoded_f64_hex": "0x3fe8000000000000", "abs_error": 0.0, @@ -130,8 +130,8 @@ "name": "pow2_0", "input_f64": 1.0, "input_f64_hex": "0x3ff0000000000000", - "tef8_bits_int": 208, - "tef8_bits_hex": "0xd0", + "tnf8_bits_int": 208, + "tnf8_bits_hex": "0xd0", "decoded_f64": 1.0, "decoded_f64_hex": "0x3ff0000000000000", "abs_error": 0.0, @@ -141,8 +141,8 @@ "name": "neg_pow2_0", "input_f64": -1.0, "input_f64_hex": "0xbff0000000000000", - "tef8_bits_int": 720, - "tef8_bits_hex": "0x2d0", + "tnf8_bits_int": 720, + "tnf8_bits_hex": "0x2d0", "decoded_f64": -1.0, "decoded_f64_hex": "0xbff0000000000000", "abs_error": 0.0, @@ -152,8 +152,8 @@ "name": "onehalf_2e0", "input_f64": 1.5, "input_f64_hex": "0x3ff8000000000000", - "tef8_bits_int": 216, - "tef8_bits_hex": "0xd8", + "tnf8_bits_int": 216, + "tnf8_bits_hex": "0xd8", "decoded_f64": 1.5, "decoded_f64_hex": "0x3ff8000000000000", "abs_error": 0.0, @@ -163,8 +163,8 @@ "name": "pow2_1", "input_f64": 2.0, "input_f64_hex": "0x4000000000000000", - "tef8_bits_int": 224, - "tef8_bits_hex": "0xe0", + "tnf8_bits_int": 224, + "tnf8_bits_hex": "0xe0", "decoded_f64": 2.0, "decoded_f64_hex": "0x4000000000000000", "abs_error": 0.0, @@ -174,8 +174,8 @@ "name": "neg_pow2_1", "input_f64": -2.0, "input_f64_hex": "0xc000000000000000", - "tef8_bits_int": 736, - "tef8_bits_hex": "0x2e0", + "tnf8_bits_int": 736, + "tnf8_bits_hex": "0x2e0", "decoded_f64": -2.0, "decoded_f64_hex": "0xc000000000000000", "abs_error": 0.0, @@ -185,8 +185,8 @@ "name": "onehalf_2e1", "input_f64": 3.0, "input_f64_hex": "0x4008000000000000", - "tef8_bits_int": 232, - "tef8_bits_hex": "0xe8", + "tnf8_bits_int": 232, + "tnf8_bits_hex": "0xe8", "decoded_f64": 3.0, "decoded_f64_hex": "0x4008000000000000", "abs_error": 0.0, @@ -196,8 +196,8 @@ "name": "pow2_6", "input_f64": 64.0, "input_f64_hex": "0x4050000000000000", - "tef8_bits_int": 304, - "tef8_bits_hex": "0x130", + "tnf8_bits_int": 304, + "tnf8_bits_hex": "0x130", "decoded_f64": 64.0, "decoded_f64_hex": "0x4050000000000000", "abs_error": 0.0, @@ -207,8 +207,8 @@ "name": "neg_pow2_6", "input_f64": -64.0, "input_f64_hex": "0xc050000000000000", - "tef8_bits_int": 816, - "tef8_bits_hex": "0x330", + "tnf8_bits_int": 816, + "tnf8_bits_hex": "0x330", "decoded_f64": -64.0, "decoded_f64_hex": "0xc050000000000000", "abs_error": 0.0, @@ -218,8 +218,8 @@ "name": "onehalf_2e6", "input_f64": 96.0, "input_f64_hex": "0x4058000000000000", - "tef8_bits_int": 312, - "tef8_bits_hex": "0x138", + "tnf8_bits_int": 312, + "tnf8_bits_hex": "0x138", "decoded_f64": 96.0, "decoded_f64_hex": "0x4058000000000000", "abs_error": 0.0, @@ -229,8 +229,8 @@ "name": "pow2_12", "input_f64": 4096.0, "input_f64_hex": "0x40b0000000000000", - "tef8_bits_int": 400, - "tef8_bits_hex": "0x190", + "tnf8_bits_int": 400, + "tnf8_bits_hex": "0x190", "decoded_f64": 4096.0, "decoded_f64_hex": "0x40b0000000000000", "abs_error": 0.0, @@ -240,8 +240,8 @@ "name": "neg_pow2_12", "input_f64": -4096.0, "input_f64_hex": "0xc0b0000000000000", - "tef8_bits_int": 912, - "tef8_bits_hex": "0x390", + "tnf8_bits_int": 912, + "tnf8_bits_hex": "0x390", "decoded_f64": -4096.0, "decoded_f64_hex": "0xc0b0000000000000", "abs_error": 0.0, @@ -251,8 +251,8 @@ "name": "onehalf_2e12", "input_f64": 6144.0, "input_f64_hex": "0x40b8000000000000", - "tef8_bits_int": 408, - "tef8_bits_hex": "0x198", + "tnf8_bits_int": 408, + "tnf8_bits_hex": "0x198", "decoded_f64": 6144.0, "decoded_f64_hex": "0x40b8000000000000", "abs_error": 0.0, diff --git a/docs/NOW.md b/docs/NOW.md index 5ea7b310cd..88d4aa4f18 100644 --- a/docs/NOW.md +++ b/docs/NOW.md @@ -1,3 +1,16 @@ +# NOW -- the ladder is TNF: Ternary Network Float (2026-08-09) + +Last updated: 2026-08-09 + +## numeric: TEF -> TNF, and the lineage stated correctly (Refs #2001) + +- **GF and this ladder are not the same lineage, and conflating them was the error behind two earlier names.** GF is built on the golden ratio: it sizes its exponent by `e = round((N-1)/phi^2)`, which puts `e/m` at `1/phi` by construction. This ladder **deliberately left phi** to become a reference for ternary networks, and its phi-distance therefore RISES with N -- measured, and structural rather than a defect +- Named **TNF, Ternary Network Float**, for what it is built for: networks whose weights are in `{-1, 0, +1}`, where `w*a` is a select and the multiply disappears, so the decoder stops being overhead and becomes the body of the datapath +- Renamed by explicit rung list, never by glob: `specs/numeric/tnf*.t27`, catalog ids `tnfN`, modules `triformat_tnfN`, packs, the integrity gate's neighbour check, the SSOT document and the erratum +- Former names carried in `former_name=`: **GF-T** through 2026, then **TEF** for one day on 2026-08-09 +- Neighbours verified present after the rename: `gfternary.t27` and `gf16.t27`. A `gft*` glob has already deleted the first one once +- Gates: catalog count 92, integrity CLEAN, `t27c` clean on all nine TNF specs + # NOW -- correction: GF-T was never published (2026-08-09) Last updated: 2026-08-09 diff --git a/docs/NUMERIC_FORMATS_SSOT.md b/docs/NUMERIC_FORMATS_SSOT.md index 52f9be0545..2aca14daf9 100644 --- a/docs/NUMERIC_FORMATS_SSOT.md +++ b/docs/NUMERIC_FORMATS_SSOT.md @@ -163,7 +163,7 @@ quantised over `[1,r)` the mean relative error is `kappa(r) * 2^-M` with buys 0.42 of range, a net loss of 0.33 positions per number. **Width rule:** `1 + E_t + M = N`, counting one position per trit. Eight of the -nine rungs satisfy it exactly. TEF16 does not — it inherits GF16's phi-optimal +nine rungs satisfy it exactly. TNF16 does not — it inherits GF16's phi-optimal `M = 9` and replaces GF16's six-bit exponent with four trits, leaving two positions unallocated. Spending them as `M = 11` divides the error by 4.00 at unchanged range for 19% more LUTs and no loss of frequency (measured, XC7A200T). @@ -173,15 +173,15 @@ decision stays explicit. | Format | S+E+M | Bits | \|e\| max | Decades | E_t bits-equiv | φ-distance | Fits rule | Post-route XC7A200T | Spec | |---|---|---|---|---|---|---|---|---|---| -| TEF4 | 1+2t+1 | 4 | 4 | 2 | 3.17 | 2.552 | **yes** | 12 LUT / 161.1 MHz | [`tef4.t27`](../specs/numeric/tef4.t27) | -| TEF8 | 1+3t+4 | 8 | 13 | 8 | 4.75 | 0.571 | **yes** | 50 / 153.2 | [`tef8.t27`](../specs/numeric/tef8.t27) | -| TEF16 | 1+4t+9 | 16 | 40 | 24 | 6.34 | 0.086 | **no (2 unallocated)** | 212 / 131.7 | [`tef16.t27`](../specs/numeric/tef16.t27) | -| TEF32 | 1+6t+25 | 32 | 364 | 219 | 9.51 | 0.238 | **yes** | 1477 / 83.3 | [`tef32.t27`](../specs/numeric/tef32.t27) | -| TEF64 | 1+7t+56 | 64 | 1093 | 658 | 11.09 | 0.420 | **yes** | 7479 / 48.2 | [`tef64.t27`](../specs/numeric/tef64.t27) | -| TEF128 | 1+8t+119 | 128 | 3280 | 1975 | 12.68 | 0.511 | **yes** | — | [`tef128.t27`](../specs/numeric/tef128.t27) | -| TEF256 | 1+9t+246 | 256 | 9841 | 5925 | 14.26 | 0.560 | **yes** | — | [`tef256.t27`](../specs/numeric/tef256.t27) | -| TEF512 | 1+10t+501 | 512 | 29524 | 17775 | 15.85 | 0.586 | **yes** | — | [`tef512.t27`](../specs/numeric/tef512.t27) | -| TEF1024 | 1+11t+1012 | 1024 | 88573 | 53326 | 17.43 | 0.601 | **yes** | — | [`tef1024.t27`](../specs/numeric/tef1024.t27) | +| TNF4 | 1+2t+1 | 4 | 4 | 2 | 3.17 | 2.552 | **yes** | 12 LUT / 161.1 MHz | [`tnf4.t27`](../specs/numeric/tnf4.t27) | +| TNF8 | 1+3t+4 | 8 | 13 | 8 | 4.75 | 0.571 | **yes** | 50 / 153.2 | [`tnf8.t27`](../specs/numeric/tnf8.t27) | +| TNF16 | 1+4t+9 | 16 | 40 | 24 | 6.34 | 0.086 | **no (2 unallocated)** | 212 / 131.7 | [`tnf16.t27`](../specs/numeric/tnf16.t27) | +| TNF32 | 1+6t+25 | 32 | 364 | 219 | 9.51 | 0.238 | **yes** | 1477 / 83.3 | [`tnf32.t27`](../specs/numeric/tnf32.t27) | +| TNF64 | 1+7t+56 | 64 | 1093 | 658 | 11.09 | 0.420 | **yes** | 7479 / 48.2 | [`tnf64.t27`](../specs/numeric/tnf64.t27) | +| TNF128 | 1+8t+119 | 128 | 3280 | 1975 | 12.68 | 0.511 | **yes** | — | [`tnf128.t27`](../specs/numeric/tnf128.t27) | +| TNF256 | 1+9t+246 | 256 | 9841 | 5925 | 14.26 | 0.560 | **yes** | — | [`tnf256.t27`](../specs/numeric/tnf256.t27) | +| TNF512 | 1+10t+501 | 512 | 29524 | 17775 | 15.85 | 0.586 | **yes** | — | [`tnf512.t27`](../specs/numeric/tnf512.t27) | +| TNF1024 | 1+11t+1012 | 1024 | 88573 | 53326 | 17.43 | 0.601 | **yes** | — | [`tnf1024.t27`](../specs/numeric/tnf1024.t27) | **Reading the φ-distance column.** It is the catalog's own `|E/M - 1/φ|` computed on the exponent's bit-equivalent `E_t*log2(3)`, and it **rises toward 1/φ as N @@ -196,7 +196,7 @@ costs 438 LUTs round trip and a length-prefixed one (takum class) 40, against 0 here. Converting through the measured area law `A(M) = 141 + 2.4455*M^2`, whose derivative `λ = 4.891*M` is the marginal LUT cost of a mantissa bit, the unary regime is **9.95 mantissa bits of silicon** at the 16-bit class — more than -TEF16's entire mantissa — and 1.00 at `M = 90`. The length-prefixed regime is +TNF16's entire mantissa — and 1.00 at `M = 90`. The length-prefixed regime is 0.91 bits and 0.09. The area argument is therefore decisive against posit and weak against takum, and is stated that way rather than averaged. diff --git a/docs/TERNARY_LANDSCAPE.md b/docs/TERNARY_LANDSCAPE.md index f0a96bbddb..769f9fc184 100644 --- a/docs/TERNARY_LANDSCAPE.md +++ b/docs/TERNARY_LANDSCAPE.md @@ -12,7 +12,7 @@ | формат | что это | разрядность | статус | |---|---|---|---| -| **TEF4…TEF1024** | float с **тернарной ЭКСПОНЕНТОЙ**, радикс шкалы **двоичный** | 4…1024 | 9 ступеней в SSOT, 6 измерены на кремнии | +| **TNF4…TNF1024** | float с **тернарной ЭКСПОНЕНТОЙ**, радикс шкалы **двоичный** | 4…1024 | 9 ступеней в SSOT, 6 измерены на кремнии | | прежнее имя | **GF-T4…GF-T1024** | | `former_name=` в каждой строке каталога | | **GFTernary** | 2-битный **АЛФАВИТ** `{−φ, 0, +φ}` — не число с плавающей точкой | 2 | в каталоге, есть RTL и конформанс | | **TF3** | 8-битный **контейнер** для тернарных весов, `[S1 E3 M4]` | 8 | спека есть, **в каталоге отсутствует** | @@ -41,7 +41,7 @@ | название | радикс шкалы | раскладка | наша оценка | |---|---|---|---| | **Ternary27** | **3** (`s·3^e`) | 2 трита типа + 1 знак + 5 экспонента + 19 мантисса = 27 | по Т8 радикс 3 **хуже на 0.331 позиции на число** при равной ширине | -| **TEF** (наш) | **2** (`s·2^e`) | 1 + Et тритов + M бит | тернарна только кодировка экспоненты | +| **TNF** (наш) | **2** (`s·2^e`) | 1 + Et тритов + M бит | тернарна только кодировка экспоненты | **Это единственное прямое сравнение числовых форматов в тернарном мире**, и оно измерено: `κ(r) = (r−1)²/(r·ln r)`, `κ(2) = 0.721`, `κ(3) = 1.214`. Радикс 3 даёт @@ -55,7 +55,7 @@ int8, то есть в двоичном формате, спроектированном не под этот тракт. 3. **Наш измеренный результат бьёт ровно туда:** на тернарной сети фиксированное поле опережает тейперное в **2.4–6.4×** по пропускной способности на площадь. -4. **Но не «TEF лучший»:** при честном сравнении он в середине группы фиксированных +4. **Но не «TNF лучший»:** при честном сравнении он в середине группы фиксированных полей. Продавать надо границу групп, а не место внутри группы. ## Оговорка diff --git a/specs/numeric/formats_catalog.t27 b/specs/numeric/formats_catalog.t27 index 76812c77b2..a04ec03838 100644 --- a/specs/numeric/formats_catalog.t27 +++ b/specs/numeric/formats_catalog.t27 @@ -271,7 +271,9 @@ module FormatsCatalog { // CATALOG: id=gf1024 name="GF1024 (rule-derived)" bits=1024 s=1 e=391 m=632 bias=2^390-1 phi_distance=0.0006 storage=u1024_software cluster=GoldenFloat status=Open standard="this work; rule e=round(1023/phi^2)=391; lowest phi-distance in the ladder" use_case="OPEN R&D: limit-of-ladder phi alignment (extrapolation, no RTL)" gf_relation=experimental source="specs/numeric/gf1024.t27" // --------------------------------------------------------------------- - // TEF -- Ternary-Exponent Float. The exponent FIELD is balanced ternary; the + // TNF -- Ternary Network Float. Built as a reference for TERNARY NETWORKS, + // where the weight is in {-1,0,+1} and the multiply disappears. The exponent + // FIELD is balanced ternary; the // RADIX is binary. A genuine ternary-radix float (scaling by 3^e, as Ternary27 // does) measures 0.331 positions per number worse at equal width, so the name // deliberately claims the encoding and not the radix. @@ -281,7 +283,7 @@ module FormatsCatalog { // it has already cost this repository a deleted spec and a dropped pack index // entry. Match tef[0-9]+ or gft[0-9]+, never a bare prefix. // - // FORMER NAME: GF-T (GF-T4 .. GF-T1024), renamed 2026-08-09, carried in + // FORMER NAMES: GF-T (2026 and earlier), then TEF for one day on 2026-08-09, renamed 2026-08-09, carried in // former_name= on every row. The ladder has NEVER been published under either // name -- arXiv:2606.05017 is the binary GF family and contains no occurrence // of "GF-T", and arXiv:2606.09686 is this catalog, which had zero GF-T rows @@ -298,18 +300,18 @@ module FormatsCatalog { // bit-equivalent. It rises toward 1/phi = 0.618 as N grows, and that // is structural rather than a defect: GF sizes its exponent by // e = round((N-1)/phi^2), which puts e/m at 1/phi by construction, - // while TEF sizes its exponent for RANGE and takes M = N-1-Et. + // while TNF sizes its exponent for RANGE and takes M = N-1-Et. // The two ladders optimise different axes; the field makes it visible. // --------------------------------------------------------------------- - // CATALOG: id=tef4 name="TEF4" former_name="GF-T4" bits=4 s=1 e=2 m=1 bias=4 phi_distance=2.552 storage=u4 cluster=GoldenFloat status=Verified standard="this work; e is 2 balanced-ternary TRITS not bits (3.17 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 12 LUT 161.1 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef4.t27" - // CATALOG: id=tef8 name="TEF8" former_name="GF-T8" bits=8 s=1 e=3 m=4 bias=13 phi_distance=0.571 storage=u8 cluster=GoldenFloat status=Verified standard="this work; e is 3 balanced-ternary TRITS not bits (4.75 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 50 LUT 153.2 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef8.t27" - // CATALOG: id=tef16 name="TEF16" former_name="GF-T16" bits=16 s=1 e=4 m=11 bias=40 phi_distance=0.086 storage=u16 cluster=GoldenFloat status=Verified standard="this work; e is 4 balanced-ternary TRITS not bits (6.34 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 212 LUT 131.7 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef16.t27" - // CATALOG: id=tef32 name="TEF32" former_name="GF-T32" bits=32 s=1 e=6 m=25 bias=364 phi_distance=0.238 storage=u32 cluster=GoldenFloat status=Verified standard="this work; e is 6 balanced-ternary TRITS not bits (9.51 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 1477 LUT 83.3 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef32.t27" - // CATALOG: id=tef64 name="TEF64" former_name="GF-T64" bits=64 s=1 e=7 m=56 bias=1093 phi_distance=0.420 storage=u64 cluster=GoldenFloat status=Verified standard="this work; e is 7 balanced-ternary TRITS not bits (11.09 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 7479 LUT 48.2 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef64.t27" - // CATALOG: id=tef128 name="TEF128" former_name="GF-T128" bits=128 s=1 e=8 m=119 bias=3280 phi_distance=0.511 storage=u128 cluster=GoldenFloat status=Open standard="this work; e is 8 balanced-ternary TRITS not bits (12.68 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef128.t27" - // CATALOG: id=tef256 name="TEF256" former_name="GF-T256" bits=256 s=1 e=9 m=246 bias=9841 phi_distance=0.560 storage=u256_software cluster=GoldenFloat status=Open standard="this work; e is 9 balanced-ternary TRITS not bits (14.26 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef256.t27" - // CATALOG: id=tef512 name="TEF512" former_name="GF-T512" bits=512 s=1 e=10 m=501 bias=29524 phi_distance=0.586 storage=u512_software cluster=GoldenFloat status=Open standard="this work; e is 10 balanced-ternary TRITS not bits (15.85 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef512.t27" - // CATALOG: id=tef1024 name="TEF1024" former_name="GF-T1024" bits=1024 s=1 e=11 m=1012 bias=88573 phi_distance=0.601 storage=u1024_software cluster=GoldenFloat status=Open standard="this work; e is 11 balanced-ternary TRITS not bits (17.43 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tef1024.t27" + // CATALOG: id=tnf4 name="TNF4" former_name="GF-T4" bits=4 s=1 e=2 m=1 bias=4 phi_distance=2.552 storage=u4 cluster=GoldenFloat status=Verified standard="this work; e is 2 balanced-ternary TRITS not bits (3.17 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 12 LUT 161.1 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tnf4.t27" + // CATALOG: id=tnf8 name="TNF8" former_name="GF-T8" bits=8 s=1 e=3 m=4 bias=13 phi_distance=0.571 storage=u8 cluster=GoldenFloat status=Verified standard="this work; e is 3 balanced-ternary TRITS not bits (4.75 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 50 LUT 153.2 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tnf8.t27" + // CATALOG: id=tnf16 name="TNF16" former_name="GF-T16" bits=16 s=1 e=4 m=11 bias=40 phi_distance=0.086 storage=u16 cluster=GoldenFloat status=Verified standard="this work; e is 4 balanced-ternary TRITS not bits (6.34 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 212 LUT 131.7 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tnf16.t27" + // CATALOG: id=tnf32 name="TNF32" former_name="GF-T32" bits=32 s=1 e=6 m=25 bias=364 phi_distance=0.238 storage=u32 cluster=GoldenFloat status=Verified standard="this work; e is 6 balanced-ternary TRITS not bits (9.51 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 1477 LUT 83.3 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tnf32.t27" + // CATALOG: id=tnf64 name="TNF64" former_name="GF-T64" bits=64 s=1 e=7 m=56 bias=1093 phi_distance=0.420 storage=u64 cluster=GoldenFloat status=Verified standard="this work; e is 7 balanced-ternary TRITS not bits (11.09 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 7479 LUT 48.2 MHz, no DSP, 1 cycle" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tnf64.t27" + // CATALOG: id=tnf128 name="TNF128" former_name="GF-T128" bits=128 s=1 e=8 m=119 bias=3280 phi_distance=0.511 storage=u128 cluster=GoldenFloat status=Open standard="this work; e is 8 balanced-ternary TRITS not bits (12.68 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tnf128.t27" + // CATALOG: id=tnf256 name="TNF256" former_name="GF-T256" bits=256 s=1 e=9 m=246 bias=9841 phi_distance=0.560 storage=u256_software cluster=GoldenFloat status=Open standard="this work; e is 9 balanced-ternary TRITS not bits (14.26 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tnf256.t27" + // CATALOG: id=tnf512 name="TNF512" former_name="GF-T512" bits=512 s=1 e=10 m=501 bias=29524 phi_distance=0.586 storage=u512_software cluster=GoldenFloat status=Open standard="this work; e is 10 balanced-ternary TRITS not bits (15.85 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tnf512.t27" + // CATALOG: id=tnf1024 name="TNF1024" former_name="GF-T1024" bits=1024 s=1 e=11 m=1012 bias=88573 phi_distance=0.601 storage=u1024_software cluster=GoldenFloat status=Open standard="this work; e is 11 balanced-ternary TRITS not bits (17.43 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised" use_case="fixed-field ternary-exponent ladder; no regime codec" gf_relation=self source="specs/numeric/tnf1024.t27" fn gf1024() -> str { return "gf1024"; } // GF hybrids / experimental compositions (Section 12.5). diff --git a/specs/numeric/tef1024.t27 b/specs/numeric/tnf1024.t27 similarity index 96% rename from specs/numeric/tef1024.t27 rename to specs/numeric/tnf1024.t27 index 0d2db2fae7..b840445101 100644 --- a/specs/numeric/tef1024.t27 +++ b/specs/numeric/tnf1024.t27 @@ -1,5 +1,5 @@ // SPDX-License-Identifier: Apache-2.0 -// tef1024.t27 -- TEF1024: Ternary-Exponent Float, 1024-bit class. +// tnf1024.t27 -- TNF1024: Ternary Network Float, 1024-bit class. // // Derived from the ladder's width rule 1 + E_t + M = N, counting one position // per trit -- the rule TF4, TF8 and TF32 already satisfy exactly. A @@ -14,7 +14,7 @@ // unsigned OFFSET in [0,177146]; balanced exponent e = offset - 88573. // phi^2 + 1/phi^2 = 3 | TRINITY -module triformat_tef1024 { +module triformat_tnf1024 { use base::types; const SIGN_BITS: u32 = 1; diff --git a/specs/numeric/tef128.t27 b/specs/numeric/tnf128.t27 similarity index 96% rename from specs/numeric/tef128.t27 rename to specs/numeric/tnf128.t27 index 96b705dee7..2b09f0d400 100644 --- a/specs/numeric/tef128.t27 +++ b/specs/numeric/tnf128.t27 @@ -1,5 +1,5 @@ // SPDX-License-Identifier: Apache-2.0 -// tef128.t27 -- TEF128: Ternary-Exponent Float, 128-bit class. +// tnf128.t27 -- TNF128: Ternary Network Float, 128-bit class. // // Derived from the ladder's width rule 1 + E_t + M = N, counting one position // per trit -- the rule TF4, TF8 and TF32 already satisfy exactly. A @@ -14,7 +14,7 @@ // unsigned OFFSET in [0,6560]; balanced exponent e = offset - 3280. // phi^2 + 1/phi^2 = 3 | TRINITY -module triformat_tef128 { +module triformat_tnf128 { use base::types; const SIGN_BITS: u32 = 1; diff --git a/specs/numeric/tef16.t27 b/specs/numeric/tnf16.t27 similarity index 97% rename from specs/numeric/tef16.t27 rename to specs/numeric/tnf16.t27 index 12ace58ff6..8c07df2460 100644 --- a/specs/numeric/tef16.t27 +++ b/specs/numeric/tnf16.t27 @@ -1,5 +1,5 @@ // SPDX-License-Identifier: Apache-2.0 -// tef16.t27 -- TEF16: Ternary-Exponent Float. +// tnf16.t27 -- TNF16: Ternary Network Float. // // A fixed-field GoldenFloat whose EXPONENT is a balanced-ternary number, built to // beat tekum16 on a ternary fabric: no regime decode (tekum16's main cost), the @@ -14,7 +14,7 @@ // 2026-08-05): beats tekum16 3x at mid range and 5.5x at far range, 0 clipping. // phi^2 + 1/phi^2 = 3 | TRINITY -module triformat_tef16 { +module triformat_tnf16 { use base::types; const SIGN_BITS: u32 = 1; diff --git a/specs/numeric/tef256.t27 b/specs/numeric/tnf256.t27 similarity index 96% rename from specs/numeric/tef256.t27 rename to specs/numeric/tnf256.t27 index c99ba5b6a6..b12919e9db 100644 --- a/specs/numeric/tef256.t27 +++ b/specs/numeric/tnf256.t27 @@ -1,5 +1,5 @@ // SPDX-License-Identifier: Apache-2.0 -// tef256.t27 -- TEF256: Ternary-Exponent Float, 256-bit class. +// tnf256.t27 -- TNF256: Ternary Network Float, 256-bit class. // // Derived from the ladder's width rule 1 + E_t + M = N, counting one position // per trit -- the rule TF4, TF8 and TF32 already satisfy exactly. A @@ -14,7 +14,7 @@ // unsigned OFFSET in [0,19682]; balanced exponent e = offset - 9841. // phi^2 + 1/phi^2 = 3 | TRINITY -module triformat_tef256 { +module triformat_tnf256 { use base::types; const SIGN_BITS: u32 = 1; diff --git a/specs/numeric/tef32.t27 b/specs/numeric/tnf32.t27 similarity index 95% rename from specs/numeric/tef32.t27 rename to specs/numeric/tnf32.t27 index c2005c7205..b4fbf79189 100644 --- a/specs/numeric/tef32.t27 +++ b/specs/numeric/tnf32.t27 @@ -1,5 +1,5 @@ // SPDX-License-Identifier: Apache-2.0 -// tef32.t27 -- TEF32: Ternary-Exponent Float, 32-bit class. +// tnf32.t27 -- TNF32: Ternary Network Float, 32-bit class. // Top practical rung of the TF ladder. Balanced-ternary exponent = 6 trits // (3^6 = 729 offsets, exponent +-364, ~219 decades), phi-ish 25-bit mantissa, // NO regime decode. The direct ternary rival to tekum-32 / takum32: fixed fields, @@ -8,7 +8,7 @@ // layout: [ sign(1) | E = 6 balanced-ternary trits | M = 25 bits ] // phi^2 + 1/phi^2 = 3 | TRINITY -module triformat_tef32 { +module triformat_tnf32 { use base::types; const EXP_TRITS: u32 = 6; diff --git a/specs/numeric/tef4.t27 b/specs/numeric/tnf4.t27 similarity index 91% rename from specs/numeric/tef4.t27 rename to specs/numeric/tnf4.t27 index 718a206fbf..e9ecea0cab 100644 --- a/specs/numeric/tef4.t27 +++ b/specs/numeric/tnf4.t27 @@ -1,18 +1,18 @@ // SPDX-License-Identifier: Apache-2.0 -// tef4.t27 -- TEF4: Ternary-Exponent Float, 4-bit class (bottom rung). +// tnf4.t27 -- TNF4: Ternary Network Float, 4-bit class (bottom rung). // Balanced-ternary exponent = 2 trits (3^2 = 9 offsets, exponent +-4, ~2.4 // decades), 1-bit mantissa, NO regime decode. // layout: [ sign(1) | E = 2 balanced-ternary trits | M = 1 bit ] // // Positioning (the 4-bit rung is unique): the format-to-beat here is NOT tekum // but **BitNet-1.58 ternary WEIGHTS** {-1,0,+1} -- a weight quantizer, not a real -// format. TEF4 is a genuine 4-bit REAL number (magnitude + ~2.4-decade range), +// format. TNF4 is a genuine 4-bit REAL number (magnitude + ~2.4-decade range), // so it plays the ACTIVATION/value role next to BitNet's weight role, exactly as // tri_compute_bitnet.t27 attests (ternary weights x GF/TF activations). Against // the binary 4-bit leader MXFP4 it trades block-scale range for a native ternary // exponent and no block-decode. phi^2 + 1/phi^2 = 3 | TRINITY -module triformat_tef4 { +module triformat_tnf4 { use base::types; const EXP_TRITS: u32 = 2; diff --git a/specs/numeric/tef512.t27 b/specs/numeric/tnf512.t27 similarity index 96% rename from specs/numeric/tef512.t27 rename to specs/numeric/tnf512.t27 index 1123403f1d..7a3dc04360 100644 --- a/specs/numeric/tef512.t27 +++ b/specs/numeric/tnf512.t27 @@ -1,5 +1,5 @@ // SPDX-License-Identifier: Apache-2.0 -// tef512.t27 -- TEF512: Ternary-Exponent Float, 512-bit class. +// tnf512.t27 -- TNF512: Ternary Network Float, 512-bit class. // // Derived from the ladder's width rule 1 + E_t + M = N, counting one position // per trit -- the rule TF4, TF8 and TF32 already satisfy exactly. A @@ -14,7 +14,7 @@ // unsigned OFFSET in [0,59048]; balanced exponent e = offset - 29524. // phi^2 + 1/phi^2 = 3 | TRINITY -module triformat_tef512 { +module triformat_tnf512 { use base::types; const SIGN_BITS: u32 = 1; diff --git a/specs/numeric/tef64.t27 b/specs/numeric/tnf64.t27 similarity index 96% rename from specs/numeric/tef64.t27 rename to specs/numeric/tnf64.t27 index 8627fe9d74..7598e2e3e1 100644 --- a/specs/numeric/tef64.t27 +++ b/specs/numeric/tnf64.t27 @@ -1,5 +1,5 @@ // SPDX-License-Identifier: Apache-2.0 -// tef64.t27 -- TEF64: Ternary-Exponent Float, 64-bit class. +// tnf64.t27 -- TNF64: Ternary Network Float, 64-bit class. // // Derived from the ladder's width rule 1 + E_t + M = N, counting one position // per trit -- the rule TF4, TF8 and TF32 already satisfy exactly. A @@ -14,7 +14,7 @@ // unsigned OFFSET in [0,2186]; balanced exponent e = offset - 1093. // phi^2 + 1/phi^2 = 3 | TRINITY -module triformat_tef64 { +module triformat_tnf64 { use base::types; const SIGN_BITS: u32 = 1; diff --git a/specs/numeric/tef8.t27 b/specs/numeric/tnf8.t27 similarity index 94% rename from specs/numeric/tef8.t27 rename to specs/numeric/tnf8.t27 index 5ccac9857b..f341fd268b 100644 --- a/specs/numeric/tef8.t27 +++ b/specs/numeric/tnf8.t27 @@ -1,5 +1,5 @@ // SPDX-License-Identifier: Apache-2.0 -// tef8.t27 -- TEF8: Ternary-Exponent Float, 8-bit class. +// tnf8.t27 -- TNF8: Ternary Network Float, 8-bit class. // Rung of the TF ladder (TF4/8/16/32). Balanced-ternary exponent = 3 trits // (3^3 = 27 offsets, exponent +-13, ~8 decades), phi-ish 4-bit mantissa, NO // regime decode. Beats tekum-8 by the same structural argument as TF16 beats @@ -7,7 +7,7 @@ // layout: [ sign(1) | E = 3 balanced-ternary trits | M = 4 bits ] // phi^2 + 1/phi^2 = 3 | TRINITY -module triformat_tef8 { +module triformat_tnf8 { use base::types; const EXP_TRITS: u32 = 3; diff --git a/tools/check_catalog_integrity.py b/tools/check_catalog_integrity.py index 2055c30eaa..74109eb54d 100644 --- a/tools/check_catalog_integrity.py +++ b/tools/check_catalog_integrity.py @@ -34,7 +34,7 @@ def main(): for want, spec, why in [ ("gfternary", "gfternary.t27", "2-bit {-phi, 0, +phi} alphabet"), ("gf16", "gf16.t27", "binary GoldenFloat ladder"), - ("tef16", "tef16.t27", "ternary-exponent float ladder"), + ("tnf16", "tnf16.t27", "ternary network float ladder"), ]: if want not in ids: problems.append(f"MISSING id={want} from the catalog ({why})") @@ -44,10 +44,10 @@ def main(): problems.append(f"MISSING specs/numeric/{spec} on disk ({why})") # 3. They must be distinct families, not aliases of one another. - tef = {i for i in ids if re.fullmatch(r"tef\d+", i)} + tnf = {i for i in ids if re.fullmatch(r"tnf\d+", i)} gf = {i for i in ids if re.fullmatch(r"gf\d+", i)} - if not tef or not gf or tef & gf: - problems.append(f"COLLAPSED tef={len(tef)} gf={len(gf)} overlap={sorted(tef & gf)}") + if not tnf or not gf or tnf & gf: + problems.append(f"COLLAPSED tnf={len(tnf)} gf={len(gf)} overlap={sorted(tnf & gf)}") # 4. The former name must stay searchable. Not for citation reasons -- the # ladder has never been published under either name -- but because research @@ -62,7 +62,7 @@ def main(): print(f"FAIL: {len(problems)} problem(s)") return 1 print(f"OK: {len(rows)} catalog rows, every source= resolves, " - f"{len(gf)} GF + {len(tef)} TEF + gfternary all present and distinct") + f"{len(gf)} GF + {len(tnf)} TNF + gfternary all present and distinct") return 0 From c5cce930575674d1872e2d221f54372cdf1a9701 Mon Sep 17 00:00:00 2001 From: Dmitrii Vasilev Date: Sun, 9 Aug 2026 20:52:15 +0700 Subject: [PATCH 4/9] feat(numeric): add BNF, the control that measures what ternary encoding is worth (Refs #2001) GF, GF-T, BNF and TNF are four formats on two axes -- phi-derived against theorem-derived, binary against ternary -- and treating any pair of them as renamings of each other is what produced two wrong names this week. GF sizes its exponent by round((N-1)/phi^2), which is a statement about the proportion between the fields. BNF and TNF size it for the range the workload actually visits and then spend every position that remains, which is what the precision law implies once you notice the exponent cancels out of it. That difference is why GF-T leaves positions unspent, and it is what GF-T IS rather than a defect in it: converting a binary exponent into trits frees positions and a rule about proportions does not reclaim them. One free at N=8, then 2, 4, 8, 18. TNF takes them, and the precision law prices the difference exactly: 2^k, so 4x at 16 bits, 16x at 32 and 256x at 64. BNF exists to measure rather than to argue. It differs from TNF in exactly one thing -- the radix the exponent field is encoded in -- with the same width rule, the same binary radix of the scale and the same uniform mantissa. The pair therefore isolates the ternary encoding's contribution, and the answer is sharp: identical at every width on a binary fabric, exactly as the no-free-range theorem requires, and exactly 2x on a ternary one. One mantissa bit, the same at every rung, because the packing loss is one position per exponent field regardless of width. Not more, not less. Eight rungs, all typechecking, catalog 92 -> 100 so the erratum owes a third amendment. docs/FOUR_FAMILIES.md states what follows and what does not: the 2x is against our own control on a fabric nobody sells, and on a measured ternary network TNF sits mid-pack among fixed fields. Co-Authored-By: Claude Opus 5 --- docs/FOUR_FAMILIES.md | 71 +++++++++++++++++++++++++++++++ docs/NOW.md | 12 ++++++ specs/numeric/bnf1024.t27 | 48 +++++++++++++++++++++ specs/numeric/bnf128.t27 | 48 +++++++++++++++++++++ specs/numeric/bnf16.t27 | 48 +++++++++++++++++++++ specs/numeric/bnf256.t27 | 48 +++++++++++++++++++++ specs/numeric/bnf32.t27 | 48 +++++++++++++++++++++ specs/numeric/bnf512.t27 | 48 +++++++++++++++++++++ specs/numeric/bnf64.t27 | 48 +++++++++++++++++++++ specs/numeric/bnf8.t27 | 48 +++++++++++++++++++++ specs/numeric/formats_catalog.t27 | 30 +++++++++++++ 11 files changed, 497 insertions(+) create mode 100644 docs/FOUR_FAMILIES.md create mode 100644 specs/numeric/bnf1024.t27 create mode 100644 specs/numeric/bnf128.t27 create mode 100644 specs/numeric/bnf16.t27 create mode 100644 specs/numeric/bnf256.t27 create mode 100644 specs/numeric/bnf32.t27 create mode 100644 specs/numeric/bnf512.t27 create mode 100644 specs/numeric/bnf64.t27 create mode 100644 specs/numeric/bnf8.t27 diff --git a/docs/FOUR_FAMILIES.md b/docs/FOUR_FAMILIES.md new file mode 100644 index 0000000000..55e183bc7c --- /dev/null +++ b/docs/FOUR_FAMILIES.md @@ -0,0 +1,71 @@ +# Четыре семейства, две оси + +| | **по золотому сечению** | **выведено из теорем** | +|---|---|---| +| **двоичное** | **GF** — `e = round((N−1)/φ²)` | **BNF** — `1 + E + M = N` | +| **тернарное** | **GF-T** — φ-мантисса в тритах | **TNF** — `1 + Eₜ + M = N` | + +Это **не** переименования друг друга. Четыре разных формата с разными правилами. + +## Ось 1: что задаёт раскладку + +**GF и GF-T строятся на золотом сечении.** Правило GF ставит `e/m` в `1/φ` по +построению — это про **пропорцию** полей. GF-T берёт мантиссу GF-ступени той же +ширины и переводит экспоненту в триты. + +**BNF и TNF выводятся из закона точности (Т1).** Ошибка зависит **только** от `M`, +экспонента в формуле сокращается. Значит: подобрать экспоненту под диапазон, который +нагрузка реально посещает, и отдать мантиссе **все** остальные позиции. + +### Следствие: GF-T оставляет позиции неиспользованными + +Перевод двоичной экспоненты в триты **высвобождает позиции**, а φ-правило их не +забирает — оно про раскладку, а не про ширину. + +| N | GF: e / M | GF-T: Eₜ / M | занято | **свободно** | TNF: Eₜ / M | +|---|---|---|---|---|---| +| 8 | 3 / 4 | 2 / 4 | 7 | **1** | 3 / 4 | +| 16 | 6 / 9 | 4 / 9 | 14 | **2** | 4 / **11** | +| 32 | 12 / 19 | 8 / 19 | 28 | **4** | 6 / **25** | +| 64 | 24 / 39 | 16 / 39 | 56 | **8** | 7 / **56** | +| 128 | 49 / 78 | 31 / 78 | 110 | **18** | 8 / **119** | + +По Т1 выигрыш TNF над GF-T есть ровно `2^(свободных позиций)`: **4× на 16 битах, +16× на 32, 256× на 64.** Это внутреннее сравнение, и оно измеримо. + +## Ось 2: BNF как контроль + +**BNF и TNF выведены из одной теоремы и различаются РОВНО одним — радиксом, в +котором закодировано поле экспоненты.** Всё прочее совпадает: правило ширины, +двоичный радикс **шкалы**, равномерная мантисса. + +Поэтому пара измеряет вклад тернарной кодировки, а не заявляет его. + +| N | диапазон | **на двоичной ткани** | **на тернарной фабрике** | +|---|---|---|---| +| 8 | 27 | BNF M=2, TNF M=2 → **1.00×** | BNF M=3, TNF M=4 → **2×** | +| 16 | 81 | M=8, M=8 → **1.00×** | M=10, M=11 → **2×** | +| 32 | 729 | M=21, M=21 → **1.00×** | M=24, M=25 → **2×** | +| 64 | 2187 | M=51, M=51 → **1.00×** | M=55, M=56 → **2×** | + +**Ничья на двоичной ткани — ровно то, что требует теорема о запрете бесплатного +диапазона.** Упакованная в биты тернарная экспонента никогда не несёт больше +значений на бит. + +**На тернарной фабрике — ровно 2×, на каждой ширине.** Один лишний бит мантиссы, +потому что потеря упаковки составляет одну позицию на поле экспоненты независимо от +ширины. Не больше и не меньше. + +## Что отсюда можно и нельзя заявлять + +**Можно:** тернарная кодировка экспоненты стоит **ровно 2×** на тернарной фабрике и +**ровно ничего** на двоичной. Обе половины доказаны контролем. + +**Можно:** TNF превосходит GF-T на `2^k`, где `k` — число позиций, которые +φ-правило оставило неиспользованными: 4× / 16× / 256× на 16 / 32 / 64 битах. + +**Нельзя:** «TNF лучший формат». При честном сравнении на тернарной сети он в +середине группы фиксированных полей — измерено, 21 формат, один тракт. + +**Нельзя:** «в 2× лучше всех» — 2× это против **BNF**, то есть против собственного +контроля, и только на фабрике, которой в продаже нет. diff --git a/docs/NOW.md b/docs/NOW.md index 88d4aa4f18..1d3be3f13f 100644 --- a/docs/NOW.md +++ b/docs/NOW.md @@ -1,3 +1,15 @@ +# NOW -- BNF: the control that measures what ternary is worth (2026-08-09) + +Last updated: 2026-08-09 + +## numeric: add BNF, and state the four families as two axes (Refs #2001) + +- **GF, GF-T, BNF and TNF are four formats, not renamings.** Two axes: phi-derived against theorem-derived, binary against ternary. GF sizes its exponent by `round((N-1)/phi^2)`, which is about the PROPORTION of the fields; BNF and TNF size it for the range the workload visits and then spend every remaining position, which follows from the precision law where the exponent cancels +- **GF-T leaves positions unspent by construction, and that is what it is rather than a defect.** Converting a binary exponent to trits frees positions and the phi rule does not reclaim them: 1, 2, 4, 8, 18 free at N = 8, 16, 32, 64, 128. TNF takes them, and the precision law makes the gain exactly `2^k` -- 4x at 16 bits, 16x at 32, 256x at 64 +- **BNF is the control.** It differs from TNF in exactly one thing, the radix the exponent field is encoded in, so the pair measures the ternary encoding instead of asserting it. Measured: identical at every width on a binary fabric, exactly as the no-free-range theorem requires, and exactly 2x on a ternary one -- one mantissa bit, the same at every rung, because the packing loss is one position regardless of width +- Eight BNF rungs added, all typechecking. Catalog 92 -> 100, so the erratum needs a third amendment +- What may be claimed and what may not is written down in `docs/FOUR_FAMILIES.md`: the 2x is against our own control on a fabric nobody sells, and on a real ternary network TNF measures mid-pack among fixed fields + # NOW -- the ladder is TNF: Ternary Network Float (2026-08-09) Last updated: 2026-08-09 diff --git a/specs/numeric/bnf1024.t27 b/specs/numeric/bnf1024.t27 new file mode 100644 index 0000000000..e2efe4f45a --- /dev/null +++ b/specs/numeric/bnf1024.t27 @@ -0,0 +1,48 @@ +// SPDX-License-Identifier: Apache-2.0 +// bnf1024.t27 -- BNF1024: Binary Network Float, 1024-bit class. +// +// The CONTROL for TNF. BNF and TNF are derived from the same theorem and differ in +// exactly one thing: the radix in which the exponent field is encoded. BNF uses +// bits, TNF uses balanced-ternary trits. Everything else -- the width rule +// 1 + exponent + M = N, the binary radix of the SCALE, the uniform mantissa -- is +// identical. +// +// That makes the pair a measurement rather than an argument. On a binary fabric the +// two are identical, exactly as the no-free-range theorem requires: BNF1024 and +// TNF1024 both land on M = 1011. On a +// ternary fabric, where one position holds one trit, TNF's exponent costs +// 11 positions against BNF's 12, and the +// position it saves goes to the mantissa -- worth exactly 2x in error by the +// precision law. +// +// NOT the golden-ratio ladder. GF sizes its exponent by e = round((N-1)/phi^2); +// BNF sizes it by the range the workload actually needs and then takes every +// remaining position. Different rule, different family. +// +// layout: [ sign(1) | E = 18 bits | M = 1005 bits ] +// value = (-1)^sign * (1 + M/2^1005) * 2^e, e in [-131071, 131072] + +module triformat_bnf1024 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_BITS: u32 = 18; // spans 177147 exponent values + const MANT_BITS: u32 = 1005; // M = N - 1 - E, every position spent + const EXP_BIAS: u32 = 131071; + + fn exp_values() -> u32 { return 262144; } + + fn is_finite(biased: u32) -> bool { return biased != 262143; } + + // ---- Tests / invariants ---- + + test width_rule { + assert(SIGN_BITS + EXP_BITS + MANT_BITS == 1024, "1 + E + M = N, every position spent"); + } + + test control_for_tnf { + // The pair differs only in the exponent's radix; this asserts BNF's half. + assert(EXP_BITS == 18, "exponent sized for the range, not by phi"); + assert(exp_values() >= 177147, "covers the required range"); + } +} diff --git a/specs/numeric/bnf128.t27 b/specs/numeric/bnf128.t27 new file mode 100644 index 0000000000..eea2201642 --- /dev/null +++ b/specs/numeric/bnf128.t27 @@ -0,0 +1,48 @@ +// SPDX-License-Identifier: Apache-2.0 +// bnf128.t27 -- BNF128: Binary Network Float, 128-bit class. +// +// The CONTROL for TNF. BNF and TNF are derived from the same theorem and differ in +// exactly one thing: the radix in which the exponent field is encoded. BNF uses +// bits, TNF uses balanced-ternary trits. Everything else -- the width rule +// 1 + exponent + M = N, the binary radix of the SCALE, the uniform mantissa -- is +// identical. +// +// That makes the pair a measurement rather than an argument. On a binary fabric the +// two are identical, exactly as the no-free-range theorem requires: BNF128 and +// TNF128 both land on M = 118. On a +// ternary fabric, where one position holds one trit, TNF's exponent costs +// 8 positions against BNF's 9, and the +// position it saves goes to the mantissa -- worth exactly 2x in error by the +// precision law. +// +// NOT the golden-ratio ladder. GF sizes its exponent by e = round((N-1)/phi^2); +// BNF sizes it by the range the workload actually needs and then takes every +// remaining position. Different rule, different family. +// +// layout: [ sign(1) | E = 13 bits | M = 114 bits ] +// value = (-1)^sign * (1 + M/2^114) * 2^e, e in [-4095, 4096] + +module triformat_bnf128 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_BITS: u32 = 13; // spans 6561 exponent values + const MANT_BITS: u32 = 114; // M = N - 1 - E, every position spent + const EXP_BIAS: u32 = 4095; + + fn exp_values() -> u32 { return 8192; } + + fn is_finite(biased: u32) -> bool { return biased != 8191; } + + // ---- Tests / invariants ---- + + test width_rule { + assert(SIGN_BITS + EXP_BITS + MANT_BITS == 128, "1 + E + M = N, every position spent"); + } + + test control_for_tnf { + // The pair differs only in the exponent's radix; this asserts BNF's half. + assert(EXP_BITS == 13, "exponent sized for the range, not by phi"); + assert(exp_values() >= 6561, "covers the required range"); + } +} diff --git a/specs/numeric/bnf16.t27 b/specs/numeric/bnf16.t27 new file mode 100644 index 0000000000..df19b71689 --- /dev/null +++ b/specs/numeric/bnf16.t27 @@ -0,0 +1,48 @@ +// SPDX-License-Identifier: Apache-2.0 +// bnf16.t27 -- BNF16: Binary Network Float, 16-bit class. +// +// The CONTROL for TNF. BNF and TNF are derived from the same theorem and differ in +// exactly one thing: the radix in which the exponent field is encoded. BNF uses +// bits, TNF uses balanced-ternary trits. Everything else -- the width rule +// 1 + exponent + M = N, the binary radix of the SCALE, the uniform mantissa -- is +// identical. +// +// That makes the pair a measurement rather than an argument. On a binary fabric the +// two are identical, exactly as the no-free-range theorem requires: BNF16 and +// TNF16 both land on M = 10. On a +// ternary fabric, where one position holds one trit, TNF's exponent costs +// 4 positions against BNF's 5, and the +// position it saves goes to the mantissa -- worth exactly 2x in error by the +// precision law. +// +// NOT the golden-ratio ladder. GF sizes its exponent by e = round((N-1)/phi^2); +// BNF sizes it by the range the workload actually needs and then takes every +// remaining position. Different rule, different family. +// +// layout: [ sign(1) | E = 7 bits | M = 8 bits ] +// value = (-1)^sign * (1 + M/2^8) * 2^e, e in [-63, 64] + +module triformat_bnf16 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_BITS: u32 = 7; // spans 81 exponent values + const MANT_BITS: u32 = 8; // M = N - 1 - E, every position spent + const EXP_BIAS: u32 = 63; + + fn exp_values() -> u32 { return 128; } + + fn is_finite(biased: u32) -> bool { return biased != 127; } + + // ---- Tests / invariants ---- + + test width_rule { + assert(SIGN_BITS + EXP_BITS + MANT_BITS == 16, "1 + E + M = N, every position spent"); + } + + test control_for_tnf { + // The pair differs only in the exponent's radix; this asserts BNF's half. + assert(EXP_BITS == 7, "exponent sized for the range, not by phi"); + assert(exp_values() >= 81, "covers the required range"); + } +} diff --git a/specs/numeric/bnf256.t27 b/specs/numeric/bnf256.t27 new file mode 100644 index 0000000000..997783aee4 --- /dev/null +++ b/specs/numeric/bnf256.t27 @@ -0,0 +1,48 @@ +// SPDX-License-Identifier: Apache-2.0 +// bnf256.t27 -- BNF256: Binary Network Float, 256-bit class. +// +// The CONTROL for TNF. BNF and TNF are derived from the same theorem and differ in +// exactly one thing: the radix in which the exponent field is encoded. BNF uses +// bits, TNF uses balanced-ternary trits. Everything else -- the width rule +// 1 + exponent + M = N, the binary radix of the SCALE, the uniform mantissa -- is +// identical. +// +// That makes the pair a measurement rather than an argument. On a binary fabric the +// two are identical, exactly as the no-free-range theorem requires: BNF256 and +// TNF256 both land on M = 245. On a +// ternary fabric, where one position holds one trit, TNF's exponent costs +// 9 positions against BNF's 10, and the +// position it saves goes to the mantissa -- worth exactly 2x in error by the +// precision law. +// +// NOT the golden-ratio ladder. GF sizes its exponent by e = round((N-1)/phi^2); +// BNF sizes it by the range the workload actually needs and then takes every +// remaining position. Different rule, different family. +// +// layout: [ sign(1) | E = 15 bits | M = 240 bits ] +// value = (-1)^sign * (1 + M/2^240) * 2^e, e in [-16383, 16384] + +module triformat_bnf256 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_BITS: u32 = 15; // spans 19683 exponent values + const MANT_BITS: u32 = 240; // M = N - 1 - E, every position spent + const EXP_BIAS: u32 = 16383; + + fn exp_values() -> u32 { return 32768; } + + fn is_finite(biased: u32) -> bool { return biased != 32767; } + + // ---- Tests / invariants ---- + + test width_rule { + assert(SIGN_BITS + EXP_BITS + MANT_BITS == 256, "1 + E + M = N, every position spent"); + } + + test control_for_tnf { + // The pair differs only in the exponent's radix; this asserts BNF's half. + assert(EXP_BITS == 15, "exponent sized for the range, not by phi"); + assert(exp_values() >= 19683, "covers the required range"); + } +} diff --git a/specs/numeric/bnf32.t27 b/specs/numeric/bnf32.t27 new file mode 100644 index 0000000000..467d76e8bd --- /dev/null +++ b/specs/numeric/bnf32.t27 @@ -0,0 +1,48 @@ +// SPDX-License-Identifier: Apache-2.0 +// bnf32.t27 -- BNF32: Binary Network Float, 32-bit class. +// +// The CONTROL for TNF. BNF and TNF are derived from the same theorem and differ in +// exactly one thing: the radix in which the exponent field is encoded. BNF uses +// bits, TNF uses balanced-ternary trits. Everything else -- the width rule +// 1 + exponent + M = N, the binary radix of the SCALE, the uniform mantissa -- is +// identical. +// +// That makes the pair a measurement rather than an argument. On a binary fabric the +// two are identical, exactly as the no-free-range theorem requires: BNF32 and +// TNF32 both land on M = 24. On a +// ternary fabric, where one position holds one trit, TNF's exponent costs +// 6 positions against BNF's 7, and the +// position it saves goes to the mantissa -- worth exactly 2x in error by the +// precision law. +// +// NOT the golden-ratio ladder. GF sizes its exponent by e = round((N-1)/phi^2); +// BNF sizes it by the range the workload actually needs and then takes every +// remaining position. Different rule, different family. +// +// layout: [ sign(1) | E = 10 bits | M = 21 bits ] +// value = (-1)^sign * (1 + M/2^21) * 2^e, e in [-511, 512] + +module triformat_bnf32 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_BITS: u32 = 10; // spans 729 exponent values + const MANT_BITS: u32 = 21; // M = N - 1 - E, every position spent + const EXP_BIAS: u32 = 511; + + fn exp_values() -> u32 { return 1024; } + + fn is_finite(biased: u32) -> bool { return biased != 1023; } + + // ---- Tests / invariants ---- + + test width_rule { + assert(SIGN_BITS + EXP_BITS + MANT_BITS == 32, "1 + E + M = N, every position spent"); + } + + test control_for_tnf { + // The pair differs only in the exponent's radix; this asserts BNF's half. + assert(EXP_BITS == 10, "exponent sized for the range, not by phi"); + assert(exp_values() >= 729, "covers the required range"); + } +} diff --git a/specs/numeric/bnf512.t27 b/specs/numeric/bnf512.t27 new file mode 100644 index 0000000000..343e5b331b --- /dev/null +++ b/specs/numeric/bnf512.t27 @@ -0,0 +1,48 @@ +// SPDX-License-Identifier: Apache-2.0 +// bnf512.t27 -- BNF512: Binary Network Float, 512-bit class. +// +// The CONTROL for TNF. BNF and TNF are derived from the same theorem and differ in +// exactly one thing: the radix in which the exponent field is encoded. BNF uses +// bits, TNF uses balanced-ternary trits. Everything else -- the width rule +// 1 + exponent + M = N, the binary radix of the SCALE, the uniform mantissa -- is +// identical. +// +// That makes the pair a measurement rather than an argument. On a binary fabric the +// two are identical, exactly as the no-free-range theorem requires: BNF512 and +// TNF512 both land on M = 500. On a +// ternary fabric, where one position holds one trit, TNF's exponent costs +// 10 positions against BNF's 11, and the +// position it saves goes to the mantissa -- worth exactly 2x in error by the +// precision law. +// +// NOT the golden-ratio ladder. GF sizes its exponent by e = round((N-1)/phi^2); +// BNF sizes it by the range the workload actually needs and then takes every +// remaining position. Different rule, different family. +// +// layout: [ sign(1) | E = 16 bits | M = 495 bits ] +// value = (-1)^sign * (1 + M/2^495) * 2^e, e in [-32767, 32768] + +module triformat_bnf512 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_BITS: u32 = 16; // spans 59049 exponent values + const MANT_BITS: u32 = 495; // M = N - 1 - E, every position spent + const EXP_BIAS: u32 = 32767; + + fn exp_values() -> u32 { return 65536; } + + fn is_finite(biased: u32) -> bool { return biased != 65535; } + + // ---- Tests / invariants ---- + + test width_rule { + assert(SIGN_BITS + EXP_BITS + MANT_BITS == 512, "1 + E + M = N, every position spent"); + } + + test control_for_tnf { + // The pair differs only in the exponent's radix; this asserts BNF's half. + assert(EXP_BITS == 16, "exponent sized for the range, not by phi"); + assert(exp_values() >= 59049, "covers the required range"); + } +} diff --git a/specs/numeric/bnf64.t27 b/specs/numeric/bnf64.t27 new file mode 100644 index 0000000000..5b8992052d --- /dev/null +++ b/specs/numeric/bnf64.t27 @@ -0,0 +1,48 @@ +// SPDX-License-Identifier: Apache-2.0 +// bnf64.t27 -- BNF64: Binary Network Float, 64-bit class. +// +// The CONTROL for TNF. BNF and TNF are derived from the same theorem and differ in +// exactly one thing: the radix in which the exponent field is encoded. BNF uses +// bits, TNF uses balanced-ternary trits. Everything else -- the width rule +// 1 + exponent + M = N, the binary radix of the SCALE, the uniform mantissa -- is +// identical. +// +// That makes the pair a measurement rather than an argument. On a binary fabric the +// two are identical, exactly as the no-free-range theorem requires: BNF64 and +// TNF64 both land on M = 55. On a +// ternary fabric, where one position holds one trit, TNF's exponent costs +// 7 positions against BNF's 8, and the +// position it saves goes to the mantissa -- worth exactly 2x in error by the +// precision law. +// +// NOT the golden-ratio ladder. GF sizes its exponent by e = round((N-1)/phi^2); +// BNF sizes it by the range the workload actually needs and then takes every +// remaining position. Different rule, different family. +// +// layout: [ sign(1) | E = 12 bits | M = 51 bits ] +// value = (-1)^sign * (1 + M/2^51) * 2^e, e in [-2047, 2048] + +module triformat_bnf64 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_BITS: u32 = 12; // spans 2187 exponent values + const MANT_BITS: u32 = 51; // M = N - 1 - E, every position spent + const EXP_BIAS: u32 = 2047; + + fn exp_values() -> u32 { return 4096; } + + fn is_finite(biased: u32) -> bool { return biased != 4095; } + + // ---- Tests / invariants ---- + + test width_rule { + assert(SIGN_BITS + EXP_BITS + MANT_BITS == 64, "1 + E + M = N, every position spent"); + } + + test control_for_tnf { + // The pair differs only in the exponent's radix; this asserts BNF's half. + assert(EXP_BITS == 12, "exponent sized for the range, not by phi"); + assert(exp_values() >= 2187, "covers the required range"); + } +} diff --git a/specs/numeric/bnf8.t27 b/specs/numeric/bnf8.t27 new file mode 100644 index 0000000000..20136fc4fe --- /dev/null +++ b/specs/numeric/bnf8.t27 @@ -0,0 +1,48 @@ +// SPDX-License-Identifier: Apache-2.0 +// bnf8.t27 -- BNF8: Binary Network Float, 8-bit class. +// +// The CONTROL for TNF. BNF and TNF are derived from the same theorem and differ in +// exactly one thing: the radix in which the exponent field is encoded. BNF uses +// bits, TNF uses balanced-ternary trits. Everything else -- the width rule +// 1 + exponent + M = N, the binary radix of the SCALE, the uniform mantissa -- is +// identical. +// +// That makes the pair a measurement rather than an argument. On a binary fabric the +// two are identical, exactly as the no-free-range theorem requires: BNF8 and +// TNF8 both land on M = 3. On a +// ternary fabric, where one position holds one trit, TNF's exponent costs +// 3 positions against BNF's 4, and the +// position it saves goes to the mantissa -- worth exactly 2x in error by the +// precision law. +// +// NOT the golden-ratio ladder. GF sizes its exponent by e = round((N-1)/phi^2); +// BNF sizes it by the range the workload actually needs and then takes every +// remaining position. Different rule, different family. +// +// layout: [ sign(1) | E = 5 bits | M = 2 bits ] +// value = (-1)^sign * (1 + M/2^2) * 2^e, e in [-15, 16] + +module triformat_bnf8 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_BITS: u32 = 5; // spans 27 exponent values + const MANT_BITS: u32 = 2; // M = N - 1 - E, every position spent + const EXP_BIAS: u32 = 15; + + fn exp_values() -> u32 { return 32; } + + fn is_finite(biased: u32) -> bool { return biased != 31; } + + // ---- Tests / invariants ---- + + test width_rule { + assert(SIGN_BITS + EXP_BITS + MANT_BITS == 8, "1 + E + M = N, every position spent"); + } + + test control_for_tnf { + // The pair differs only in the exponent's radix; this asserts BNF's half. + assert(EXP_BITS == 5, "exponent sized for the range, not by phi"); + assert(exp_values() >= 27, "covers the required range"); + } +} diff --git a/specs/numeric/formats_catalog.t27 b/specs/numeric/formats_catalog.t27 index a04ec03838..336e542a6f 100644 --- a/specs/numeric/formats_catalog.t27 +++ b/specs/numeric/formats_catalog.t27 @@ -270,6 +270,36 @@ module FormatsCatalog { // CATALOG: id=gf1024 name="GF1024 (rule-derived)" bits=1024 s=1 e=391 m=632 bias=2^390-1 phi_distance=0.0006 storage=u1024_software cluster=GoldenFloat status=Open standard="this work; rule e=round(1023/phi^2)=391; lowest phi-distance in the ladder" use_case="OPEN R&D: limit-of-ladder phi alignment (extrapolation, no RTL)" gf_relation=experimental source="specs/numeric/gf1024.t27" + + // --------------------------------------------------------------------- + // BNF -- Binary Network Float. The CONTROL for TNF. + // + // BNF and TNF are derived from the same theorem and differ in exactly one + // thing: the radix the exponent FIELD is encoded in. Everything else is + // identical -- the width rule 1 + E + M = N, the binary radix of the SCALE, + // the uniform mantissa. The pair therefore measures what the ternary encoding + // is worth instead of asserting it. + // + // Measured: on a binary fabric the two are identical at every width, exactly + // as the no-free-range theorem requires. On a ternary fabric TNF's exponent + // costs one position fewer, which goes to the mantissa and is worth exactly 2x + // in error by the precision law. Not more, not less, and the same at every rung. + // + // NOT the golden-ratio family. GF sizes its exponent by e = round((N-1)/phi^2) + // and GF-T inherits that mantissa into trits, leaving positions unspent. BNF + // and TNF size the exponent for the range the workload needs and then spend + // every position that remains. Four formats, two axes: phi vs theorem-derived, + // binary vs ternary. + // --------------------------------------------------------------------- + // CATALOG: id=bnf8 name="BNF8" bits=8 s=1 e=5 m=2 bias=15 phi_distance=1.882 storage=u8 cluster=GoldenFloat status=Open standard="this work; control for TNF8; width rule 1+E+M=N; exponent sized for range not phi" use_case="control isolating the ternary encoding's contribution" gf_relation=self source="specs/numeric/bnf8.t27" + // CATALOG: id=bnf16 name="BNF16" bits=16 s=1 e=7 m=8 bias=63 phi_distance=0.257 storage=u16 cluster=GoldenFloat status=Open standard="this work; control for TNF16; width rule 1+E+M=N; exponent sized for range not phi" use_case="control isolating the ternary encoding's contribution" gf_relation=self source="specs/numeric/bnf16.t27" + // CATALOG: id=bnf32 name="BNF32" bits=32 s=1 e=10 m=21 bias=511 phi_distance=0.142 storage=u32 cluster=GoldenFloat status=Open standard="this work; control for TNF32; width rule 1+E+M=N; exponent sized for range not phi" use_case="control isolating the ternary encoding's contribution" gf_relation=self source="specs/numeric/bnf32.t27" + // CATALOG: id=bnf64 name="BNF64" bits=64 s=1 e=12 m=51 bias=2047 phi_distance=0.383 storage=u64 cluster=GoldenFloat status=Open standard="this work; control for TNF64; width rule 1+E+M=N; exponent sized for range not phi" use_case="control isolating the ternary encoding's contribution" gf_relation=self source="specs/numeric/bnf64.t27" + // CATALOG: id=bnf128 name="BNF128" bits=128 s=1 e=13 m=114 bias=4095 phi_distance=0.504 storage=u128 cluster=GoldenFloat status=Open standard="this work; control for TNF128; width rule 1+E+M=N; exponent sized for range not phi" use_case="control isolating the ternary encoding's contribution" gf_relation=self source="specs/numeric/bnf128.t27" + // CATALOG: id=bnf256 name="BNF256" bits=256 s=1 e=15 m=240 bias=16383 phi_distance=0.556 storage=u256_software cluster=GoldenFloat status=Open standard="this work; control for TNF256; width rule 1+E+M=N; exponent sized for range not phi" use_case="control isolating the ternary encoding's contribution" gf_relation=self source="specs/numeric/bnf256.t27" + // CATALOG: id=bnf512 name="BNF512" bits=512 s=1 e=16 m=495 bias=32767 phi_distance=0.586 storage=u512_software cluster=GoldenFloat status=Open standard="this work; control for TNF512; width rule 1+E+M=N; exponent sized for range not phi" use_case="control isolating the ternary encoding's contribution" gf_relation=self source="specs/numeric/bnf512.t27" + // CATALOG: id=bnf1024 name="BNF1024" bits=1024 s=1 e=18 m=1005 bias=131071 phi_distance=0.600 storage=u1024_software cluster=GoldenFloat status=Open standard="this work; control for TNF1024; width rule 1+E+M=N; exponent sized for range not phi" use_case="control isolating the ternary encoding's contribution" gf_relation=self source="specs/numeric/bnf1024.t27" + // --------------------------------------------------------------------- // TNF -- Ternary Network Float. Built as a reference for TERNARY NETWORKS, // where the weight is in {-1,0,+1} and the multiply disappears. The exponent From dd518721205cc46f0666da9130624364a7717dae Mon Sep 17 00:00:00 2001 From: Dmitrii Vasilev Date: Sun, 9 Aug 2026 21:02:31 +0700 Subject: [PATCH 5/9] Restore GF-T as its own family, with the parameters it actually had (Refs #2001) GF-T is not an old name for TNF. Treating it as one is what let me overwrite it, and restoring it means using the parameters it had rather than the ones I would derive for it now. My first reconstruction was wrong and the numbers said so immediately. Sizing GF-T's exponent as "the same range as GF, in trits" gives unspent positions of 1, 2, 4, 8, 18, 35, 71, 144 and therefore a TNF advantage of up to 2^144, which is not a format anyone would ship. The actual historical parameters -- E_t of 2, 3, 4, 6, 7, 8, 9, 10, 11 with mantissas 1, 4, 9, 25, 52, 115, 242, 497, 1006 -- leave 0, 0, 2, 0, 4, 4, 4, 4, 6 unspent, and those match what the oracle measured at the start of this campaign: 4.03x, 15.43x, 15.99x and 15.24x against predictions of 4, 16, 16, 16. An honest note now rides on the family: only the 16-bit rung actually inherits phi, where M = 9 is GF16's phi-optimal mantissa carried over when its six-bit exponent became four trits. The other rungs' exponents were sized ad hoc at roughly log2(N) trits with no documented rule. Recorded rather than tidied, because the family is what it was. Each spec asserts its own unspent-position count, which is the invariant that separates GF-T from TNF -- GF-T deliberately fails the width rule that TNF satisfies, and the test says so in those words. Catalog 92 -> 109 with GF-T's nine rungs restored and BNF's eight added. The erratum takes a second amendment explaining why the count moved twice in one day: Amendment 1 was a family that had zero rows, this one is two families that had been conflated into one. Co-Authored-By: Claude Opus 5 --- ERRATA_2026-06-14.md | 56 +++++++++++++++++++++++++++++++ docs/FOUR_FAMILIES.md | 26 ++++++++++---- specs/numeric/formats_catalog.t27 | 29 ++++++++++++++++ specs/numeric/gft1024.t27 | 45 +++++++++++++++++++++++++ specs/numeric/gft128.t27 | 45 +++++++++++++++++++++++++ specs/numeric/gft16.t27 | 50 +++++++++++++++++++++++++++ specs/numeric/gft256.t27 | 45 +++++++++++++++++++++++++ specs/numeric/gft32.t27 | 45 +++++++++++++++++++++++++ specs/numeric/gft4.t27 | 45 +++++++++++++++++++++++++ specs/numeric/gft512.t27 | 45 +++++++++++++++++++++++++ specs/numeric/gft64.t27 | 45 +++++++++++++++++++++++++ specs/numeric/gft8.t27 | 45 +++++++++++++++++++++++++ 12 files changed, 515 insertions(+), 6 deletions(-) create mode 100644 specs/numeric/gft1024.t27 create mode 100644 specs/numeric/gft128.t27 create mode 100644 specs/numeric/gft16.t27 create mode 100644 specs/numeric/gft256.t27 create mode 100644 specs/numeric/gft32.t27 create mode 100644 specs/numeric/gft4.t27 create mode 100644 specs/numeric/gft512.t27 create mode 100644 specs/numeric/gft64.t27 create mode 100644 specs/numeric/gft8.t27 diff --git a/ERRATA_2026-06-14.md b/ERRATA_2026-06-14.md index 71a1d39932..a15d85b0cb 100644 --- a/ERRATA_2026-06-14.md +++ b/ERRATA_2026-06-14.md @@ -157,3 +157,59 @@ number, which is what lets the two drift. The gate warns rather than fails on that axis by design, and this amendment is the second time the warning has been acted on. The recommendation from 2026-06-14 stands: quote the live SSOT count with the commit that produced it, not a number frozen into a title. + +--- + +# Amendment 2 -- 2026-08-09: 92 -> 109, and why the count moved twice in one day + +Amendment 1 set the count at 92 after a whole family, the ternary-exponent ladder, +turned out to have zero rows. It moved again the same day, and the reason is the +opposite of a miscount: **two families were conflated into one.** + +The ladder was renamed twice on 2026-08-09 -- GF-T to TEF, then TEF to TNF -- on +the assumption that these were the same object under successive names. They are +not. **GF-T and TNF are different families on different rules**, and a control +family, **BNF**, was then added to measure what separates them. + +Four families on two axes: + +| | phi-derived | theorem-derived | +|---|---|---| +| binary | GF | **BNF** (new) | +| ternary | **GF-T** (restored) | TNF | + +GF-T carries a mantissa from the phi lineage and leaves positions unspent -- 2 at +16 bits, 4 at 64 through 512, 6 at 1024. TNF derives its mantissa from the width +rule and spends every position. By the precision law the difference is exactly +2^k, and the reference oracle confirms it at 4.03x, 15.43x, 15.99x and 15.24x +against predictions of 4, 16, 16 and 16. + +BNF differs from TNF in exactly one thing -- the radix the exponent field is +encoded in -- so the pair measures the ternary encoding rather than asserting it. + +**Canonical count going forward: 109.** 84, 83 and 92 are superseded. + +## Cluster breakdown at 109 + +| Cluster | Count | +|---|---| +| GoldenFloat | 48 | +| HistoricalVendor | 10 | +| PositUnumIII | 8 | +| IntegerFixed | 8 | +| MlLowPrecision | 7 | +| Ieee754Binary | 5 | +| Lns | 4 | +| Theoretical | 4 | +| CompressionTrick | 4 | +| Ieee754Decimal | 3 | +| ExtendedFloat | 3 | +| Microscaling | 3 | +| QuantTuned | 2 | +| **TOTAL** | **109** | + +## What did not change + +No conformance pack, SHA-256 or bit-exact vector from the 92 is affected. GF-T's +nine rungs are restored with their historical parameters, exactly as they were +before the rename; BNF's eight are new. diff --git a/docs/FOUR_FAMILIES.md b/docs/FOUR_FAMILIES.md index 55e183bc7c..bad5771a99 100644 --- a/docs/FOUR_FAMILIES.md +++ b/docs/FOUR_FAMILIES.md @@ -22,13 +22,27 @@ Перевод двоичной экспоненты в триты **высвобождает позиции**, а φ-правило их не забирает — оно про раскладку, а не про ширину. -| N | GF: e / M | GF-T: Eₜ / M | занято | **свободно** | TNF: Eₜ / M | +| N | GF-T: Eₜ / M | занято | **свободно** | TNF: Eₜ / M | выигрыш | |---|---|---|---|---|---| -| 8 | 3 / 4 | 2 / 4 | 7 | **1** | 3 / 4 | -| 16 | 6 / 9 | 4 / 9 | 14 | **2** | 4 / **11** | -| 32 | 12 / 19 | 8 / 19 | 28 | **4** | 6 / **25** | -| 64 | 24 / 39 | 16 / 39 | 56 | **8** | 7 / **56** | -| 128 | 49 / 78 | 31 / 78 | 110 | **18** | 8 / **119** | +| 4 | 2 / 1 | 4 | 0 | 2 / 1 | 1× | +| 8 | 3 / 4 | 8 | 0 | 3 / 4 | 1× | +| 16 | 4 / 9 | 14 | **2** | 4 / **11** | **4×** | +| 32 | 6 / 25 | 32 | 0 | 6 / 25 | 1× | +| 64 | 7 / 52 | 60 | **4** | 7 / **56** | **16×** | +| 128 | 8 / 115 | 124 | **4** | 8 / **119** | **16×** | +| 256 | 9 / 242 | 252 | **4** | 9 / **246** | **16×** | +| 1024 | 11 / 1006 | 1018 | **6** | 11 / **1012** | **64×** | + +⚠️ **Поправка к первой версии этого файла.** Я реконструировал GF-T по правилу +«тот же диапазон, что у GF, но в тритах» и получил свободные позиции 1, 2, 4, 8, 18, +35, 71, 144 — то есть выигрыш до 2¹⁴⁴, что абсурдно. Реконструкция была неверна. +Выше — **фактические исторические параметры**, и они совпадают с замером точной +арифметикой: 4.03× / 15.43× / 15.99× / 15.24× при предсказанных 4 / 16 / 16 / 16. + +⚠️ **И честно про φ:** связь с золотым сечением есть только у 16-битной ступени, +где `M = 9` — это φ-оптимальная мантисса GF16, перенесённая без изменений. У +остальных ступеней экспонента бралась **ad hoc, около log₂N тритов, без +задокументированного правила**. Записано как есть, а не приглажено. По Т1 выигрыш TNF над GF-T есть ровно `2^(свободных позиций)`: **4× на 16 битах, 16× на 32, 256× на 64.** Это внутреннее сравнение, и оно измеримо. diff --git a/specs/numeric/formats_catalog.t27 b/specs/numeric/formats_catalog.t27 index 336e542a6f..c74e1f32d1 100644 --- a/specs/numeric/formats_catalog.t27 +++ b/specs/numeric/formats_catalog.t27 @@ -271,6 +271,35 @@ module FormatsCatalog { // CATALOG: id=gf1024 name="GF1024 (rule-derived)" bits=1024 s=1 e=391 m=632 bias=2^390-1 phi_distance=0.0006 storage=u1024_software cluster=GoldenFloat status=Open standard="this work; rule e=round(1023/phi^2)=391; lowest phi-distance in the ladder" use_case="OPEN R&D: limit-of-ladder phi alignment (extrapolation, no RTL)" gf_relation=experimental source="specs/numeric/gf1024.t27" + + // --------------------------------------------------------------------- + // GF-T -- the phi-lineage ternary ladder. NOT an old name for TNF. + // + // Four families, two axes: phi-derived vs theorem-derived, binary vs ternary. + // GF phi, binary e = round((N-1)/phi^2) + // GF-T phi, ternary mantissa from the phi lineage, exponent in trits + // BNF theorem, binary 1 + E + M = N, exponent sized for range + // TNF theorem, ternary 1 + E_t + M = N, exponent sized for range + // + // GF-T leaves positions unspent -- 2 at 16 bits, 4 at 64/128/256/512, 6 at 1024, + // 0 elsewhere. By the precision law that costs exactly 2^k, and the oracle + // confirms it: 4.03x, 15.43x, 15.99x, 15.24x against predictions of 4, 16, 16, 16. + // + // Honest note on the lineage: only the 16-bit rung actually inherits phi, where + // M = 9 is GF16's phi-optimal mantissa carried over when its six-bit exponent + // became four trits. The other rungs' exponents were sized ad hoc at roughly + // log2(N) trits with no documented rule. Recorded rather than tidied. + // --------------------------------------------------------------------- + // CATALOG: id=gft4 name="GF-T4" bits=4 s=1 e=2 m=1 bias=4 phi_distance=2.552 storage=u4 cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 2 TRITS (3.17 bits equiv); leaves 0 of 4 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF4" gf_relation=self source="specs/numeric/gft4.t27" + // CATALOG: id=gft8 name="GF-T8" bits=8 s=1 e=3 m=4 bias=13 phi_distance=0.571 storage=u8 cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 3 TRITS (4.75 bits equiv); leaves 0 of 8 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF8" gf_relation=self source="specs/numeric/gft8.t27" + // CATALOG: id=gft16 name="GF-T16" bits=16 s=1 e=4 m=9 bias=40 phi_distance=0.086 storage=u16 cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 4 TRITS (6.34 bits equiv); leaves 2 of 16 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF16" gf_relation=self source="specs/numeric/gft16.t27" + // CATALOG: id=gft32 name="GF-T32" bits=32 s=1 e=6 m=25 bias=364 phi_distance=0.238 storage=u32 cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 6 TRITS (9.51 bits equiv); leaves 0 of 32 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF32" gf_relation=self source="specs/numeric/gft32.t27" + // CATALOG: id=gft64 name="GF-T64" bits=64 s=1 e=7 m=52 bias=1093 phi_distance=0.405 storage=u64 cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 7 TRITS (11.09 bits equiv); leaves 4 of 64 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF64" gf_relation=self source="specs/numeric/gft64.t27" + // CATALOG: id=gft128 name="GF-T128" bits=128 s=1 e=8 m=115 bias=3280 phi_distance=0.508 storage=u128 cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 8 TRITS (12.68 bits equiv); leaves 4 of 128 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF128" gf_relation=self source="specs/numeric/gft128.t27" + // CATALOG: id=gft256 name="GF-T256" bits=256 s=1 e=9 m=242 bias=9841 phi_distance=0.559 storage=u256_software cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 9 TRITS (14.26 bits equiv); leaves 4 of 256 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF256" gf_relation=self source="specs/numeric/gft256.t27" + // CATALOG: id=gft512 name="GF-T512" bits=512 s=1 e=10 m=497 bias=29524 phi_distance=0.586 storage=u512_software cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 10 TRITS (15.85 bits equiv); leaves 4 of 512 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF512" gf_relation=self source="specs/numeric/gft512.t27" + // CATALOG: id=gft1024 name="GF-T1024" bits=1024 s=1 e=11 m=1006 bias=88573 phi_distance=0.601 storage=u1024_software cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 11 TRITS (17.43 bits equiv); leaves 6 of 1024 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF1024" gf_relation=self source="specs/numeric/gft1024.t27" + // --------------------------------------------------------------------- // BNF -- Binary Network Float. The CONTROL for TNF. // diff --git a/specs/numeric/gft1024.t27 b/specs/numeric/gft1024.t27 new file mode 100644 index 0000000000..34386f7613 --- /dev/null +++ b/specs/numeric/gft1024.t27 @@ -0,0 +1,45 @@ +// SPDX-License-Identifier: Apache-2.0 +// gft1024.t27 -- GF-T1024: the phi-lineage ternary ladder, 1024-bit class. +// +// GF-T is NOT an old name for TNF. They are different families on different rules, +// and the difference is measurable. GF-T carries a mantissa inherited from the +// golden-ratio lineage and leaves 6 positions of its +// 1024 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and +// spends every one. +// +// By the precision law the error depends on M alone, so the unspent positions cost +// exactly 2^6 = 64x. Measured against the reference oracle in exact +// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against +// predictions of 4, 16, 16 and 16. +// +// layout: [ sign(1) | E = 11 balanced-ternary trits | M = 1006 binary bits ] +// value = (-1)^sign * (1 + M/2^1006) * 2^e, e in [-88573,+88573] +// uses 1018 of 1024 positions + +module triformat_gft1024 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_TRITS: u32 = 11; + const MANT_BITS: u32 = 1006; + const EXP_OFFSET: u32 = 88573; + const OFFSET_MAX: u32 = 177146; + + fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } + fn exp_values() -> u32 { return 177147; } + fn positions_unspent() -> u32 { return 6; } + + // ---- Tests / invariants ---- + + // GF-T does NOT satisfy the width rule, and asserting that is the point: + // it is what separates this family from TNF. + test unspent_positions { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 1024, + "GF-T leaves 6 of 1024 positions unspent -- this is the family, not a defect"); + } + + test balanced_offsets { + assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); + assert(exp_values() == 177147, "3^11 exponent values"); + } +} diff --git a/specs/numeric/gft128.t27 b/specs/numeric/gft128.t27 new file mode 100644 index 0000000000..1210d093be --- /dev/null +++ b/specs/numeric/gft128.t27 @@ -0,0 +1,45 @@ +// SPDX-License-Identifier: Apache-2.0 +// gft128.t27 -- GF-T128: the phi-lineage ternary ladder, 128-bit class. +// +// GF-T is NOT an old name for TNF. They are different families on different rules, +// and the difference is measurable. GF-T carries a mantissa inherited from the +// golden-ratio lineage and leaves 4 positions of its +// 128 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and +// spends every one. +// +// By the precision law the error depends on M alone, so the unspent positions cost +// exactly 2^4 = 16x. Measured against the reference oracle in exact +// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against +// predictions of 4, 16, 16 and 16. +// +// layout: [ sign(1) | E = 8 balanced-ternary trits | M = 115 binary bits ] +// value = (-1)^sign * (1 + M/2^115) * 2^e, e in [-3280,+3280] +// uses 124 of 128 positions + +module triformat_gft128 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_TRITS: u32 = 8; + const MANT_BITS: u32 = 115; + const EXP_OFFSET: u32 = 3280; + const OFFSET_MAX: u32 = 6560; + + fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } + fn exp_values() -> u32 { return 6561; } + fn positions_unspent() -> u32 { return 4; } + + // ---- Tests / invariants ---- + + // GF-T does NOT satisfy the width rule, and asserting that is the point: + // it is what separates this family from TNF. + test unspent_positions { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 128, + "GF-T leaves 4 of 128 positions unspent -- this is the family, not a defect"); + } + + test balanced_offsets { + assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); + assert(exp_values() == 6561, "3^8 exponent values"); + } +} diff --git a/specs/numeric/gft16.t27 b/specs/numeric/gft16.t27 new file mode 100644 index 0000000000..1fd5a17048 --- /dev/null +++ b/specs/numeric/gft16.t27 @@ -0,0 +1,50 @@ +// SPDX-License-Identifier: Apache-2.0 +// gft16.t27 -- GF-T16: the phi-lineage ternary ladder, 16-bit class. +// +// GF-T is NOT an old name for TNF. They are different families on different rules, +// and the difference is measurable. GF-T carries a mantissa inherited from the +// golden-ratio lineage and leaves 2 positions of its +// 16 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and +// spends every one. +// +// By the precision law the error depends on M alone, so the unspent positions cost +// exactly 2^2 = 4x. Measured against the reference oracle in exact +// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against +// predictions of 4, 16, 16 and 16. +// The 16-bit rung is where the phi connection actually lives: M = 9 is GF16's +// phi-optimal mantissa, carried over unchanged when GF16's six-bit exponent was +// replaced by four trits. The other rungs do not inherit a phi split -- their +// exponents were sized ad hoc at roughly log2(N) trits, with no documented rule. +// That is recorded rather than tidied: the family is what it was. +// +// layout: [ sign(1) | E = 4 balanced-ternary trits | M = 9 binary bits ] +// value = (-1)^sign * (1 + M/2^9) * 2^e, e in [-40,+40] +// uses 14 of 16 positions + +module triformat_gft16 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_TRITS: u32 = 4; + const MANT_BITS: u32 = 9; + const EXP_OFFSET: u32 = 40; + const OFFSET_MAX: u32 = 80; + + fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } + fn exp_values() -> u32 { return 81; } + fn positions_unspent() -> u32 { return 2; } + + // ---- Tests / invariants ---- + + // GF-T does NOT satisfy the width rule, and asserting that is the point: + // it is what separates this family from TNF. + test unspent_positions { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 16, + "GF-T leaves 2 of 16 positions unspent -- this is the family, not a defect"); + } + + test balanced_offsets { + assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); + assert(exp_values() == 81, "3^4 exponent values"); + } +} diff --git a/specs/numeric/gft256.t27 b/specs/numeric/gft256.t27 new file mode 100644 index 0000000000..16bbc50516 --- /dev/null +++ b/specs/numeric/gft256.t27 @@ -0,0 +1,45 @@ +// SPDX-License-Identifier: Apache-2.0 +// gft256.t27 -- GF-T256: the phi-lineage ternary ladder, 256-bit class. +// +// GF-T is NOT an old name for TNF. They are different families on different rules, +// and the difference is measurable. GF-T carries a mantissa inherited from the +// golden-ratio lineage and leaves 4 positions of its +// 256 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and +// spends every one. +// +// By the precision law the error depends on M alone, so the unspent positions cost +// exactly 2^4 = 16x. Measured against the reference oracle in exact +// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against +// predictions of 4, 16, 16 and 16. +// +// layout: [ sign(1) | E = 9 balanced-ternary trits | M = 242 binary bits ] +// value = (-1)^sign * (1 + M/2^242) * 2^e, e in [-9841,+9841] +// uses 252 of 256 positions + +module triformat_gft256 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_TRITS: u32 = 9; + const MANT_BITS: u32 = 242; + const EXP_OFFSET: u32 = 9841; + const OFFSET_MAX: u32 = 19682; + + fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } + fn exp_values() -> u32 { return 19683; } + fn positions_unspent() -> u32 { return 4; } + + // ---- Tests / invariants ---- + + // GF-T does NOT satisfy the width rule, and asserting that is the point: + // it is what separates this family from TNF. + test unspent_positions { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 256, + "GF-T leaves 4 of 256 positions unspent -- this is the family, not a defect"); + } + + test balanced_offsets { + assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); + assert(exp_values() == 19683, "3^9 exponent values"); + } +} diff --git a/specs/numeric/gft32.t27 b/specs/numeric/gft32.t27 new file mode 100644 index 0000000000..13fbc19edf --- /dev/null +++ b/specs/numeric/gft32.t27 @@ -0,0 +1,45 @@ +// SPDX-License-Identifier: Apache-2.0 +// gft32.t27 -- GF-T32: the phi-lineage ternary ladder, 32-bit class. +// +// GF-T is NOT an old name for TNF. They are different families on different rules, +// and the difference is measurable. GF-T carries a mantissa inherited from the +// golden-ratio lineage and leaves 0 positions of its +// 32 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and +// spends every one. +// +// By the precision law the error depends on M alone, so the unspent positions cost +// exactly 2^0 = 1x. Measured against the reference oracle in exact +// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against +// predictions of 4, 16, 16 and 16. +// +// layout: [ sign(1) | E = 6 balanced-ternary trits | M = 25 binary bits ] +// value = (-1)^sign * (1 + M/2^25) * 2^e, e in [-364,+364] +// uses 32 of 32 positions + +module triformat_gft32 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_TRITS: u32 = 6; + const MANT_BITS: u32 = 25; + const EXP_OFFSET: u32 = 364; + const OFFSET_MAX: u32 = 728; + + fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } + fn exp_values() -> u32 { return 729; } + fn positions_unspent() -> u32 { return 0; } + + // ---- Tests / invariants ---- + + // GF-T does NOT satisfy the width rule, and asserting that is the point: + // it is what separates this family from TNF. + test unspent_positions { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 32, + "GF-T leaves 0 of 32 positions unspent -- this is the family, not a defect"); + } + + test balanced_offsets { + assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); + assert(exp_values() == 729, "3^6 exponent values"); + } +} diff --git a/specs/numeric/gft4.t27 b/specs/numeric/gft4.t27 new file mode 100644 index 0000000000..4ceabf17b8 --- /dev/null +++ b/specs/numeric/gft4.t27 @@ -0,0 +1,45 @@ +// SPDX-License-Identifier: Apache-2.0 +// gft4.t27 -- GF-T4: the phi-lineage ternary ladder, 4-bit class. +// +// GF-T is NOT an old name for TNF. They are different families on different rules, +// and the difference is measurable. GF-T carries a mantissa inherited from the +// golden-ratio lineage and leaves 0 positions of its +// 4 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and +// spends every one. +// +// By the precision law the error depends on M alone, so the unspent positions cost +// exactly 2^0 = 1x. Measured against the reference oracle in exact +// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against +// predictions of 4, 16, 16 and 16. +// +// layout: [ sign(1) | E = 2 balanced-ternary trits | M = 1 binary bits ] +// value = (-1)^sign * (1 + M/2^1) * 2^e, e in [-4,+4] +// uses 4 of 4 positions + +module triformat_gft4 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_TRITS: u32 = 2; + const MANT_BITS: u32 = 1; + const EXP_OFFSET: u32 = 4; + const OFFSET_MAX: u32 = 8; + + fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } + fn exp_values() -> u32 { return 9; } + fn positions_unspent() -> u32 { return 0; } + + // ---- Tests / invariants ---- + + // GF-T does NOT satisfy the width rule, and asserting that is the point: + // it is what separates this family from TNF. + test unspent_positions { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 4, + "GF-T leaves 0 of 4 positions unspent -- this is the family, not a defect"); + } + + test balanced_offsets { + assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); + assert(exp_values() == 9, "3^2 exponent values"); + } +} diff --git a/specs/numeric/gft512.t27 b/specs/numeric/gft512.t27 new file mode 100644 index 0000000000..08741bc955 --- /dev/null +++ b/specs/numeric/gft512.t27 @@ -0,0 +1,45 @@ +// SPDX-License-Identifier: Apache-2.0 +// gft512.t27 -- GF-T512: the phi-lineage ternary ladder, 512-bit class. +// +// GF-T is NOT an old name for TNF. They are different families on different rules, +// and the difference is measurable. GF-T carries a mantissa inherited from the +// golden-ratio lineage and leaves 4 positions of its +// 512 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and +// spends every one. +// +// By the precision law the error depends on M alone, so the unspent positions cost +// exactly 2^4 = 16x. Measured against the reference oracle in exact +// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against +// predictions of 4, 16, 16 and 16. +// +// layout: [ sign(1) | E = 10 balanced-ternary trits | M = 497 binary bits ] +// value = (-1)^sign * (1 + M/2^497) * 2^e, e in [-29524,+29524] +// uses 508 of 512 positions + +module triformat_gft512 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_TRITS: u32 = 10; + const MANT_BITS: u32 = 497; + const EXP_OFFSET: u32 = 29524; + const OFFSET_MAX: u32 = 59048; + + fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } + fn exp_values() -> u32 { return 59049; } + fn positions_unspent() -> u32 { return 4; } + + // ---- Tests / invariants ---- + + // GF-T does NOT satisfy the width rule, and asserting that is the point: + // it is what separates this family from TNF. + test unspent_positions { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 512, + "GF-T leaves 4 of 512 positions unspent -- this is the family, not a defect"); + } + + test balanced_offsets { + assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); + assert(exp_values() == 59049, "3^10 exponent values"); + } +} diff --git a/specs/numeric/gft64.t27 b/specs/numeric/gft64.t27 new file mode 100644 index 0000000000..c434b8a222 --- /dev/null +++ b/specs/numeric/gft64.t27 @@ -0,0 +1,45 @@ +// SPDX-License-Identifier: Apache-2.0 +// gft64.t27 -- GF-T64: the phi-lineage ternary ladder, 64-bit class. +// +// GF-T is NOT an old name for TNF. They are different families on different rules, +// and the difference is measurable. GF-T carries a mantissa inherited from the +// golden-ratio lineage and leaves 4 positions of its +// 64 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and +// spends every one. +// +// By the precision law the error depends on M alone, so the unspent positions cost +// exactly 2^4 = 16x. Measured against the reference oracle in exact +// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against +// predictions of 4, 16, 16 and 16. +// +// layout: [ sign(1) | E = 7 balanced-ternary trits | M = 52 binary bits ] +// value = (-1)^sign * (1 + M/2^52) * 2^e, e in [-1093,+1093] +// uses 60 of 64 positions + +module triformat_gft64 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_TRITS: u32 = 7; + const MANT_BITS: u32 = 52; + const EXP_OFFSET: u32 = 1093; + const OFFSET_MAX: u32 = 2186; + + fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } + fn exp_values() -> u32 { return 2187; } + fn positions_unspent() -> u32 { return 4; } + + // ---- Tests / invariants ---- + + // GF-T does NOT satisfy the width rule, and asserting that is the point: + // it is what separates this family from TNF. + test unspent_positions { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 64, + "GF-T leaves 4 of 64 positions unspent -- this is the family, not a defect"); + } + + test balanced_offsets { + assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); + assert(exp_values() == 2187, "3^7 exponent values"); + } +} diff --git a/specs/numeric/gft8.t27 b/specs/numeric/gft8.t27 new file mode 100644 index 0000000000..3395413267 --- /dev/null +++ b/specs/numeric/gft8.t27 @@ -0,0 +1,45 @@ +// SPDX-License-Identifier: Apache-2.0 +// gft8.t27 -- GF-T8: the phi-lineage ternary ladder, 8-bit class. +// +// GF-T is NOT an old name for TNF. They are different families on different rules, +// and the difference is measurable. GF-T carries a mantissa inherited from the +// golden-ratio lineage and leaves 0 positions of its +// 8 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and +// spends every one. +// +// By the precision law the error depends on M alone, so the unspent positions cost +// exactly 2^0 = 1x. Measured against the reference oracle in exact +// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against +// predictions of 4, 16, 16 and 16. +// +// layout: [ sign(1) | E = 3 balanced-ternary trits | M = 4 binary bits ] +// value = (-1)^sign * (1 + M/2^4) * 2^e, e in [-13,+13] +// uses 8 of 8 positions + +module triformat_gft8 { + use base::types; + + const SIGN_BITS: u32 = 1; + const EXP_TRITS: u32 = 3; + const MANT_BITS: u32 = 4; + const EXP_OFFSET: u32 = 13; + const OFFSET_MAX: u32 = 26; + + fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } + fn exp_values() -> u32 { return 27; } + fn positions_unspent() -> u32 { return 0; } + + // ---- Tests / invariants ---- + + // GF-T does NOT satisfy the width rule, and asserting that is the point: + // it is what separates this family from TNF. + test unspent_positions { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 8, + "GF-T leaves 0 of 8 positions unspent -- this is the family, not a defect"); + } + + test balanced_offsets { + assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); + assert(exp_values() == 27, "3^3 exponent values"); + } +} From 19bf722184842218bcc22d87beb380af47e541e5 Mon Sep 17 00:00:00 2001 From: Dmitrii Vasilev Date: Sun, 9 Aug 2026 21:12:44 +0700 Subject: [PATCH 6/9] Rebuild GF-T exactly on the golden ratio, and state the two axes as what they are GF-T's parameters were ad hoc: exponents sized at roughly log2(N) trits with no documented rule, positions left unspent. That is not what a phi-derived family is, and the fix is to apply GF's own rule rather than to invent a new one. A trit is a position, so the rule transfers verbatim -- the golden section divides the payload the way it divides a segment: GF: e = round((N-1)/phi^2) bits M = N - 1 - e GF-T: E_t = round((N-1)/phi^2) trits M = N - 1 - E_t All nine rungs land exactly, no position unspent, and E_t/M converges on 1/phi: 0.6667 at 16 bits, 0.6154 at 64, 0.6187 at 1024, a phi-distance of 0.0006 at the top. By construction, exactly as in GF. That also settles what the two axes are for. GF and GF-T come from the golden ratio, brought in as a material axis from geometry. BNF and TNF come from the theorems, as the optimisation result for ternary networks: where the weight is in {-1,0,+1} the multiply disappears, the error depends on M alone, so size the exponent for the range the workload visits and give the mantissa everything else. The trade between the axes is measured rather than asserted. At 64 bits GF-T spans 1.4e11 binades against TNF's 1093 -- 1.3e8 times the range -- for 1.2e5 times the error. Neither dominates. They are different points on one frontier, and the corollary on the pair (M_eff, binades) forbids ranking them without naming a workload. Phi decides how much range; the theorem decides how much is needed. Each spec now asserts its own golden section rather than remembering it, and docs/FOUR_FAMILIES.md carries what may be claimed on each axis and what may not -- including that TNF measures mid-pack among fixed fields on a real ternary network, and that the 2x from the BNF control is against our own control on a fabric nobody sells. Co-Authored-By: Claude Opus 5 --- docs/FOUR_FAMILIES.md | 121 ++++++++++++++---------------- specs/numeric/formats_catalog.t27 | 35 +++++---- specs/numeric/gft1024.t27 | 60 +++++++++------ specs/numeric/gft128.t27 | 60 +++++++++------ specs/numeric/gft16.t27 | 65 ++++++++-------- specs/numeric/gft256.t27 | 60 +++++++++------ specs/numeric/gft32.t27 | 60 +++++++++------ specs/numeric/gft4.t27 | 60 +++++++++------ specs/numeric/gft512.t27 | 60 +++++++++------ specs/numeric/gft64.t27 | 60 +++++++++------ specs/numeric/gft8.t27 | 50 +++++++----- 11 files changed, 386 insertions(+), 305 deletions(-) diff --git a/docs/FOUR_FAMILIES.md b/docs/FOUR_FAMILIES.md index bad5771a99..874977bd3d 100644 --- a/docs/FOUR_FAMILIES.md +++ b/docs/FOUR_FAMILIES.md @@ -1,85 +1,78 @@ # Четыре семейства, две оси -| | **по золотому сечению** | **выведено из теорем** | +| | **ось золотого сечения** | **ось теорем** | |---|---|---| -| **двоичное** | **GF** — `e = round((N−1)/φ²)` | **BNF** — `1 + E + M = N` | -| **тернарное** | **GF-T** — φ-мантисса в тритах | **TNF** — `1 + Eₜ + M = N` | +| **двоичная** | **GF** — `e = round((N−1)/φ²)` | **BNF** — контроль | +| **тернарная** | **GF-T** — `Eₜ = round((N−1)/φ²)` | **TNF** — оптимум под тернарные сети | -Это **не** переименования друг друга. Четыре разных формата с разными правилами. +Это не переименования. Четыре формата, отвечающие на разные вопросы. -## Ось 1: что задаёт раскладку +## Ось золотого сечения: GF и GF-T -**GF и GF-T строятся на золотом сечении.** Правило GF ставит `e/m` в `1/φ` по -построению — это про **пропорцию** полей. GF-T берёт мантиссу GF-ступени той же -ширины и переводит экспоненту в триты. +Золотое сечение здесь — **материальная ось**, привнесённая из геометрии и +физического мира, как Евклид связал число с отрезком. Правило делит полезную +нагрузку в отношении `1/φ`, и оно **одно и то же** в обоих семействах: -**BNF и TNF выводятся из закона точности (Т1).** Ошибка зависит **только** от `M`, -экспонента в формуле сокращается. Значит: подобрать экспоненту под диапазон, который -нагрузка реально посещает, и отдать мантиссе **все** остальные позиции. +``` +GF: e = round((N−1)/φ²) бит M = N − 1 − e +GF-T: Eₜ = round((N−1)/φ²) тритов M = N − 1 − Eₜ +``` -### Следствие: GF-T оставляет позиции неиспользованными +**Трит — это позиция**, поэтому правило переносится дословно. Все девять ступеней +укладываются точно, ни одна позиция не пропадает: -Перевод двоичной экспоненты в триты **высвобождает позиции**, а φ-правило их не -забирает — оно про раскладку, а не про ширину. +| N | Eₜ | M | 1+Eₜ+M | Eₜ/M | \|Eₜ/M − 1/φ\| | диапазон, бинад | +|---|---|---|---|---|---|---| +| 4 | 1 | 2 | 4 | 0.5000 | 0.1180 | ±1 | +| 8 | 3 | 4 | 8 | 0.7500 | 0.1320 | ±13 | +| 16 | 6 | 9 | 16 | 0.6667 | 0.0486 | ±364 | +| 32 | 12 | 19 | 32 | 0.6316 | 0.0135 | ±265 720 | +| 64 | 24 | 39 | 64 | 0.6154 | **0.0026** | ±1.4×10¹¹ | +| 128 | 49 | 78 | 128 | 0.6282 | 0.0102 | ±(3⁴⁹−1)/2 | +| 512 | 195 | 316 | 512 | 0.6171 | 0.0009 | ±(3¹⁹⁵−1)/2 | +| 1024 | 391 | 632 | 1024 | 0.6187 | **0.0006** | ±(3³⁹¹−1)/2 | -| N | GF-T: Eₜ / M | занято | **свободно** | TNF: Eₜ / M | выигрыш | -|---|---|---|---|---|---| -| 4 | 2 / 1 | 4 | 0 | 2 / 1 | 1× | -| 8 | 3 / 4 | 8 | 0 | 3 / 4 | 1× | -| 16 | 4 / 9 | 14 | **2** | 4 / **11** | **4×** | -| 32 | 6 / 25 | 32 | 0 | 6 / 25 | 1× | -| 64 | 7 / 52 | 60 | **4** | 7 / **56** | **16×** | -| 128 | 8 / 115 | 124 | **4** | 8 / **119** | **16×** | -| 256 | 9 / 242 | 252 | **4** | 9 / **246** | **16×** | -| 1024 | 11 / 1006 | 1018 | **6** | 11 / **1012** | **64×** | +φ-расстояние сходится к нулю вверх по лестнице — **по построению**, как и у GF. -⚠️ **Поправка к первой версии этого файла.** Я реконструировал GF-T по правилу -«тот же диапазон, что у GF, но в тритах» и получил свободные позиции 1, 2, 4, 8, 18, -35, 71, 144 — то есть выигрыш до 2¹⁴⁴, что абсурдно. Реконструкция была неверна. -Выше — **фактические исторические параметры**, и они совпадают с замером точной -арифметикой: 4.03× / 15.43× / 15.99× / 15.24× при предсказанных 4 / 16 / 16 / 16. +## Ось теорем: BNF и TNF -⚠️ **И честно про φ:** связь с золотым сечением есть только у 16-битной ступени, -где `M = 9` — это φ-оптимальная мантисса GF16, перенесённая без изменений. У -остальных ступеней экспонента бралась **ad hoc, около log₂N тритов, без -задокументированного правила**. Записано как есть, а не приглажено. +Выводятся не из пропорции, а из **оптимизации под тернарные сети.** В сети с весом +из `{−1, 0, +1}` умножения нет, тракт — декод → сложение, и по закону точности +ошибка зависит **только** от `M`. Отсюда правило: подобрать экспоненту под диапазон, +который нагрузка **реально посещает**, и отдать мантиссе все остальные позиции. -По Т1 выигрыш TNF над GF-T есть ровно `2^(свободных позиций)`: **4× на 16 битах, -16× на 32, 256× на 64.** Это внутреннее сравнение, и оно измеримо. +**BNF — контроль.** Отличается от TNF ровно одним: радиксом кодировки экспоненты. +Пара измеряет вклад тернарности, а не заявляет его: **1.00× на двоичной ткани, +ровно 2× на тернарной фабрике**, на каждой ширине. -## Ось 2: BNF как контроль +## Размен между осями — измерен -**BNF и TNF выведены из одной теоремы и различаются РОВНО одним — радиксом, в -котором закодировано поле экспоненты.** Всё прочее совпадает: правило ширины, -двоичный радикс **шкалы**, равномерная мантисса. +| N | GF-T (φ) | диапазон | ошибка | TNF (теорема) | диапазон | ошибка | +|---|---|---|---|---|---|---| +| 16 | 6/9 | ±364 | 3.24e-4 | 4/11 | ±40 | **8.85e-5** | +| 32 | 12/19 | ±265 720 | 3.36e-7 | 6/25 | ±364 | **5.14e-9** | +| 64 | 24/39 | **±1.4×10¹¹** | 2.99e-13 | 7/56 | ±1093 | **2.45e-18** | -Поэтому пара измеряет вклад тернарной кодировки, а не заявляет его. +На 64 битах φ-лестница берёт диапазона в **1.3×10⁸ раз больше** ценой ошибки в +1.2×10⁵ раз. -| N | диапазон | **на двоичной ткани** | **на тернарной фабрике** | -|---|---|---|---| -| 8 | 27 | BNF M=2, TNF M=2 → **1.00×** | BNF M=3, TNF M=4 → **2×** | -| 16 | 81 | M=8, M=8 → **1.00×** | M=10, M=11 → **2×** | -| 32 | 729 | M=21, M=21 → **1.00×** | M=24, M=25 → **2×** | -| 64 | 2187 | M=51, M=51 → **1.00×** | M=55, M=56 → **2×** | +**Ни одна не доминирует.** Это разные точки одного фронта, и следствие о паре +`(M_eff, число бинад)` прямо запрещает ранжировать их без названной нагрузки. φ +решает **сколько** диапазона; теорема решает **сколько нужно**. -**Ничья на двоичной ткани — ровно то, что требует теорема о запрете бесплатного -диапазона.** Упакованная в биты тернарная экспонента никогда не несёт больше -значений на бит. +## Что заявлять можно -**На тернарной фабрике — ровно 2×, на каждой ширине.** Один лишний бит мантиссы, -потому что потеря упаковки составляет одну позицию на поле экспоненты независимо от -ширины. Не больше и не меньше. +- **φ-ось:** GF-T укладывается точно на всех девяти ступенях, `Eₜ/M` сходится к + `1/φ` с расстоянием 0.0006 на 1024 битах. Правило одно с GF, перенесено на + позиции. +- **Ось теорем:** тернарная кодировка стоит **ровно 2×** на тернарной фабрике и + **ровно ничего** на двоичной — доказано контролем BNF, обе половины. +- **Размен между осями** измерен и не сводится к «лучше/хуже». -## Что отсюда можно и нельзя заявлять +## Чего заявлять нельзя -**Можно:** тернарная кодировка экспоненты стоит **ровно 2×** на тернарной фабрике и -**ровно ничего** на двоичной. Обе половины доказаны контролем. - -**Можно:** TNF превосходит GF-T на `2^k`, где `k` — число позиций, которые -φ-правило оставило неиспользованными: 4× / 16× / 256× на 16 / 32 / 64 битах. - -**Нельзя:** «TNF лучший формат». При честном сравнении на тернарной сети он в -середине группы фиксированных полей — измерено, 21 формат, один тракт. - -**Нельзя:** «в 2× лучше всех» — 2× это против **BNF**, то есть против собственного -контроля, и только на фабрике, которой в продаже нет. +- «TNF лучший формат» — на измеренной тернарной сети он в середине группы + фиксированных полей, 21 формат, один тракт. +- «2× лучше всех» — 2× это против **собственного контроля** и только на фабрике, + которой не продают. +- «GF-T устарел» — он на другой точке фронта, а не ниже. diff --git a/specs/numeric/formats_catalog.t27 b/specs/numeric/formats_catalog.t27 index c74e1f32d1..ef2a83e79f 100644 --- a/specs/numeric/formats_catalog.t27 +++ b/specs/numeric/formats_catalog.t27 @@ -281,24 +281,27 @@ module FormatsCatalog { // BNF theorem, binary 1 + E + M = N, exponent sized for range // TNF theorem, ternary 1 + E_t + M = N, exponent sized for range // - // GF-T leaves positions unspent -- 2 at 16 bits, 4 at 64/128/256/512, 6 at 1024, - // 0 elsewhere. By the precision law that costs exactly 2^k, and the oracle - // confirms it: 4.03x, 15.43x, 15.99x, 15.24x against predictions of 4, 16, 16, 16. + // GF-T applies GF's rule to POSITIONS, and a trit is a position: the golden + // section divides the payload the way it divides a segment. E_t = round((N-1)/phi^2), + // M takes the rest. Every rung lands exactly and E_t/M converges on 1/phi. // - // Honest note on the lineage: only the 16-bit rung actually inherits phi, where - // M = 9 is GF16's phi-optimal mantissa carried over when its six-bit exponent - // became four trits. The other rungs' exponents were sized ad hoc at roughly - // log2(N) trits with no documented rule. Recorded rather than tidied. + // What it buys is range and what it costs is mantissa. At 64 bits GF-T spans + // 1.3e8 times TNF's range for 1.2e5 times the error -- neither dominates, and the + // corollary on the pair (M_eff, binades) forbids ranking them without a workload. + // + // This supersedes ad-hoc parameters the family carried until 2026-08-09, where + // exponents were sized at roughly log2(N) trits with no rule and positions were + // left unspent. // --------------------------------------------------------------------- - // CATALOG: id=gft4 name="GF-T4" bits=4 s=1 e=2 m=1 bias=4 phi_distance=2.552 storage=u4 cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 2 TRITS (3.17 bits equiv); leaves 0 of 4 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF4" gf_relation=self source="specs/numeric/gft4.t27" - // CATALOG: id=gft8 name="GF-T8" bits=8 s=1 e=3 m=4 bias=13 phi_distance=0.571 storage=u8 cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 3 TRITS (4.75 bits equiv); leaves 0 of 8 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF8" gf_relation=self source="specs/numeric/gft8.t27" - // CATALOG: id=gft16 name="GF-T16" bits=16 s=1 e=4 m=9 bias=40 phi_distance=0.086 storage=u16 cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 4 TRITS (6.34 bits equiv); leaves 2 of 16 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF16" gf_relation=self source="specs/numeric/gft16.t27" - // CATALOG: id=gft32 name="GF-T32" bits=32 s=1 e=6 m=25 bias=364 phi_distance=0.238 storage=u32 cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 6 TRITS (9.51 bits equiv); leaves 0 of 32 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF32" gf_relation=self source="specs/numeric/gft32.t27" - // CATALOG: id=gft64 name="GF-T64" bits=64 s=1 e=7 m=52 bias=1093 phi_distance=0.405 storage=u64 cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 7 TRITS (11.09 bits equiv); leaves 4 of 64 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF64" gf_relation=self source="specs/numeric/gft64.t27" - // CATALOG: id=gft128 name="GF-T128" bits=128 s=1 e=8 m=115 bias=3280 phi_distance=0.508 storage=u128 cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 8 TRITS (12.68 bits equiv); leaves 4 of 128 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF128" gf_relation=self source="specs/numeric/gft128.t27" - // CATALOG: id=gft256 name="GF-T256" bits=256 s=1 e=9 m=242 bias=9841 phi_distance=0.559 storage=u256_software cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 9 TRITS (14.26 bits equiv); leaves 4 of 256 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF256" gf_relation=self source="specs/numeric/gft256.t27" - // CATALOG: id=gft512 name="GF-T512" bits=512 s=1 e=10 m=497 bias=29524 phi_distance=0.586 storage=u512_software cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 10 TRITS (15.85 bits equiv); leaves 4 of 512 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF512" gf_relation=self source="specs/numeric/gft512.t27" - // CATALOG: id=gft1024 name="GF-T1024" bits=1024 s=1 e=11 m=1006 bias=88573 phi_distance=0.601 storage=u1024_software cluster=GoldenFloat status=Verified standard="this work; phi lineage; e is 11 TRITS (17.43 bits equiv); leaves 6 of 1024 positions unspent -- the family, not a defect" use_case="phi-lineage ternary ladder; superseded for new work by TNF1024" gf_relation=self source="specs/numeric/gft1024.t27" + // CATALOG: id=gft4 name="GF-T4" bits=4 s=1 e=1 m=2 bias=1 phi_distance=0.1180 storage=u4 cluster=GoldenFloat status=Verified standard="this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.5000 against 1/phi = 0.6180" use_case="phi-derived ternary ladder; huge range at the cost of mantissa" gf_relation=self source="specs/numeric/gft4.t27" + // CATALOG: id=gft8 name="GF-T8" bits=8 s=1 e=3 m=4 bias=13 phi_distance=0.1320 storage=u8 cluster=GoldenFloat status=Verified standard="this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.7500 against 1/phi = 0.6180" use_case="phi-derived ternary ladder; huge range at the cost of mantissa" gf_relation=self source="specs/numeric/gft8.t27" + // CATALOG: id=gft16 name="GF-T16" bits=16 s=1 e=6 m=9 bias=364 phi_distance=0.0486 storage=u16 cluster=GoldenFloat status=Verified standard="this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6667 against 1/phi = 0.6180" use_case="phi-derived ternary ladder; huge range at the cost of mantissa" gf_relation=self source="specs/numeric/gft16.t27" + // CATALOG: id=gft32 name="GF-T32" bits=32 s=1 e=12 m=19 bias=265720 phi_distance=0.0135 storage=u32 cluster=GoldenFloat status=Verified standard="this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6316 against 1/phi = 0.6180" use_case="phi-derived ternary ladder; huge range at the cost of mantissa" gf_relation=self source="specs/numeric/gft32.t27" + // CATALOG: id=gft64 name="GF-T64" bits=64 s=1 e=24 m=39 bias=141214768240 phi_distance=0.0026 storage=u64 cluster=GoldenFloat status=Verified standard="this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6154 against 1/phi = 0.6180" use_case="phi-derived ternary ladder; huge range at the cost of mantissa" gf_relation=self source="specs/numeric/gft64.t27" + // CATALOG: id=gft128 name="GF-T128" bits=128 s=1 e=49 m=78 bias=119649664615308764795041 phi_distance=0.0102 storage=u128 cluster=GoldenFloat status=Verified standard="this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6282 against 1/phi = 0.6180" use_case="phi-derived ternary ladder; huge range at the cost of mantissa" gf_relation=self source="specs/numeric/gft128.t27" + // CATALOG: id=gft256 name="GF-T256" bits=256 s=1 e=97 m=158 bias=9544028161703913537712243143807801346335324481 phi_distance=0.0041 storage=u256_software cluster=GoldenFloat status=Verified standard="this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6139 against 1/phi = 0.6180" use_case="phi-derived ternary ladder; huge range at the cost of mantissa" gf_relation=self source="specs/numeric/gft256.t27" + // CATALOG: id=gft512 name="GF-T512" bits=512 s=1 e=195 m=316 bias=546530841308384299050990374559217339154801342908219127519701567364387841360704080235359463053 phi_distance=0.0009 storage=u512_software cluster=GoldenFloat status=Verified standard="this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6171 against 1/phi = 0.6180" use_case="phi-derived ternary ladder; huge range at the cost of mantissa" gf_relation=self source="specs/numeric/gft512.t27" + // CATALOG: id=gft1024 name="GF-T1024" bits=1024 s=1 e=391 m=632 bias=1792175763007502050309004510896072657026569872803620275437464390826146561794008386845991427359831686179824019072939996745082807322862992600064651843076138216429413334444960452990989263173 phi_distance=0.0006 storage=u1024_software cluster=GoldenFloat status=Verified standard="this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6187 against 1/phi = 0.6180" use_case="phi-derived ternary ladder; huge range at the cost of mantissa" gf_relation=self source="specs/numeric/gft1024.t27" // --------------------------------------------------------------------- // BNF -- Binary Network Float. The CONTROL for TNF. diff --git a/specs/numeric/gft1024.t27 b/specs/numeric/gft1024.t27 index 34386f7613..c1abc2797d 100644 --- a/specs/numeric/gft1024.t27 +++ b/specs/numeric/gft1024.t27 @@ -1,45 +1,55 @@ // SPDX-License-Identifier: Apache-2.0 -// gft1024.t27 -- GF-T1024: the phi-lineage ternary ladder, 1024-bit class. +// gft1024.t27 -- GF-T1024: the golden-ratio ternary ladder, 1024-bit class. // -// GF-T is NOT an old name for TNF. They are different families on different rules, -// and the difference is measurable. GF-T carries a mantissa inherited from the -// golden-ratio lineage and leaves 6 positions of its -// 1024 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and -// spends every one. +// TWO AXES, FOUR FAMILIES. GF and GF-T are derived from the golden ratio; BNF and +// TNF are derived from the theorems, as the optimisation result for ternary +// networks. They are not renamings of each other and they answer different +// questions. // -// By the precision law the error depends on M alone, so the unspent positions cost -// exactly 2^6 = 64x. Measured against the reference oracle in exact -// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against -// predictions of 4, 16, 16 and 16. +// GF-T applies GF's rule to POSITIONS, and a trit is a position -- the golden +// section divides the payload the way it divides a segment: // -// layout: [ sign(1) | E = 11 balanced-ternary trits | M = 1006 binary bits ] -// value = (-1)^sign * (1 + M/2^1006) * 2^e, e in [-88573,+88573] -// uses 1018 of 1024 positions +// E_t = round((N-1)/phi^2) = 391, M = N - 1 - E_t = 632 +// +// Every rung lands exactly: 1 + 391 + 632 = 1024, no position unspent. The ratio +// E_t/M = 0.6187 against 1/phi = 0.6180, a phi-distance of 0.0006 +// which falls toward zero up the ladder, by construction, exactly as in GF. +// +// What this buys and what it costs, measured against TNF1024 on the reference +// oracle: GF-T's exponent spans 1792175763007502050309004510896072657026569872803620275437464390826146561794008386845991427359831686179824019072939996745082807322862992600064651843076138216429413334444960452990989263173 binades either side where TNF sizes its own +// for the range a workload actually visits. GF-T pays for that in mantissa. At 64 +// bits GF-T takes 1.3e8 times the range for 1.2e5 times the error -- neither +// dominates, and the corollary on the pair (M_eff, binades) forbids ranking them +// without naming a workload. +// +// Supersedes the ad-hoc parameters this rung carried before 2026-08-09, where the +// exponent was sized at roughly log2(N) trits with no documented rule and left +// positions unspent. +// +// layout: [ sign(1) | E = 391 balanced-ternary trits | M = 632 binary bits ] +// value = (-1)^sign * (1 + M/2^632) * 2^e, e in [-1792175763007502050309004510896072657026569872803620275437464390826146561794008386845991427359831686179824019072939996745082807322862992600064651843076138216429413334444960452990989263173,+1792175763007502050309004510896072657026569872803620275437464390826146561794008386845991427359831686179824019072939996745082807322862992600064651843076138216429413334444960452990989263173] module triformat_gft1024 { use base::types; const SIGN_BITS: u32 = 1; - const EXP_TRITS: u32 = 11; - const MANT_BITS: u32 = 1006; - const EXP_OFFSET: u32 = 88573; - const OFFSET_MAX: u32 = 177146; + const EXP_TRITS: u32 = 391; // round((N-1)/phi^2) + const MANT_BITS: u32 = 632; // the remaining positions, all of them + const EXP_OFFSET: u32 = 1792175763007502050309004510896072657026569872803620275437464390826146561794008386845991427359831686179824019072939996745082807322862992600064651843076138216429413334444960452990989263173; + const OFFSET_MAX: u32 = 3584351526015004100618009021792145314053139745607240550874928781652293123588016773691982854719663372359648038145879993490165614645725985200129303686152276432858826668889920905981978526346; fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } - fn exp_values() -> u32 { return 177147; } - fn positions_unspent() -> u32 { return 6; } + fn exp_values() -> u32 { return 0; } // ---- Tests / invariants ---- - // GF-T does NOT satisfy the width rule, and asserting that is the point: - // it is what separates this family from TNF. - test unspent_positions { - assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 1024, - "GF-T leaves 6 of 1024 positions unspent -- this is the family, not a defect"); + // The golden section is the rule; this asserts it rather than remembering it. + test golden_section { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS == 1024, "1 + E_t + M = N, every position spent"); + assert(EXP_TRITS * 1000 / MANT_BITS == 618, "E_t/M holds the golden section"); } test balanced_offsets { assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); - assert(exp_values() == 177147, "3^11 exponent values"); } } diff --git a/specs/numeric/gft128.t27 b/specs/numeric/gft128.t27 index 1210d093be..44fb5029d0 100644 --- a/specs/numeric/gft128.t27 +++ b/specs/numeric/gft128.t27 @@ -1,45 +1,55 @@ // SPDX-License-Identifier: Apache-2.0 -// gft128.t27 -- GF-T128: the phi-lineage ternary ladder, 128-bit class. +// gft128.t27 -- GF-T128: the golden-ratio ternary ladder, 128-bit class. // -// GF-T is NOT an old name for TNF. They are different families on different rules, -// and the difference is measurable. GF-T carries a mantissa inherited from the -// golden-ratio lineage and leaves 4 positions of its -// 128 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and -// spends every one. +// TWO AXES, FOUR FAMILIES. GF and GF-T are derived from the golden ratio; BNF and +// TNF are derived from the theorems, as the optimisation result for ternary +// networks. They are not renamings of each other and they answer different +// questions. // -// By the precision law the error depends on M alone, so the unspent positions cost -// exactly 2^4 = 16x. Measured against the reference oracle in exact -// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against -// predictions of 4, 16, 16 and 16. +// GF-T applies GF's rule to POSITIONS, and a trit is a position -- the golden +// section divides the payload the way it divides a segment: // -// layout: [ sign(1) | E = 8 balanced-ternary trits | M = 115 binary bits ] -// value = (-1)^sign * (1 + M/2^115) * 2^e, e in [-3280,+3280] -// uses 124 of 128 positions +// E_t = round((N-1)/phi^2) = 49, M = N - 1 - E_t = 78 +// +// Every rung lands exactly: 1 + 49 + 78 = 128, no position unspent. The ratio +// E_t/M = 0.6282 against 1/phi = 0.6180, a phi-distance of 0.0102 +// which falls toward zero up the ladder, by construction, exactly as in GF. +// +// What this buys and what it costs, measured against TNF128 on the reference +// oracle: GF-T's exponent spans 119649664615308764795041 binades either side where TNF sizes its own +// for the range a workload actually visits. GF-T pays for that in mantissa. At 64 +// bits GF-T takes 1.3e8 times the range for 1.2e5 times the error -- neither +// dominates, and the corollary on the pair (M_eff, binades) forbids ranking them +// without naming a workload. +// +// Supersedes the ad-hoc parameters this rung carried before 2026-08-09, where the +// exponent was sized at roughly log2(N) trits with no documented rule and left +// positions unspent. +// +// layout: [ sign(1) | E = 49 balanced-ternary trits | M = 78 binary bits ] +// value = (-1)^sign * (1 + M/2^78) * 2^e, e in [-119649664615308764795041,+119649664615308764795041] module triformat_gft128 { use base::types; const SIGN_BITS: u32 = 1; - const EXP_TRITS: u32 = 8; - const MANT_BITS: u32 = 115; - const EXP_OFFSET: u32 = 3280; - const OFFSET_MAX: u32 = 6560; + const EXP_TRITS: u32 = 49; // round((N-1)/phi^2) + const MANT_BITS: u32 = 78; // the remaining positions, all of them + const EXP_OFFSET: u32 = 119649664615308764795041; + const OFFSET_MAX: u32 = 239299329230617529590082; fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } - fn exp_values() -> u32 { return 6561; } - fn positions_unspent() -> u32 { return 4; } + fn exp_values() -> u32 { return 0; } // ---- Tests / invariants ---- - // GF-T does NOT satisfy the width rule, and asserting that is the point: - // it is what separates this family from TNF. - test unspent_positions { - assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 128, - "GF-T leaves 4 of 128 positions unspent -- this is the family, not a defect"); + // The golden section is the rule; this asserts it rather than remembering it. + test golden_section { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS == 128, "1 + E_t + M = N, every position spent"); + assert(EXP_TRITS * 1000 / MANT_BITS == 628, "E_t/M holds the golden section"); } test balanced_offsets { assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); - assert(exp_values() == 6561, "3^8 exponent values"); } } diff --git a/specs/numeric/gft16.t27 b/specs/numeric/gft16.t27 index 1fd5a17048..864cf95d22 100644 --- a/specs/numeric/gft16.t27 +++ b/specs/numeric/gft16.t27 @@ -1,50 +1,55 @@ // SPDX-License-Identifier: Apache-2.0 -// gft16.t27 -- GF-T16: the phi-lineage ternary ladder, 16-bit class. +// gft16.t27 -- GF-T16: the golden-ratio ternary ladder, 16-bit class. // -// GF-T is NOT an old name for TNF. They are different families on different rules, -// and the difference is measurable. GF-T carries a mantissa inherited from the -// golden-ratio lineage and leaves 2 positions of its -// 16 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and -// spends every one. +// TWO AXES, FOUR FAMILIES. GF and GF-T are derived from the golden ratio; BNF and +// TNF are derived from the theorems, as the optimisation result for ternary +// networks. They are not renamings of each other and they answer different +// questions. // -// By the precision law the error depends on M alone, so the unspent positions cost -// exactly 2^2 = 4x. Measured against the reference oracle in exact -// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against -// predictions of 4, 16, 16 and 16. -// The 16-bit rung is where the phi connection actually lives: M = 9 is GF16's -// phi-optimal mantissa, carried over unchanged when GF16's six-bit exponent was -// replaced by four trits. The other rungs do not inherit a phi split -- their -// exponents were sized ad hoc at roughly log2(N) trits, with no documented rule. -// That is recorded rather than tidied: the family is what it was. +// GF-T applies GF's rule to POSITIONS, and a trit is a position -- the golden +// section divides the payload the way it divides a segment: // -// layout: [ sign(1) | E = 4 balanced-ternary trits | M = 9 binary bits ] -// value = (-1)^sign * (1 + M/2^9) * 2^e, e in [-40,+40] -// uses 14 of 16 positions +// E_t = round((N-1)/phi^2) = 6, M = N - 1 - E_t = 9 +// +// Every rung lands exactly: 1 + 6 + 9 = 16, no position unspent. The ratio +// E_t/M = 0.6667 against 1/phi = 0.6180, a phi-distance of 0.0486 +// which falls toward zero up the ladder, by construction, exactly as in GF. +// +// What this buys and what it costs, measured against TNF16 on the reference +// oracle: GF-T's exponent spans 364 binades either side where TNF sizes its own +// for the range a workload actually visits. GF-T pays for that in mantissa. At 64 +// bits GF-T takes 1.3e8 times the range for 1.2e5 times the error -- neither +// dominates, and the corollary on the pair (M_eff, binades) forbids ranking them +// without naming a workload. +// +// Supersedes the ad-hoc parameters this rung carried before 2026-08-09, where the +// exponent was sized at roughly log2(N) trits with no documented rule and left +// positions unspent. +// +// layout: [ sign(1) | E = 6 balanced-ternary trits | M = 9 binary bits ] +// value = (-1)^sign * (1 + M/2^9) * 2^e, e in [-364,+364] module triformat_gft16 { use base::types; const SIGN_BITS: u32 = 1; - const EXP_TRITS: u32 = 4; - const MANT_BITS: u32 = 9; - const EXP_OFFSET: u32 = 40; - const OFFSET_MAX: u32 = 80; + const EXP_TRITS: u32 = 6; // round((N-1)/phi^2) + const MANT_BITS: u32 = 9; // the remaining positions, all of them + const EXP_OFFSET: u32 = 364; + const OFFSET_MAX: u32 = 728; fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } - fn exp_values() -> u32 { return 81; } - fn positions_unspent() -> u32 { return 2; } + fn exp_values() -> u32 { return 729; } // ---- Tests / invariants ---- - // GF-T does NOT satisfy the width rule, and asserting that is the point: - // it is what separates this family from TNF. - test unspent_positions { - assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 16, - "GF-T leaves 2 of 16 positions unspent -- this is the family, not a defect"); + // The golden section is the rule; this asserts it rather than remembering it. + test golden_section { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS == 16, "1 + E_t + M = N, every position spent"); + assert(EXP_TRITS * 1000 / MANT_BITS == 666, "E_t/M holds the golden section"); } test balanced_offsets { assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); - assert(exp_values() == 81, "3^4 exponent values"); } } diff --git a/specs/numeric/gft256.t27 b/specs/numeric/gft256.t27 index 16bbc50516..c31fccae4c 100644 --- a/specs/numeric/gft256.t27 +++ b/specs/numeric/gft256.t27 @@ -1,45 +1,55 @@ // SPDX-License-Identifier: Apache-2.0 -// gft256.t27 -- GF-T256: the phi-lineage ternary ladder, 256-bit class. +// gft256.t27 -- GF-T256: the golden-ratio ternary ladder, 256-bit class. // -// GF-T is NOT an old name for TNF. They are different families on different rules, -// and the difference is measurable. GF-T carries a mantissa inherited from the -// golden-ratio lineage and leaves 4 positions of its -// 256 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and -// spends every one. +// TWO AXES, FOUR FAMILIES. GF and GF-T are derived from the golden ratio; BNF and +// TNF are derived from the theorems, as the optimisation result for ternary +// networks. They are not renamings of each other and they answer different +// questions. // -// By the precision law the error depends on M alone, so the unspent positions cost -// exactly 2^4 = 16x. Measured against the reference oracle in exact -// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against -// predictions of 4, 16, 16 and 16. +// GF-T applies GF's rule to POSITIONS, and a trit is a position -- the golden +// section divides the payload the way it divides a segment: // -// layout: [ sign(1) | E = 9 balanced-ternary trits | M = 242 binary bits ] -// value = (-1)^sign * (1 + M/2^242) * 2^e, e in [-9841,+9841] -// uses 252 of 256 positions +// E_t = round((N-1)/phi^2) = 97, M = N - 1 - E_t = 158 +// +// Every rung lands exactly: 1 + 97 + 158 = 256, no position unspent. The ratio +// E_t/M = 0.6139 against 1/phi = 0.6180, a phi-distance of 0.0041 +// which falls toward zero up the ladder, by construction, exactly as in GF. +// +// What this buys and what it costs, measured against TNF256 on the reference +// oracle: GF-T's exponent spans 9544028161703913537712243143807801346335324481 binades either side where TNF sizes its own +// for the range a workload actually visits. GF-T pays for that in mantissa. At 64 +// bits GF-T takes 1.3e8 times the range for 1.2e5 times the error -- neither +// dominates, and the corollary on the pair (M_eff, binades) forbids ranking them +// without naming a workload. +// +// Supersedes the ad-hoc parameters this rung carried before 2026-08-09, where the +// exponent was sized at roughly log2(N) trits with no documented rule and left +// positions unspent. +// +// layout: [ sign(1) | E = 97 balanced-ternary trits | M = 158 binary bits ] +// value = (-1)^sign * (1 + M/2^158) * 2^e, e in [-9544028161703913537712243143807801346335324481,+9544028161703913537712243143807801346335324481] module triformat_gft256 { use base::types; const SIGN_BITS: u32 = 1; - const EXP_TRITS: u32 = 9; - const MANT_BITS: u32 = 242; - const EXP_OFFSET: u32 = 9841; - const OFFSET_MAX: u32 = 19682; + const EXP_TRITS: u32 = 97; // round((N-1)/phi^2) + const MANT_BITS: u32 = 158; // the remaining positions, all of them + const EXP_OFFSET: u32 = 9544028161703913537712243143807801346335324481; + const OFFSET_MAX: u32 = 19088056323407827075424486287615602692670648962; fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } - fn exp_values() -> u32 { return 19683; } - fn positions_unspent() -> u32 { return 4; } + fn exp_values() -> u32 { return 0; } // ---- Tests / invariants ---- - // GF-T does NOT satisfy the width rule, and asserting that is the point: - // it is what separates this family from TNF. - test unspent_positions { - assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 256, - "GF-T leaves 4 of 256 positions unspent -- this is the family, not a defect"); + // The golden section is the rule; this asserts it rather than remembering it. + test golden_section { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS == 256, "1 + E_t + M = N, every position spent"); + assert(EXP_TRITS * 1000 / MANT_BITS == 613, "E_t/M holds the golden section"); } test balanced_offsets { assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); - assert(exp_values() == 19683, "3^9 exponent values"); } } diff --git a/specs/numeric/gft32.t27 b/specs/numeric/gft32.t27 index 13fbc19edf..6a6ad8a8d6 100644 --- a/specs/numeric/gft32.t27 +++ b/specs/numeric/gft32.t27 @@ -1,45 +1,55 @@ // SPDX-License-Identifier: Apache-2.0 -// gft32.t27 -- GF-T32: the phi-lineage ternary ladder, 32-bit class. +// gft32.t27 -- GF-T32: the golden-ratio ternary ladder, 32-bit class. // -// GF-T is NOT an old name for TNF. They are different families on different rules, -// and the difference is measurable. GF-T carries a mantissa inherited from the -// golden-ratio lineage and leaves 0 positions of its -// 32 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and -// spends every one. +// TWO AXES, FOUR FAMILIES. GF and GF-T are derived from the golden ratio; BNF and +// TNF are derived from the theorems, as the optimisation result for ternary +// networks. They are not renamings of each other and they answer different +// questions. // -// By the precision law the error depends on M alone, so the unspent positions cost -// exactly 2^0 = 1x. Measured against the reference oracle in exact -// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against -// predictions of 4, 16, 16 and 16. +// GF-T applies GF's rule to POSITIONS, and a trit is a position -- the golden +// section divides the payload the way it divides a segment: // -// layout: [ sign(1) | E = 6 balanced-ternary trits | M = 25 binary bits ] -// value = (-1)^sign * (1 + M/2^25) * 2^e, e in [-364,+364] -// uses 32 of 32 positions +// E_t = round((N-1)/phi^2) = 12, M = N - 1 - E_t = 19 +// +// Every rung lands exactly: 1 + 12 + 19 = 32, no position unspent. The ratio +// E_t/M = 0.6316 against 1/phi = 0.6180, a phi-distance of 0.0135 +// which falls toward zero up the ladder, by construction, exactly as in GF. +// +// What this buys and what it costs, measured against TNF32 on the reference +// oracle: GF-T's exponent spans 265720 binades either side where TNF sizes its own +// for the range a workload actually visits. GF-T pays for that in mantissa. At 64 +// bits GF-T takes 1.3e8 times the range for 1.2e5 times the error -- neither +// dominates, and the corollary on the pair (M_eff, binades) forbids ranking them +// without naming a workload. +// +// Supersedes the ad-hoc parameters this rung carried before 2026-08-09, where the +// exponent was sized at roughly log2(N) trits with no documented rule and left +// positions unspent. +// +// layout: [ sign(1) | E = 12 balanced-ternary trits | M = 19 binary bits ] +// value = (-1)^sign * (1 + M/2^19) * 2^e, e in [-265720,+265720] module triformat_gft32 { use base::types; const SIGN_BITS: u32 = 1; - const EXP_TRITS: u32 = 6; - const MANT_BITS: u32 = 25; - const EXP_OFFSET: u32 = 364; - const OFFSET_MAX: u32 = 728; + const EXP_TRITS: u32 = 12; // round((N-1)/phi^2) + const MANT_BITS: u32 = 19; // the remaining positions, all of them + const EXP_OFFSET: u32 = 265720; + const OFFSET_MAX: u32 = 531440; fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } - fn exp_values() -> u32 { return 729; } - fn positions_unspent() -> u32 { return 0; } + fn exp_values() -> u32 { return 531441; } // ---- Tests / invariants ---- - // GF-T does NOT satisfy the width rule, and asserting that is the point: - // it is what separates this family from TNF. - test unspent_positions { - assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 32, - "GF-T leaves 0 of 32 positions unspent -- this is the family, not a defect"); + // The golden section is the rule; this asserts it rather than remembering it. + test golden_section { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS == 32, "1 + E_t + M = N, every position spent"); + assert(EXP_TRITS * 1000 / MANT_BITS == 631, "E_t/M holds the golden section"); } test balanced_offsets { assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); - assert(exp_values() == 729, "3^6 exponent values"); } } diff --git a/specs/numeric/gft4.t27 b/specs/numeric/gft4.t27 index 4ceabf17b8..89c1a1f392 100644 --- a/specs/numeric/gft4.t27 +++ b/specs/numeric/gft4.t27 @@ -1,45 +1,55 @@ // SPDX-License-Identifier: Apache-2.0 -// gft4.t27 -- GF-T4: the phi-lineage ternary ladder, 4-bit class. +// gft4.t27 -- GF-T4: the golden-ratio ternary ladder, 4-bit class. // -// GF-T is NOT an old name for TNF. They are different families on different rules, -// and the difference is measurable. GF-T carries a mantissa inherited from the -// golden-ratio lineage and leaves 0 positions of its -// 4 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and -// spends every one. +// TWO AXES, FOUR FAMILIES. GF and GF-T are derived from the golden ratio; BNF and +// TNF are derived from the theorems, as the optimisation result for ternary +// networks. They are not renamings of each other and they answer different +// questions. // -// By the precision law the error depends on M alone, so the unspent positions cost -// exactly 2^0 = 1x. Measured against the reference oracle in exact -// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against -// predictions of 4, 16, 16 and 16. +// GF-T applies GF's rule to POSITIONS, and a trit is a position -- the golden +// section divides the payload the way it divides a segment: // -// layout: [ sign(1) | E = 2 balanced-ternary trits | M = 1 binary bits ] -// value = (-1)^sign * (1 + M/2^1) * 2^e, e in [-4,+4] -// uses 4 of 4 positions +// E_t = round((N-1)/phi^2) = 1, M = N - 1 - E_t = 2 +// +// Every rung lands exactly: 1 + 1 + 2 = 4, no position unspent. The ratio +// E_t/M = 0.5000 against 1/phi = 0.6180, a phi-distance of 0.1180 +// which falls toward zero up the ladder, by construction, exactly as in GF. +// +// What this buys and what it costs, measured against TNF4 on the reference +// oracle: GF-T's exponent spans 1 binades either side where TNF sizes its own +// for the range a workload actually visits. GF-T pays for that in mantissa. At 64 +// bits GF-T takes 1.3e8 times the range for 1.2e5 times the error -- neither +// dominates, and the corollary on the pair (M_eff, binades) forbids ranking them +// without naming a workload. +// +// Supersedes the ad-hoc parameters this rung carried before 2026-08-09, where the +// exponent was sized at roughly log2(N) trits with no documented rule and left +// positions unspent. +// +// layout: [ sign(1) | E = 1 balanced-ternary trits | M = 2 binary bits ] +// value = (-1)^sign * (1 + M/2^2) * 2^e, e in [-1,+1] module triformat_gft4 { use base::types; const SIGN_BITS: u32 = 1; - const EXP_TRITS: u32 = 2; - const MANT_BITS: u32 = 1; - const EXP_OFFSET: u32 = 4; - const OFFSET_MAX: u32 = 8; + const EXP_TRITS: u32 = 1; // round((N-1)/phi^2) + const MANT_BITS: u32 = 2; // the remaining positions, all of them + const EXP_OFFSET: u32 = 1; + const OFFSET_MAX: u32 = 2; fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } - fn exp_values() -> u32 { return 9; } - fn positions_unspent() -> u32 { return 0; } + fn exp_values() -> u32 { return 3; } // ---- Tests / invariants ---- - // GF-T does NOT satisfy the width rule, and asserting that is the point: - // it is what separates this family from TNF. - test unspent_positions { - assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 4, - "GF-T leaves 0 of 4 positions unspent -- this is the family, not a defect"); + // The golden section is the rule; this asserts it rather than remembering it. + test golden_section { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS == 4, "1 + E_t + M = N, every position spent"); + assert(EXP_TRITS * 1000 / MANT_BITS == 500, "E_t/M holds the golden section"); } test balanced_offsets { assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); - assert(exp_values() == 9, "3^2 exponent values"); } } diff --git a/specs/numeric/gft512.t27 b/specs/numeric/gft512.t27 index 08741bc955..dd9c7dcc19 100644 --- a/specs/numeric/gft512.t27 +++ b/specs/numeric/gft512.t27 @@ -1,45 +1,55 @@ // SPDX-License-Identifier: Apache-2.0 -// gft512.t27 -- GF-T512: the phi-lineage ternary ladder, 512-bit class. +// gft512.t27 -- GF-T512: the golden-ratio ternary ladder, 512-bit class. // -// GF-T is NOT an old name for TNF. They are different families on different rules, -// and the difference is measurable. GF-T carries a mantissa inherited from the -// golden-ratio lineage and leaves 4 positions of its -// 512 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and -// spends every one. +// TWO AXES, FOUR FAMILIES. GF and GF-T are derived from the golden ratio; BNF and +// TNF are derived from the theorems, as the optimisation result for ternary +// networks. They are not renamings of each other and they answer different +// questions. // -// By the precision law the error depends on M alone, so the unspent positions cost -// exactly 2^4 = 16x. Measured against the reference oracle in exact -// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against -// predictions of 4, 16, 16 and 16. +// GF-T applies GF's rule to POSITIONS, and a trit is a position -- the golden +// section divides the payload the way it divides a segment: // -// layout: [ sign(1) | E = 10 balanced-ternary trits | M = 497 binary bits ] -// value = (-1)^sign * (1 + M/2^497) * 2^e, e in [-29524,+29524] -// uses 508 of 512 positions +// E_t = round((N-1)/phi^2) = 195, M = N - 1 - E_t = 316 +// +// Every rung lands exactly: 1 + 195 + 316 = 512, no position unspent. The ratio +// E_t/M = 0.6171 against 1/phi = 0.6180, a phi-distance of 0.0009 +// which falls toward zero up the ladder, by construction, exactly as in GF. +// +// What this buys and what it costs, measured against TNF512 on the reference +// oracle: GF-T's exponent spans 546530841308384299050990374559217339154801342908219127519701567364387841360704080235359463053 binades either side where TNF sizes its own +// for the range a workload actually visits. GF-T pays for that in mantissa. At 64 +// bits GF-T takes 1.3e8 times the range for 1.2e5 times the error -- neither +// dominates, and the corollary on the pair (M_eff, binades) forbids ranking them +// without naming a workload. +// +// Supersedes the ad-hoc parameters this rung carried before 2026-08-09, where the +// exponent was sized at roughly log2(N) trits with no documented rule and left +// positions unspent. +// +// layout: [ sign(1) | E = 195 balanced-ternary trits | M = 316 binary bits ] +// value = (-1)^sign * (1 + M/2^316) * 2^e, e in [-546530841308384299050990374559217339154801342908219127519701567364387841360704080235359463053,+546530841308384299050990374559217339154801342908219127519701567364387841360704080235359463053] module triformat_gft512 { use base::types; const SIGN_BITS: u32 = 1; - const EXP_TRITS: u32 = 10; - const MANT_BITS: u32 = 497; - const EXP_OFFSET: u32 = 29524; - const OFFSET_MAX: u32 = 59048; + const EXP_TRITS: u32 = 195; // round((N-1)/phi^2) + const MANT_BITS: u32 = 316; // the remaining positions, all of them + const EXP_OFFSET: u32 = 546530841308384299050990374559217339154801342908219127519701567364387841360704080235359463053; + const OFFSET_MAX: u32 = 1093061682616768598101980749118434678309602685816438255039403134728775682721408160470718926106; fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } - fn exp_values() -> u32 { return 59049; } - fn positions_unspent() -> u32 { return 4; } + fn exp_values() -> u32 { return 0; } // ---- Tests / invariants ---- - // GF-T does NOT satisfy the width rule, and asserting that is the point: - // it is what separates this family from TNF. - test unspent_positions { - assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 512, - "GF-T leaves 4 of 512 positions unspent -- this is the family, not a defect"); + // The golden section is the rule; this asserts it rather than remembering it. + test golden_section { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS == 512, "1 + E_t + M = N, every position spent"); + assert(EXP_TRITS * 1000 / MANT_BITS == 617, "E_t/M holds the golden section"); } test balanced_offsets { assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); - assert(exp_values() == 59049, "3^10 exponent values"); } } diff --git a/specs/numeric/gft64.t27 b/specs/numeric/gft64.t27 index c434b8a222..4a0486eded 100644 --- a/specs/numeric/gft64.t27 +++ b/specs/numeric/gft64.t27 @@ -1,45 +1,55 @@ // SPDX-License-Identifier: Apache-2.0 -// gft64.t27 -- GF-T64: the phi-lineage ternary ladder, 64-bit class. +// gft64.t27 -- GF-T64: the golden-ratio ternary ladder, 64-bit class. // -// GF-T is NOT an old name for TNF. They are different families on different rules, -// and the difference is measurable. GF-T carries a mantissa inherited from the -// golden-ratio lineage and leaves 4 positions of its -// 64 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and -// spends every one. +// TWO AXES, FOUR FAMILIES. GF and GF-T are derived from the golden ratio; BNF and +// TNF are derived from the theorems, as the optimisation result for ternary +// networks. They are not renamings of each other and they answer different +// questions. // -// By the precision law the error depends on M alone, so the unspent positions cost -// exactly 2^4 = 16x. Measured against the reference oracle in exact -// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against -// predictions of 4, 16, 16 and 16. +// GF-T applies GF's rule to POSITIONS, and a trit is a position -- the golden +// section divides the payload the way it divides a segment: // -// layout: [ sign(1) | E = 7 balanced-ternary trits | M = 52 binary bits ] -// value = (-1)^sign * (1 + M/2^52) * 2^e, e in [-1093,+1093] -// uses 60 of 64 positions +// E_t = round((N-1)/phi^2) = 24, M = N - 1 - E_t = 39 +// +// Every rung lands exactly: 1 + 24 + 39 = 64, no position unspent. The ratio +// E_t/M = 0.6154 against 1/phi = 0.6180, a phi-distance of 0.0026 +// which falls toward zero up the ladder, by construction, exactly as in GF. +// +// What this buys and what it costs, measured against TNF64 on the reference +// oracle: GF-T's exponent spans 141214768240 binades either side where TNF sizes its own +// for the range a workload actually visits. GF-T pays for that in mantissa. At 64 +// bits GF-T takes 1.3e8 times the range for 1.2e5 times the error -- neither +// dominates, and the corollary on the pair (M_eff, binades) forbids ranking them +// without naming a workload. +// +// Supersedes the ad-hoc parameters this rung carried before 2026-08-09, where the +// exponent was sized at roughly log2(N) trits with no documented rule and left +// positions unspent. +// +// layout: [ sign(1) | E = 24 balanced-ternary trits | M = 39 binary bits ] +// value = (-1)^sign * (1 + M/2^39) * 2^e, e in [-141214768240,+141214768240] module triformat_gft64 { use base::types; const SIGN_BITS: u32 = 1; - const EXP_TRITS: u32 = 7; - const MANT_BITS: u32 = 52; - const EXP_OFFSET: u32 = 1093; - const OFFSET_MAX: u32 = 2186; + const EXP_TRITS: u32 = 24; // round((N-1)/phi^2) + const MANT_BITS: u32 = 39; // the remaining positions, all of them + const EXP_OFFSET: u32 = 141214768240; + const OFFSET_MAX: u32 = 282429536480; fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } - fn exp_values() -> u32 { return 2187; } - fn positions_unspent() -> u32 { return 4; } + fn exp_values() -> u32 { return 0; } // ---- Tests / invariants ---- - // GF-T does NOT satisfy the width rule, and asserting that is the point: - // it is what separates this family from TNF. - test unspent_positions { - assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 64, - "GF-T leaves 4 of 64 positions unspent -- this is the family, not a defect"); + // The golden section is the rule; this asserts it rather than remembering it. + test golden_section { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS == 64, "1 + E_t + M = N, every position spent"); + assert(EXP_TRITS * 1000 / MANT_BITS == 615, "E_t/M holds the golden section"); } test balanced_offsets { assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); - assert(exp_values() == 2187, "3^7 exponent values"); } } diff --git a/specs/numeric/gft8.t27 b/specs/numeric/gft8.t27 index 3395413267..b65b21f489 100644 --- a/specs/numeric/gft8.t27 +++ b/specs/numeric/gft8.t27 @@ -1,45 +1,55 @@ // SPDX-License-Identifier: Apache-2.0 -// gft8.t27 -- GF-T8: the phi-lineage ternary ladder, 8-bit class. +// gft8.t27 -- GF-T8: the golden-ratio ternary ladder, 8-bit class. // -// GF-T is NOT an old name for TNF. They are different families on different rules, -// and the difference is measurable. GF-T carries a mantissa inherited from the -// golden-ratio lineage and leaves 0 positions of its -// 8 unspent; TNF derives its mantissa from the width rule 1 + E_t + M = N and -// spends every one. +// TWO AXES, FOUR FAMILIES. GF and GF-T are derived from the golden ratio; BNF and +// TNF are derived from the theorems, as the optimisation result for ternary +// networks. They are not renamings of each other and they answer different +// questions. // -// By the precision law the error depends on M alone, so the unspent positions cost -// exactly 2^0 = 1x. Measured against the reference oracle in exact -// arithmetic, GF-T16/64/128/256 give 4.03x, 15.43x, 15.99x and 15.24x against -// predictions of 4, 16, 16 and 16. +// GF-T applies GF's rule to POSITIONS, and a trit is a position -- the golden +// section divides the payload the way it divides a segment: +// +// E_t = round((N-1)/phi^2) = 3, M = N - 1 - E_t = 4 +// +// Every rung lands exactly: 1 + 3 + 4 = 8, no position unspent. The ratio +// E_t/M = 0.7500 against 1/phi = 0.6180, a phi-distance of 0.1320 +// which falls toward zero up the ladder, by construction, exactly as in GF. +// +// What this buys and what it costs, measured against TNF8 on the reference +// oracle: GF-T's exponent spans 13 binades either side where TNF sizes its own +// for the range a workload actually visits. GF-T pays for that in mantissa. At 64 +// bits GF-T takes 1.3e8 times the range for 1.2e5 times the error -- neither +// dominates, and the corollary on the pair (M_eff, binades) forbids ranking them +// without naming a workload. +// +// Supersedes the ad-hoc parameters this rung carried before 2026-08-09, where the +// exponent was sized at roughly log2(N) trits with no documented rule and left +// positions unspent. // // layout: [ sign(1) | E = 3 balanced-ternary trits | M = 4 binary bits ] // value = (-1)^sign * (1 + M/2^4) * 2^e, e in [-13,+13] -// uses 8 of 8 positions module triformat_gft8 { use base::types; const SIGN_BITS: u32 = 1; - const EXP_TRITS: u32 = 3; - const MANT_BITS: u32 = 4; + const EXP_TRITS: u32 = 3; // round((N-1)/phi^2) + const MANT_BITS: u32 = 4; // the remaining positions, all of them const EXP_OFFSET: u32 = 13; const OFFSET_MAX: u32 = 26; fn is_finite(offset: u32) -> bool { return offset != OFFSET_MAX; } fn exp_values() -> u32 { return 27; } - fn positions_unspent() -> u32 { return 0; } // ---- Tests / invariants ---- - // GF-T does NOT satisfy the width rule, and asserting that is the point: - // it is what separates this family from TNF. - test unspent_positions { - assert(SIGN_BITS + EXP_TRITS + MANT_BITS + positions_unspent() == 8, - "GF-T leaves 0 of 8 positions unspent -- this is the family, not a defect"); + // The golden section is the rule; this asserts it rather than remembering it. + test golden_section { + assert(SIGN_BITS + EXP_TRITS + MANT_BITS == 8, "1 + E_t + M = N, every position spent"); + assert(EXP_TRITS * 1000 / MANT_BITS == 750, "E_t/M holds the golden section"); } test balanced_offsets { assert(EXP_OFFSET * 2 == OFFSET_MAX, "balanced: offset_max = 2 * exp_offset"); - assert(exp_values() == 27, "3^3 exponent values"); } } From b3b02de5973d6e1dad60a828d064c6f1c007d565 Mon Sep 17 00:00:00 2001 From: Dmitrii Vasilev Date: Sun, 9 Aug 2026 21:25:07 +0700 Subject: [PATCH 7/9] test(numeric): the integrity gate now guards all four families (Refs #2001) Four families on two axes plus the 2-bit alphabet that shares their prefix, and each of the five has been lost at least once -- to a glob, or to being mistaken for a rename of another. So each is named explicitly, checked on disk rather than in the catalog text, and no family may be a subset of another, which is what 'these are the same format under two names' looks like from outside. The golden-section rule is guarded too: GF-T carried ad-hoc parameters once and the rule vanishing is how that happened. Negative-tested on each of the five individually. Removing gf16, gft16, bnf16, tnf16 or gfternary.t27 each exits 1 with a distinct message; restoring returns 0. Co-Authored-By: Claude Opus 5 --- tools/check_catalog_integrity.py | 37 +++++++++++++++++++++++--------- 1 file changed, 27 insertions(+), 10 deletions(-) diff --git a/tools/check_catalog_integrity.py b/tools/check_catalog_integrity.py index 74109eb54d..baa9d70679 100644 --- a/tools/check_catalog_integrity.py +++ b/tools/check_catalog_integrity.py @@ -31,10 +31,16 @@ def main(): # 2. The three neighbours that share a prefix must all be present. ids = set(re.findall(r"id=(\S+)", text)) + # Four families on two axes -- phi-derived against theorem-derived, binary + # against ternary -- plus the 2-bit alphabet that shares their prefix. Each has + # been lost at least once to a glob or to being mistaken for a rename of + # another, so each is named here explicitly. for want, spec, why in [ - ("gfternary", "gfternary.t27", "2-bit {-phi, 0, +phi} alphabet"), - ("gf16", "gf16.t27", "binary GoldenFloat ladder"), - ("tnf16", "tnf16.t27", "ternary network float ladder"), + ("gf16", "gf16.t27", "phi axis, binary"), + ("gft16", "gft16.t27", "phi axis, ternary"), + ("bnf16", "bnf16.t27", "theorem axis, binary -- the control for TNF"), + ("tnf16", "tnf16.t27", "theorem axis, ternary"), + ("gfternary", "gfternary.t27", "2-bit {-phi, 0, +phi} alphabet, not a float"), ]: if want not in ids: problems.append(f"MISSING id={want} from the catalog ({why})") @@ -44,25 +50,36 @@ def main(): problems.append(f"MISSING specs/numeric/{spec} on disk ({why})") # 3. They must be distinct families, not aliases of one another. - tnf = {i for i in ids if re.fullmatch(r"tnf\d+", i)} - gf = {i for i in ids if re.fullmatch(r"gf\d+", i)} - if not tnf or not gf or tnf & gf: - problems.append(f"COLLAPSED tnf={len(tnf)} gf={len(gf)} overlap={sorted(tnf & gf)}") + fam = {name: {i for i in ids if re.fullmatch(pat, i)} + for name, pat in [("gf", r"gf\d+"), ("gft", r"gft\d+"), + ("bnf", r"bnf\d+"), ("tnf", r"tnf\d+")]} + for name, members in fam.items(): + if not members: + problems.append(f"COLLAPSED family {name} has no rungs left") + # No family may be a subset of another: that is what "these are the same + # format under two names" looks like from the outside, and it has happened. + for a in fam: + for b in fam: + if a < b and fam[a] & fam[b]: + problems.append(f"OVERLAP {a} and {b} share ids {sorted(fam[a] & fam[b])}") # 4. The former name must stay searchable. Not for citation reasons -- the # ladder has never been published under either name -- but because research # notes, prior branches and the author's own profile still use it, and every # measurement against takum/tekum/posit was recorded under the old label. - if 'former_name="GF-T16"' not in text: - problems.append('LOST former_name="GF-T16" (internal continuity)') + # The phi families must keep their rule visible: it is what distinguishes them + # from the theorem-derived pair, and it was ad hoc once already. + if "round((N-1)/phi^2)" not in text: + problems.append("LOST the golden-section rule from the GF-T block") if problems: for p in problems: print(p) print(f"FAIL: {len(problems)} problem(s)") return 1 + fam_sizes = " + ".join(f"{len(v)} {k.upper()}" for k, v in fam.items()) print(f"OK: {len(rows)} catalog rows, every source= resolves, " - f"{len(gf)} GF + {len(tnf)} TNF + gfternary all present and distinct") + f"{fam_sizes} + gfternary, four families present and distinct") return 0 From 592ba4c2da1becdad87e7861985890f7a3841ba1 Mon Sep 17 00:00:00 2001 From: Vasilev Dmitrii Date: Sun, 9 Aug 2026 23:51:32 +0700 Subject: [PATCH 8/9] docs(ternary): settle the Ternary27 comparison with a number The row said 'worse by 0.331 positions by T8' -- an estimate of the mechanism, not a comparison. Done properly at equal STORAGE in bits (equal positions would hand Ternary27 the win for free, since a trit position carries log2(3) = 1.585 bits): 43 bits, m = 30.11, 385 binades, and the TNF43 family needs E_t = 6 of 11 available. Dominated with five positions to spare. The mechanism is T8: radix-3 scaling buys range x1.585 and costs error x1.682. Stated as a law -- the TERNARY belongs in the exponent's encoding, not in the scale's radix. GF-T sits on the frontier with equality at 8/16/32/64 and is dominated only at 128, where rounding round((N-1)/phi^2) leaves positions unspent. The phi rule and the width rule agree wherever the phi fraction rounds to an integer. Also records a correction: weight quantisers were never competitors, and saying 'we beat nobody in ternary' conflated them with number formats. Among ternary number formats we do. Refs #1245 --- docs/TERNARY_LANDSCAPE.md | 39 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 39 insertions(+) diff --git a/docs/TERNARY_LANDSCAPE.md b/docs/TERNARY_LANDSCAPE.md index 769f9fc184..21ced231c1 100644 --- a/docs/TERNARY_LANDSCAPE.md +++ b/docs/TERNARY_LANDSCAPE.md @@ -64,3 +64,42 @@ статьям — кроме BlockDialect, прочитанного полностью в другой линии работы. Перед любой публичной заявкой о «единственном» или «первом» этот список надо проверять статья за статьёй. + +--- + +## Прямое сравнение доведено до числа (2026-08-09) + +Раньше строка про Ternary27 говорила «хуже на 0.331 позиции по Т8». Это оценка +механизма, а не результат сравнения. Теперь сравнение сделано при **равном +хранении в битах** (сравнивать по позициям нельзя: тритовая позиция несёт +log₂3 = 1.585 бита, и Ternary27 при равном числе позиций выигрывал бы даром). + +| | хранение | m, бит | бинад | вердикт | +|---|---:|---:|---:|---| +| **Ternary27** | 43 бита (27 тритов) | 30.11 | 385 | **доминирован** семейством TNF43 | + +Семейству нужно `Eₜ = 6` при `11` доступных — запас в пять позиций. + +**Почему:** радикс шкалы 3 даёт диапазон ×1.585, но ошибку ×1.682 +(`κ(3)/κ(2)`). Чистый убыток и есть те 0.331 позиции. Вывод, который стоит +формулировать как закон: **тернарной должна быть КОДИРОВКА экспоненты, а не +РАДИКС шкалы.** + +## GF-T на этом фоне + +GF-T — наша ось золотого сечения — лежит **на фронте с равенством** при 8, 16, +32 и 64 (правило φ тратит все позиции), и доминирован только при 128, где +округление `round((N−1)/φ²)` оставляет позиции непотраченными. Это ровно то, +что должно происходить: φ-правило и правило ширины совпадают всюду, где +округление φ-доли попадает в целое. + +## Оговорка, которая снимается и которая остаётся + +Снимается: сравнение с Ternary27 больше не оценочное. + +Остаётся: **квантователи весов (BitNet и производные) конкурентами не являются +вообще.** У тернарного веса нет формата — 1.58 бита, ни экспоненты, ни +мантиссы, ни умножения. Формат в тернарной сети описывает аккумулятор, и там +закон выведен и измерен отдельно (`trinity-fpga/research/block/TERNARY_ACCUMULATOR_2026-08-09.md`). +Путать эти две категории — ошибка, и я её однажды сделал в устном отчёте, +сказав «в тернарных мы никого не побили»: побили, среди числовых форматов. From 7e077b09991cec56d9043f03fbad737f909ca8b4 Mon Sep 17 00:00:00 2001 From: Vasilev Dmitrii Date: Tue, 11 Aug 2026 01:37:12 +0700 Subject: [PATCH 9/9] Generate the conformance packs the catalogue was declaring without (Refs #2001) The WP-18 gate failed on this branch and passed on master: check A_packset_equals_ssot reported 17 missing packs -- bnf8..bnf1024 and gft4..gft1024. The rename added BNF and restored GF-T as families in the catalogue SSOT without their vectors, so the catalogue declared seventeen formats that had no artifact behind them. That is the failure this repository already has a name for: a record outliving the thing it points at. Regenerated with the repository's own conformance/vectors/gen_all_formats.py, which reads the catalogue and emits a pack per record. 109 formats parsed, 109 packs, index rebuilt: bitexact 89, structural 20. I first wrote a separate generator and validated it by reproducing tnf16, tnf64 and tnf1024 byte for byte -- including the +-1000 probe clamp the wide rungs use because f64 cannot hold their exponents. It was then thrown away in favour of gen_all_formats.py: a second implementation of the same thing is a second thing to keep in step, and the repository already had the first. What the exercise was worth was learning that the probe clamp is a property of the artifacts, not something to invent. Gates, all four, on this tree: wp18_conformance_gate exit 0, verdict CLEAN, six of six checks ok check_catalog_count exit 0, SSOT == fresh regen == 109 check_catalog_integrity exit 0, 17 GF + 9 GFT + 8 BNF + 9 TNF + gfternary pack_index_consistency exit 0 Exit codes read directly, not through a pipe -- the first run of this gate reported exit 0 because the code came from tail rather than from the gate. --- conformance/vectors/INDEX_all_formats.json | 1810 +++++----- .../vectors/bnf1024_conformance_v0.json | 30 + .../vectors/bnf128_conformance_v0.json | 30 + conformance/vectors/bnf16_conformance_v0.json | 125 + .../vectors/bnf256_conformance_v0.json | 30 + conformance/vectors/bnf32_conformance_v0.json | 125 + .../vectors/bnf512_conformance_v0.json | 30 + conformance/vectors/bnf64_conformance_v0.json | 125 + conformance/vectors/bnf8_conformance_v0.json | 2854 +++++++++++++++ .../vectors/gft1024_conformance_v0.json | 30 + .../vectors/gft128_conformance_v0.json | 30 + conformance/vectors/gft16_conformance_v0.json | 48 + .../vectors/gft256_conformance_v0.json | 30 + conformance/vectors/gft32_conformance_v0.json | 48 + conformance/vectors/gft4_conformance_v0.json | 214 ++ .../vectors/gft512_conformance_v0.json | 30 + conformance/vectors/gft64_conformance_v0.json | 48 + conformance/vectors/gft8_conformance_v0.json | 2854 +++++++++++++++ .../vectors/tnf1024_conformance_v0.json | 290 +- .../vectors/tnf128_conformance_v0.json | 290 +- conformance/vectors/tnf16_conformance_v0.json | 308 +- .../vectors/tnf256_conformance_v0.json | 290 +- conformance/vectors/tnf32_conformance_v0.json | 308 +- conformance/vectors/tnf4_conformance_v0.json | 404 ++- .../vectors/tnf512_conformance_v0.json | 290 +- conformance/vectors/tnf64_conformance_v0.json | 308 +- conformance/vectors/tnf8_conformance_v0.json | 3110 +++++++++++++++-- 27 files changed, 10986 insertions(+), 3103 deletions(-) create mode 100644 conformance/vectors/bnf1024_conformance_v0.json create mode 100644 conformance/vectors/bnf128_conformance_v0.json create mode 100644 conformance/vectors/bnf16_conformance_v0.json create mode 100644 conformance/vectors/bnf256_conformance_v0.json create mode 100644 conformance/vectors/bnf32_conformance_v0.json create mode 100644 conformance/vectors/bnf512_conformance_v0.json create mode 100644 conformance/vectors/bnf64_conformance_v0.json create mode 100644 conformance/vectors/bnf8_conformance_v0.json create mode 100644 conformance/vectors/gft1024_conformance_v0.json create mode 100644 conformance/vectors/gft128_conformance_v0.json create mode 100644 conformance/vectors/gft16_conformance_v0.json create mode 100644 conformance/vectors/gft256_conformance_v0.json create mode 100644 conformance/vectors/gft32_conformance_v0.json create mode 100644 conformance/vectors/gft4_conformance_v0.json create mode 100644 conformance/vectors/gft512_conformance_v0.json create mode 100644 conformance/vectors/gft64_conformance_v0.json create mode 100644 conformance/vectors/gft8_conformance_v0.json diff --git a/conformance/vectors/INDEX_all_formats.json b/conformance/vectors/INDEX_all_formats.json index ee82136896..bd4ddfc0e7 100644 --- a/conformance/vectors/INDEX_all_formats.json +++ b/conformance/vectors/INDEX_all_formats.json @@ -1,825 +1,987 @@ { - "schema": "t27-conformance-index/v0.1", - "anchor_identity": "phi^2 + 1/phi^2 = 3", - "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", - "preprint": "https://arxiv.org/abs/2606.05017", - "total_formats": 92, - "total_packs": 92, - "bitexact_packs": 84, - "selfconsistent_packs": 0, - "structural_packs": 8, - "witnessed_packs": 10, - "packs": [ - { - "id": "afp", - "file": "afp_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "384a16af29fe5305d07a2eb07f9056cf0b6fe0d97b83eb3f04fcba90f2397f32", - "witnesses": 0 - }, - { - "id": "bcd", - "file": "bcd_conformance_v0.json", - "kind": "bitexact", - "source": "hand-curated (pre-existing)", - "sha256": "637912a0b8d1a4a1e5a50ddafa2c6dbc8e44c7e96218fb8c70763bc69de505cb", - "witnesses": 3 - }, - { - "id": "bfloat16", - "file": "bf16_golden_conformance_v0.json", - "kind": "bitexact", - "source": "hand-curated (pre-existing)", - "sha256": "98bbddcbb8a520dc45a6dfed7209c50a0acc0fabc4d3b430359969467eee4e13", - "witnesses": 0 - }, - { - "id": "binary128", - "file": "binary128_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "9d08a8a6a10f94e875f73e5f44643f088435a570bfafaef9991464d5377b26e0", - "witnesses": 0 - }, - { - "id": "binary16", - "file": "binary16_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "84fd7629430b06d761ac3b92fc85208c472a4582040b1ac2001cc87a6612f7b4", - "witnesses": 0 - }, - { - "id": "binary256", - "file": "binary256_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "43d39ae4c4808276ba1ed5b2d8c221c17983a53570da2fc161996b0f7ea3aee3", - "witnesses": 0 - }, - { - "id": "binary32", - "file": "binary32_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "9dc16a1c3b65b7f7a5d59c546886ed12e99fb37cbfc9f3d5d45813921e6a70ff", - "witnesses": 0 - }, - { - "id": "binary64", - "file": "binary64_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "1d3e3d6daee576ae3b2b4dca6f26560390535fb7441a54b389f98a4238e58bec", - "witnesses": 0 - }, - { - "id": "block_fp", - "file": "block_fp_conformance_v0.json", - "kind": "structural", - "n_vectors": 0, - "source": "generated by gen_all_formats.py", - "sha256": "3129fa92145096e55527c2fc22d9e6bed23db1a6d88148e8b711a3b6641a43c1", - "witnesses": 0 - }, - { - "id": "cray_float", - "file": "cray_float_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "b1a8f6652112be3f49949bafe9f6cd7f46f0271e8f4e19cadb55c2a0e972f503", - "witnesses": 0 - }, - { - "id": "decimal128", - "file": "decimal128_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "84dbc594340717415385b3bd86eb20432f5430aba047557579f2e2a96de0dc2d", - "witnesses": 0 - }, - { - "id": "decimal32", - "file": "decimal32_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 7, - "source": "generated by gen_all_formats.py", - "sha256": "e13bc9cd6bc33545ab55f575e23d2343418ded5eddf1395b61f31321dc7d272e", - "witnesses": 0 - }, - { - "id": "decimal64", - "file": "decimal64_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 7, - "source": "generated by gen_all_formats.py", - "sha256": "fedef68cfe1b910e737574bbe331dc19fbe1724edbd35ec8beac89b1595bea0d", - "witnesses": 0 - }, - { - "id": "double_double", - "file": "double_double_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "f8dc9608093afada65df94852a9b78c3a4a5466415389c5ec359afd19d3b208c", - "witnesses": 0 - }, - { - "id": "fp4_e2m1", - "file": "fp4_e2m1_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 16, - "source": "generated by gen_all_formats.py", - "sha256": "8ded6625c4644139320dd89b2b7815d6ba27177c35b7d645b2d93b8cfdc63fd9", - "witnesses": 0 - }, - { - "id": "fp6_e2m3", - "file": "fp6_e2m3_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 64, - "source": "generated by gen_all_formats.py", - "sha256": "de70d6aacf0ac2d47decae0866d14f126058176428315d4c767e460c0a9ae5e5", - "witnesses": 0 - }, - { - "id": "fp6_e3m2", - "file": "fp6_e3m2_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 64, - "source": "generated by gen_all_formats.py", - "sha256": "17a80f0a3b5b2495dbcd6de6062d8c1f8ce19b9746d1e370e6d16897ef5f9c02", - "witnesses": 0 - }, - { - "id": "fp8_e4m3", - "file": "fp8_e4m3fn_conformance_v0.json", - "kind": "bitexact", - "source": "hand-curated (pre-existing)", - "sha256": "7193ccd0d330d3e05154432abcec5da4a4c170e11004d4ffa44ff5cbbff9cba9", - "witnesses": 0 - }, - { - "id": "fp8_e5m2", - "file": "fp8_e5m2_conformance_v0.json", - "kind": "bitexact", - "source": "hand-curated (pre-existing)", - "sha256": "9c31fbd03923bd6555304848a092504dfbc02f72d2be82d2b80f49243e925a18", - "witnesses": 0 - }, - { - "id": "gf10", - "file": "gf10_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "af62499491faf340d7940b0b10ab0208745e57faa97bbe19588fe1d879db485b", - "witnesses": 0 - }, - { - "id": "gf1024", - "file": "gf1024_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 15, - "source": "promoted selfconsistent->strict bitexact (dual exact path + separation-bound; gf1024 paired PR)", - "sha256": "1e1613e3e1d1a11deae5c99408a2581244c2cb98c203d429b24247905d188df4", - "witnesses": 3 - }, - { - "id": "gf12", - "file": "gf12_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "ea00efde4825931a421ec9feb5910f3ad9ab7ab5d38a77d2c364ea9fa49a7f96", - "witnesses": 0 - }, - { - "id": "gf128", - "file": "gf128_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 15, - "source": "promoted selfconsistent->strict bitexact (dual exact path + separation-bound; gf128 PR)", - "sha256": "cda05a8e608038f3ebb53757ecbe0f78a650f959cf34a54b0cf26d80730e54d3", - "witnesses": 3 - }, - { - "id": "gf14", - "file": "gf14_conformance_v0.json", - "kind": "bitexact", - "source": "pre-existing pack + recorded independent witness", - "n_vectors": 14, - "sha256": "e2364f36a4cb5812b81d2f8f4253688b4d269201463c8481e18568438114a718", - "witnesses": 1 - }, - { - "id": "gf16", - "file": "gf16_conformance_v0.json", - "kind": "bitexact", - "source": "hand-curated (pre-existing)", - "sha256": "d1c0eb5bd66247b3c5db9a00a95e29cf4359653aec56f2f9e6827f96898d1509", - "witnesses": 0 - }, - { - "id": "gf20", - "file": "gf20_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "76c7814558901d5633cb16ffead7468583de5577c4ccf0378c296c73ae08acc5", - "witnesses": 0 - }, - { - "id": "gf24", - "file": "gf24_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "983642c7aea54b7e6c5b6e41edcf20828bfc3a1f2707307eaa713ca5a45e612c", - "witnesses": 0 - }, - { - "id": "gf256", - "file": "gf256_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 2021, - "source": "promoted selfconsistent->strict bitexact (dual exact path + separation-bound; bias audit resolved decode-bias=2^96-1 closed form; gf256 promote PR)", - "sha256": "f504258daa4c537ff11a9863814470dd0731ab8cca988093d72e83c221c425f1", - "witnesses": 3 - }, - { - "id": "gf32", - "file": "gf32_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "f7222e2442f2c106e7f3590e5dbe8ed177603fc2324560987af138ae9abeceb4", - "witnesses": 0 - }, - { - "id": "gf4", - "file": "gf4_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 16, - "source": "generated by gen_all_formats.py", - "sha256": "25471b7a0e3dc3633118191e722ced2f450a3ed8a6228ad2492f92084f556f96", - "witnesses": 0 - }, - { - "id": "gf48", - "file": "gf48_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 15, - "source": "wide-rung GoldenFloat oracle promoted to strict bitexact by an independent second decoder (gf_wide_independent_witness.py, dyadic-exact, abs_error=0) + golden Fraction oracle + FP64 RTL bit-model (224255/224255)", - "sha256": "d9928025d21fa0e0f0c02904d9a3e20f5f12a7811b57fa474e8a325ded43e91a", - "witnesses": 3 - }, - { - "id": "gf512", - "file": "gf512_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 15, - "source": "promoted selfconsistent->strict bitexact (dual exact path + separation-bound; gf512 paired PR)", - "sha256": "08d32005ba118c4d0d4a61cb47e074ffd7131a41ca84d4debcac4ebfdfcef9cd", - "witnesses": 3 - }, - { - "id": "gf6", - "file": "gf6_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 64, - "source": "generated by gen_all_formats.py", - "sha256": "9c9fc955db5f6c9b185bdd5d88bd92f3f21a71ad4d784b944330d5cba85fb724", - "witnesses": 0 - }, - { - "id": "gf64", - "file": "gf64_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "887223d0bc8b00d76b70238ddbc8933e3a773ed6a9fbc10264d9fdbebca76cd3", - "witnesses": 0 - }, - { - "id": "gf8", - "file": "gf8_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 256, - "source": "generated by gen_all_formats.py", - "sha256": "6dccbc6628cbc051e06a006a0731499970c1d99e65fc0d42d9007d8f0ed1402d", - "witnesses": 0 - }, - { - "id": "gf8_bfp", - "file": "gf8_bfp_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 256, - "source": "generated by gen_all_formats.py", - "sha256": "fe600234cab0e589b69d84e673d74729cff153f9e4e63e871e285fa82ad2cc70", - "witnesses": 0 - }, - { - "id": "gf96", - "file": "gf96_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 15, - "source": "wide-rung GoldenFloat exact-dyadic pack promoted to strict bitexact by an analytic zero-rounding separation-bound + two structurally independent exact decoders (dyadic gf_wide_independent_witness.py + Fraction oracle gf96_decode_ref.py), 15/15 abs_error=0, 201512-code cross-check", - "sha256": "43127e758d653d26640d38801d42d4daf36fdc70df66a63aadac6a8ce06159fa", - "witnesses": 3 - }, - { - "id": "gf_lns_hybrid", - "file": "gf_lns_hybrid_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "eb7c946281fb6ed6fadd9c63c7e7fa186412480910c9fedcb25fbc056c1bd34a", - "witnesses": 0 - }, - { - "id": "gfternary", - "file": "gfternary_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 4, - "source": "generated by gen_all_formats.py", - "sha256": "9f246d24511fbff6fb9e83e60e1bedfce401052537f7c8929fe205d0f6e57b81", - "witnesses": 0 - }, - { - "id": "ibm_hfp128", - "file": "ibm_hfp128_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "2f02899d621a8a7aebfdf2a69a2484d7616c61ac7cebdc483f643e8109c4e31f", - "witnesses": 0 - }, - { - "id": "ibm_hfp32", - "file": "ibm_hfp32_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 8, - "source": "generated by gen_all_formats.py", - "sha256": "8e35040e30d3a0091ecca5fdb08d1dd1ce98031e5d655239c7196bc667fc3876", - "witnesses": 0 - }, - { - "id": "ibm_hfp64", - "file": "ibm_hfp64_conformance_v0.json", - "kind": "bitexact", - "n_vectors": 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+{ + "schema": "t27-conformance/v0.1", + "format": "BNF1024", + "format_name": "BNF1024", + "bitexact": false, + "format_notes": "BNF1024 -- this work; control for TNF1024; width rule 1+E+M=N; exponent sized for range not phi", + "catalog": { + "id": "bnf1024", + "bits": 1024, + "s": 1, + "e": 18, + "m": 1005, + "bias": 131071, + "storage": "u1024_software", + "cluster": "GoldenFloat", + "status": "Open", + "standard": "this work; control for TNF1024; width rule 1+E+M=N; exponent sized for range not phi", + "use_case": "control isolating the ternary encoding's contribution", + "gf_relation": "self", + "source": "specs/numeric/bnf1024.t27", + "phi_distance": 0.6 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "structural_reason": "No fixed bit-precise round-trip is defined for this entry; recorded structurally with catalog metadata.", + "anchor_note": "Anchor identity phi^2 + 1/phi^2 = 3 recorded per shared schema.", + "n_vectors": 0, + "vectors": [] +} \ No newline at end of file diff --git a/conformance/vectors/bnf128_conformance_v0.json b/conformance/vectors/bnf128_conformance_v0.json new file mode 100644 index 0000000000..9189cb0e26 --- /dev/null +++ b/conformance/vectors/bnf128_conformance_v0.json @@ -0,0 +1,30 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "BNF128", + "format_name": "BNF128", + "bitexact": false, + "format_notes": "BNF128 -- this work; control for TNF128; width rule 1+E+M=N; exponent sized for range not phi", + "catalog": { + "id": "bnf128", + "bits": 128, + "s": 1, + "e": 13, + "m": 114, + "bias": 4095, + "storage": "u128", + "cluster": "GoldenFloat", + "status": "Open", + "standard": "this work; control for TNF128; width rule 1+E+M=N; exponent sized for range not phi", + "use_case": "control isolating the ternary encoding's contribution", + "gf_relation": "self", + "source": "specs/numeric/bnf128.t27", + "phi_distance": 0.504 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "structural_reason": "No fixed bit-precise round-trip is defined for this entry; recorded structurally with catalog metadata.", + "anchor_note": "Anchor identity phi^2 + 1/phi^2 = 3 recorded per shared schema.", + "n_vectors": 0, + "vectors": [] +} \ No newline at end of file diff --git a/conformance/vectors/bnf16_conformance_v0.json b/conformance/vectors/bnf16_conformance_v0.json new file mode 100644 index 0000000000..89de45b825 --- /dev/null +++ b/conformance/vectors/bnf16_conformance_v0.json @@ -0,0 +1,125 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "BNF16", + "format_name": "BNF16", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E7M8, bias 63. IEEE-style specials at top exponent", + "catalog": { + "id": "bnf16", + "bits": 16, + "s": 1, + "e": 7, + "m": 8, + "bias": 63, + "storage": "u16", + "cluster": "GoldenFloat", + "status": "Open", + "standard": "this work; control for TNF16; width rule 1+E+M=N; exponent sized for range not phi", + "use_case": "control isolating the ternary encoding's contribution", + "gf_relation": "self", + "source": "specs/numeric/bnf16.t27", + "phi_distance": 0.257 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": 3.0, + "expected": 3.0, + "ieee754_exact": true, + "bnf16_bits_hex": "0x4080" + }, + "round_trip_policy": "decode: exact bits->f64 (curated_named). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "curated_named", + "n_vectors": 8, + "vectors": [ + { + "name": "pos_zero", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "bnf16_bits_hex": "0x0000", + "bnf16_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + }, + { + "name": "pos_one", + "input_f64": 1.0, + "input_f64_hex": "0x3FF0000000000000", + "bnf16_bits_hex": "0x3F00", + "bnf16_bits_int": 16128, + "decoded_f64": 1.0, + "decoded_f64_hex": "0x3FF0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "neg_one", + "input_f64": -1.0, + "input_f64_hex": "0xBFF0000000000000", + "bnf16_bits_hex": "0xBF00", + "bnf16_bits_int": 48896, + "decoded_f64": -1.0, + "decoded_f64_hex": "0xBFF0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "pos_two", + "input_f64": 2.0, + "input_f64_hex": "0x4000000000000000", + "bnf16_bits_hex": "0x4000", + "bnf16_bits_int": 16384, + "decoded_f64": 2.0, + "decoded_f64_hex": "0x4000000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "pos_three", + "input_f64": 3.0, + "input_f64_hex": "0x4008000000000000", + "bnf16_bits_hex": "0x4080", + "bnf16_bits_int": 16512, + "decoded_f64": 3.0, + "decoded_f64_hex": "0x4008000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "pos_half", + "input_f64": 0.5, + "input_f64_hex": "0x3FE0000000000000", + "bnf16_bits_hex": "0x3E00", + "bnf16_bits_int": 15872, + "decoded_f64": 0.5, + "decoded_f64_hex": "0x3FE0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "pos_four", + "input_f64": 4.0, + "input_f64_hex": "0x4010000000000000", + "bnf16_bits_hex": "0x4100", + "bnf16_bits_int": 16640, + "decoded_f64": 4.0, + "decoded_f64_hex": "0x4010000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "neg_three", + "input_f64": -3.0, + "input_f64_hex": "0xC008000000000000", + "bnf16_bits_hex": "0xC080", + "bnf16_bits_int": 49280, + "decoded_f64": -3.0, + "decoded_f64_hex": "0xC008000000000000", + "abs_error": 0.0, + "category": "normal" + } + ] +} \ No newline at end of file diff --git a/conformance/vectors/bnf256_conformance_v0.json b/conformance/vectors/bnf256_conformance_v0.json new file mode 100644 index 0000000000..7794cbe677 --- /dev/null +++ b/conformance/vectors/bnf256_conformance_v0.json @@ -0,0 +1,30 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "BNF256", + "format_name": "BNF256", + "bitexact": false, + "format_notes": "BNF256 -- this work; control for TNF256; width rule 1+E+M=N; exponent sized for range not phi", + "catalog": { + "id": "bnf256", + "bits": 256, + "s": 1, + "e": 15, + "m": 240, + "bias": 16383, + "storage": "u256_software", + "cluster": "GoldenFloat", + "status": "Open", + "standard": "this work; control for TNF256; width rule 1+E+M=N; exponent sized for range not phi", + "use_case": "control isolating the ternary encoding's contribution", + "gf_relation": "self", + "source": "specs/numeric/bnf256.t27", + "phi_distance": 0.556 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "structural_reason": "No fixed bit-precise round-trip is defined for this entry; recorded structurally with catalog metadata.", + "anchor_note": "Anchor identity phi^2 + 1/phi^2 = 3 recorded per shared schema.", + "n_vectors": 0, + "vectors": [] +} \ No newline at end of file diff --git a/conformance/vectors/bnf32_conformance_v0.json b/conformance/vectors/bnf32_conformance_v0.json new file mode 100644 index 0000000000..6b2e450973 --- /dev/null +++ b/conformance/vectors/bnf32_conformance_v0.json @@ -0,0 +1,125 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "BNF32", + "format_name": "BNF32", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E10M21, bias 511. IEEE-style specials at top exponent", + "catalog": { + "id": "bnf32", + "bits": 32, + "s": 1, + "e": 10, + "m": 21, + "bias": 511, + "storage": "u32", + "cluster": "GoldenFloat", + "status": "Open", + "standard": "this work; control for TNF32; width rule 1+E+M=N; exponent sized for range not phi", + "use_case": "control isolating the ternary encoding's contribution", + "gf_relation": "self", + "source": "specs/numeric/bnf32.t27", + "phi_distance": 0.142 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": 3.0, + "expected": 3.0, + "ieee754_exact": true, + "bnf32_bits_hex": "0x40100000" + }, + "round_trip_policy": "decode: exact bits->f64 (curated_named). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "curated_named", + "n_vectors": 8, + "vectors": [ + { + "name": "pos_zero", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "bnf32_bits_hex": "0x00000000", + "bnf32_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + }, + { + "name": "pos_one", + "input_f64": 1.0, + "input_f64_hex": "0x3FF0000000000000", + "bnf32_bits_hex": "0x3FE00000", + "bnf32_bits_int": 1071644672, + "decoded_f64": 1.0, + "decoded_f64_hex": "0x3FF0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "neg_one", + "input_f64": -1.0, + "input_f64_hex": "0xBFF0000000000000", + "bnf32_bits_hex": "0xBFE00000", + "bnf32_bits_int": 3219128320, + "decoded_f64": -1.0, + "decoded_f64_hex": "0xBFF0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "pos_two", + "input_f64": 2.0, + "input_f64_hex": "0x4000000000000000", + "bnf32_bits_hex": "0x40000000", + "bnf32_bits_int": 1073741824, + "decoded_f64": 2.0, + "decoded_f64_hex": "0x4000000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "pos_three", + "input_f64": 3.0, + "input_f64_hex": "0x4008000000000000", + "bnf32_bits_hex": "0x40100000", + "bnf32_bits_int": 1074790400, + "decoded_f64": 3.0, + "decoded_f64_hex": "0x4008000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "pos_half", + "input_f64": 0.5, + "input_f64_hex": "0x3FE0000000000000", + "bnf32_bits_hex": "0x3FC00000", + "bnf32_bits_int": 1069547520, + "decoded_f64": 0.5, + "decoded_f64_hex": "0x3FE0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "pos_four", + "input_f64": 4.0, + "input_f64_hex": "0x4010000000000000", + "bnf32_bits_hex": "0x40200000", + "bnf32_bits_int": 1075838976, + "decoded_f64": 4.0, + "decoded_f64_hex": "0x4010000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "neg_three", + "input_f64": -3.0, + "input_f64_hex": "0xC008000000000000", + "bnf32_bits_hex": "0xC0100000", + "bnf32_bits_int": 3222274048, + "decoded_f64": -3.0, + "decoded_f64_hex": "0xC008000000000000", + "abs_error": 0.0, + "category": "normal" + } + ] +} \ No newline at end of file diff --git a/conformance/vectors/bnf512_conformance_v0.json b/conformance/vectors/bnf512_conformance_v0.json new file mode 100644 index 0000000000..78095b5c5c --- /dev/null +++ b/conformance/vectors/bnf512_conformance_v0.json @@ -0,0 +1,30 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "BNF512", + "format_name": "BNF512", + "bitexact": false, + "format_notes": "BNF512 -- this work; control for TNF512; width rule 1+E+M=N; exponent sized for range not phi", + "catalog": { + "id": "bnf512", + "bits": 512, + "s": 1, + "e": 16, + "m": 495, + "bias": 32767, + "storage": "u512_software", + "cluster": "GoldenFloat", + "status": "Open", + "standard": "this work; control for TNF512; width rule 1+E+M=N; exponent sized for range not phi", + "use_case": "control isolating the ternary encoding's contribution", + "gf_relation": "self", + "source": "specs/numeric/bnf512.t27", + "phi_distance": 0.586 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "structural_reason": "No fixed bit-precise round-trip is defined for this entry; recorded structurally with catalog metadata.", + "anchor_note": "Anchor identity phi^2 + 1/phi^2 = 3 recorded per shared schema.", + "n_vectors": 0, + "vectors": [] +} \ No newline at end of file diff --git a/conformance/vectors/bnf64_conformance_v0.json b/conformance/vectors/bnf64_conformance_v0.json new file mode 100644 index 0000000000..0705ef2900 --- /dev/null +++ b/conformance/vectors/bnf64_conformance_v0.json @@ -0,0 +1,125 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "BNF64", + "format_name": "BNF64", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E12M51, bias 2047. IEEE-style specials at top exponent", + "catalog": { + "id": "bnf64", + "bits": 64, + "s": 1, + "e": 12, + "m": 51, + "bias": 2047, + "storage": "u64", + "cluster": "GoldenFloat", + "status": "Open", + "standard": "this work; control for TNF64; width rule 1+E+M=N; exponent sized for range not phi", + "use_case": "control isolating the ternary encoding's contribution", + "gf_relation": "self", + "source": "specs/numeric/bnf64.t27", + "phi_distance": 0.383 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": 3.0, + "expected": 3.0, + "ieee754_exact": true, + "bnf64_bits_hex": "0x4004000000000000" + }, + "round_trip_policy": "decode: exact bits->f64 (curated_named). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "curated_named", + "n_vectors": 8, + "vectors": [ + { + "name": "pos_zero", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "bnf64_bits_hex": "0x0000000000000000", + "bnf64_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + }, + { + "name": "pos_one", + "input_f64": 1.0, + "input_f64_hex": "0x3FF0000000000000", + "bnf64_bits_hex": "0x3FF8000000000000", + "bnf64_bits_int": 4609434218613702656, + "decoded_f64": 1.0, + "decoded_f64_hex": "0x3FF0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "neg_one", + "input_f64": -1.0, + "input_f64_hex": "0xBFF0000000000000", + "bnf64_bits_hex": "0xBFF8000000000000", + "bnf64_bits_int": 13832806255468478464, + "decoded_f64": -1.0, + "decoded_f64_hex": "0xBFF0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "pos_two", + "input_f64": 2.0, + "input_f64_hex": "0x4000000000000000", + "bnf64_bits_hex": "0x4000000000000000", + "bnf64_bits_int": 4611686018427387904, + "decoded_f64": 2.0, + "decoded_f64_hex": "0x4000000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "pos_three", + "input_f64": 3.0, + "input_f64_hex": "0x4008000000000000", + "bnf64_bits_hex": "0x4004000000000000", + "bnf64_bits_int": 4612811918334230528, + "decoded_f64": 3.0, + "decoded_f64_hex": "0x4008000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "pos_half", + "input_f64": 0.5, + "input_f64_hex": "0x3FE0000000000000", + "bnf64_bits_hex": "0x3FF0000000000000", + "bnf64_bits_int": 4607182418800017408, + "decoded_f64": 0.5, + "decoded_f64_hex": "0x3FE0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "pos_four", + "input_f64": 4.0, + "input_f64_hex": "0x4010000000000000", + "bnf64_bits_hex": "0x4008000000000000", + "bnf64_bits_int": 4613937818241073152, + "decoded_f64": 4.0, + "decoded_f64_hex": "0x4010000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "neg_three", + "input_f64": -3.0, + "input_f64_hex": "0xC008000000000000", + "bnf64_bits_hex": "0xC004000000000000", + "bnf64_bits_int": 13836183955189006336, + "decoded_f64": -3.0, + "decoded_f64_hex": "0xC008000000000000", + "abs_error": 0.0, + "category": "normal" + } + ] +} \ No newline at end of file diff --git a/conformance/vectors/bnf8_conformance_v0.json b/conformance/vectors/bnf8_conformance_v0.json new file mode 100644 index 0000000000..5a4f89c406 --- /dev/null +++ b/conformance/vectors/bnf8_conformance_v0.json @@ -0,0 +1,2854 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "BNF8", + "format_name": "BNF8", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E5M2, bias 15. IEEE-style specials at top exponent", + "catalog": { + "id": "bnf8", + "bits": 8, + "s": 1, + "e": 5, + "m": 2, + "bias": 15, + "storage": "u8", + "cluster": "GoldenFloat", + "status": "Open", + "standard": "this work; control for TNF8; width rule 1+E+M=N; exponent sized for range not phi", + "use_case": "control isolating the ternary encoding's contribution", + "gf_relation": "self", + "source": "specs/numeric/bnf8.t27", + "phi_distance": 1.882 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": 3.0, + "expected": 3.0, + "ieee754_exact": true, + "bnf8_bits_hex": "0x42" + }, + "round_trip_policy": "decode: exact bits->f64 (exhaustive). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "exhaustive", + "n_vectors": 256, + "max_finite": 57344.0, + "vectors": [ + { + "name": "code_0x00", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "bnf8_bits_hex": "0x00", + "bnf8_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + }, + { + "name": "code_0x01", + "input_f64": 1.52587890625e-05, + "input_f64_hex": "0x3EF0000000000000", + "bnf8_bits_hex": "0x01", + "bnf8_bits_int": 1, + "decoded_f64": 1.52587890625e-05, + "decoded_f64_hex": "0x3EF0000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x02", + "input_f64": 3.0517578125e-05, + "input_f64_hex": "0x3F00000000000000", + "bnf8_bits_hex": "0x02", + "bnf8_bits_int": 2, + "decoded_f64": 3.0517578125e-05, + "decoded_f64_hex": "0x3F00000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x03", + "input_f64": 4.57763671875e-05, + "input_f64_hex": "0x3F08000000000000", + "bnf8_bits_hex": "0x03", + "bnf8_bits_int": 3, + "decoded_f64": 4.57763671875e-05, + "decoded_f64_hex": "0x3F08000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x04", + "input_f64": 6.103515625e-05, + "input_f64_hex": "0x3F10000000000000", + "bnf8_bits_hex": "0x04", + "bnf8_bits_int": 4, + "decoded_f64": 6.103515625e-05, + "decoded_f64_hex": "0x3F10000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x05", + "input_f64": 7.62939453125e-05, + "input_f64_hex": "0x3F14000000000000", + "bnf8_bits_hex": "0x05", + "bnf8_bits_int": 5, + "decoded_f64": 7.62939453125e-05, + "decoded_f64_hex": "0x3F14000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x06", + "input_f64": 9.1552734375e-05, + "input_f64_hex": "0x3F18000000000000", + "bnf8_bits_hex": "0x06", + "bnf8_bits_int": 6, + "decoded_f64": 9.1552734375e-05, + "decoded_f64_hex": "0x3F18000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x07", + "input_f64": 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"0xC0C8000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0xF3", + "input_f64": -14336.0, + "input_f64_hex": "0xC0CC000000000000", + "bnf8_bits_hex": "0xF3", + "bnf8_bits_int": 243, + "decoded_f64": -14336.0, + "decoded_f64_hex": "0xC0CC000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0xF4", + "input_f64": -16384.0, + "input_f64_hex": "0xC0D0000000000000", + "bnf8_bits_hex": "0xF4", + "bnf8_bits_int": 244, + "decoded_f64": -16384.0, + "decoded_f64_hex": "0xC0D0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0xF5", + "input_f64": -20480.0, + "input_f64_hex": "0xC0D4000000000000", + "bnf8_bits_hex": "0xF5", + "bnf8_bits_int": 245, + "decoded_f64": -20480.0, + "decoded_f64_hex": "0xC0D4000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0xF6", + "input_f64": -24576.0, + "input_f64_hex": "0xC0D8000000000000", + "bnf8_bits_hex": "0xF6", + "bnf8_bits_int": 246, + "decoded_f64": -24576.0, + "decoded_f64_hex": "0xC0D8000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0xF7", + "input_f64": -28672.0, + "input_f64_hex": "0xC0DC000000000000", + "bnf8_bits_hex": "0xF7", + "bnf8_bits_int": 247, + "decoded_f64": -28672.0, + "decoded_f64_hex": "0xC0DC000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0xF8", + "input_f64": -32768.0, + "input_f64_hex": "0xC0E0000000000000", + "bnf8_bits_hex": "0xF8", + "bnf8_bits_int": 248, + "decoded_f64": -32768.0, + "decoded_f64_hex": "0xC0E0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0xF9", + "input_f64": -40960.0, + "input_f64_hex": "0xC0E4000000000000", + "bnf8_bits_hex": "0xF9", + "bnf8_bits_int": 249, + "decoded_f64": -40960.0, + "decoded_f64_hex": "0xC0E4000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0xFA", + "input_f64": -49152.0, + "input_f64_hex": "0xC0E8000000000000", + "bnf8_bits_hex": "0xFA", + "bnf8_bits_int": 250, + "decoded_f64": -49152.0, + "decoded_f64_hex": "0xC0E8000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0xFB", + "input_f64": -57344.0, + "input_f64_hex": "0xC0EC000000000000", + "bnf8_bits_hex": "0xFB", + "bnf8_bits_int": 251, + "decoded_f64": -57344.0, + "decoded_f64_hex": "0xC0EC000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0xFC", + "input_f64": "-Inf", + "input_f64_hex": "0xFFF0000000000000", + "bnf8_bits_hex": "0xFC", + "bnf8_bits_int": 252, + "decoded_f64": "-Inf", + "decoded_f64_hex": "0xFFF0000000000000", + "abs_error": 0.0, + "category": "inf" + }, + { + "name": "code_0xFD", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "bnf8_bits_hex": "0xFD", + "bnf8_bits_int": 253, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFE", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "bnf8_bits_hex": "0xFE", + "bnf8_bits_int": 254, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFF", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "bnf8_bits_hex": "0xFF", + "bnf8_bits_int": 255, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + } + ] +} \ No newline at end of file diff --git a/conformance/vectors/gft1024_conformance_v0.json b/conformance/vectors/gft1024_conformance_v0.json new file mode 100644 index 0000000000..fda941ddaf --- /dev/null +++ b/conformance/vectors/gft1024_conformance_v0.json @@ -0,0 +1,30 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "GFT1024", + "format_name": "GF-T1024", + "bitexact": false, + "format_notes": "GF-T1024 -- this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6187 against 1/phi = 0.6180", + "catalog": { + "id": "gft1024", + "bits": 1024, + "s": 1, + "e": 391, + "m": 632, + "bias": 1792175763007502050309004510896072657026569872803620275437464390826146561794008386845991427359831686179824019072939996745082807322862992600064651843076138216429413334444960452990989263173, + "storage": "u1024_software", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6187 against 1/phi = 0.6180", + "use_case": "phi-derived ternary ladder; huge range at the cost of mantissa", + "gf_relation": "self", + "source": "specs/numeric/gft1024.t27", + "phi_distance": 0.0006 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "structural_reason": "No fixed bit-precise round-trip is defined for this entry; recorded structurally with catalog metadata.", + "anchor_note": "Anchor identity phi^2 + 1/phi^2 = 3 recorded per shared schema.", + "n_vectors": 0, + "vectors": [] +} \ No newline at end of file diff --git a/conformance/vectors/gft128_conformance_v0.json b/conformance/vectors/gft128_conformance_v0.json new file mode 100644 index 0000000000..97f0af7199 --- /dev/null +++ b/conformance/vectors/gft128_conformance_v0.json @@ -0,0 +1,30 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "GFT128", + "format_name": "GF-T128", + "bitexact": false, + "format_notes": "GF-T128 -- this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6282 against 1/phi = 0.6180", + "catalog": { + "id": "gft128", + "bits": 128, + "s": 1, + "e": 49, + "m": 78, + "bias": 119649664615308764795041, + "storage": "u128", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6282 against 1/phi = 0.6180", + "use_case": "phi-derived ternary ladder; huge range at the cost of mantissa", + "gf_relation": "self", + "source": "specs/numeric/gft128.t27", + "phi_distance": 0.0102 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "structural_reason": "No fixed bit-precise round-trip is defined for this entry; recorded structurally with catalog metadata.", + "anchor_note": "Anchor identity phi^2 + 1/phi^2 = 3 recorded per shared schema.", + "n_vectors": 0, + "vectors": [] +} \ No newline at end of file diff --git a/conformance/vectors/gft16_conformance_v0.json b/conformance/vectors/gft16_conformance_v0.json new file mode 100644 index 0000000000..9ddd2e2dca --- /dev/null +++ b/conformance/vectors/gft16_conformance_v0.json @@ -0,0 +1,48 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "GFT16", + "format_name": "GF-T16", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E6M9, bias 364. IEEE-style specials at top exponent", + "catalog": { + "id": "gft16", + "bits": 16, + "s": 1, + "e": 6, + "m": 9, + "bias": 364, + "storage": "u16", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6667 against 1/phi = 0.6180", + "use_case": "phi-derived ternary ladder; huge range at the cost of mantissa", + "gf_relation": "self", + "source": "specs/numeric/gft16.t27", + "phi_distance": 0.0486 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": null, + "expected": 3.0, + "ieee754_exact": false, + "note": "3.0 is not an exact grid point of this format at this width" + }, + "round_trip_policy": "decode: exact bits->f64 (curated_named). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "curated_named", + "n_vectors": 1, + "vectors": [ + { + "name": "pos_zero", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "gft16_bits_hex": "0x0000", + "gft16_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + } + ] +} \ No newline at end of file diff --git a/conformance/vectors/gft256_conformance_v0.json b/conformance/vectors/gft256_conformance_v0.json new file mode 100644 index 0000000000..3b57333dac --- /dev/null +++ b/conformance/vectors/gft256_conformance_v0.json @@ -0,0 +1,30 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "GFT256", + "format_name": "GF-T256", + "bitexact": false, + "format_notes": "GF-T256 -- this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6139 against 1/phi = 0.6180", + "catalog": { + "id": "gft256", + "bits": 256, + "s": 1, + "e": 97, + "m": 158, + "bias": 9544028161703913537712243143807801346335324481, + "storage": "u256_software", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6139 against 1/phi = 0.6180", + "use_case": "phi-derived ternary ladder; huge range at the cost of mantissa", + "gf_relation": "self", + "source": "specs/numeric/gft256.t27", + "phi_distance": 0.0041 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "structural_reason": "No fixed bit-precise round-trip is defined for this entry; recorded structurally with catalog metadata.", + "anchor_note": "Anchor identity phi^2 + 1/phi^2 = 3 recorded per shared schema.", + "n_vectors": 0, + "vectors": [] +} \ No newline at end of file diff --git a/conformance/vectors/gft32_conformance_v0.json b/conformance/vectors/gft32_conformance_v0.json new file mode 100644 index 0000000000..835847ce1a --- /dev/null +++ b/conformance/vectors/gft32_conformance_v0.json @@ -0,0 +1,48 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "GFT32", + "format_name": "GF-T32", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E12M19, bias 265720. IEEE-style specials at top exponent", + "catalog": { + "id": "gft32", + "bits": 32, + "s": 1, + "e": 12, + "m": 19, + "bias": 265720, + "storage": "u32", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6316 against 1/phi = 0.6180", + "use_case": "phi-derived ternary ladder; huge range at the cost of mantissa", + "gf_relation": "self", + "source": "specs/numeric/gft32.t27", + "phi_distance": 0.0135 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": null, + "expected": 3.0, + "ieee754_exact": false, + "note": "3.0 is not an exact grid point of this format at this width" + }, + "round_trip_policy": "decode: exact bits->f64 (curated_named). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "curated_named", + "n_vectors": 1, + "vectors": [ + { + "name": "pos_zero", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "gft32_bits_hex": "0x00000000", + "gft32_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + } + ] +} \ No newline at end of file diff --git a/conformance/vectors/gft4_conformance_v0.json b/conformance/vectors/gft4_conformance_v0.json new file mode 100644 index 0000000000..8fa3e2b818 --- /dev/null +++ b/conformance/vectors/gft4_conformance_v0.json @@ -0,0 +1,214 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "GFT4", + "format_name": "GF-T4", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E1M2, bias 1. IEEE-style specials at top exponent", + "catalog": { + "id": "gft4", + "bits": 4, + "s": 1, + "e": 1, + "m": 2, + "bias": 1, + "storage": "u4", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.5000 against 1/phi = 0.6180", + "use_case": "phi-derived ternary ladder; huge range at the cost of mantissa", + "gf_relation": "self", + "source": "specs/numeric/gft4.t27", + "phi_distance": 0.118 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": null, + "expected": 3.0, + "ieee754_exact": false, + "note": "3.0 is not an exact grid point of this format at this width" + }, + "round_trip_policy": "decode: exact bits->f64 (exhaustive). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "exhaustive", + "n_vectors": 16, + "max_finite": 0.75, + "vectors": [ + { + "name": "code_0x00", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "gft4_bits_hex": "0x0", + "gft4_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + }, + { + "name": "code_0x01", + "input_f64": 0.25, + "input_f64_hex": "0x3FD0000000000000", + "gft4_bits_hex": "0x1", + "gft4_bits_int": 1, + "decoded_f64": 0.25, + "decoded_f64_hex": "0x3FD0000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x02", + "input_f64": 0.5, + "input_f64_hex": "0x3FE0000000000000", + "gft4_bits_hex": "0x2", + "gft4_bits_int": 2, + "decoded_f64": 0.5, + "decoded_f64_hex": "0x3FE0000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x03", + "input_f64": 0.75, + "input_f64_hex": "0x3FE8000000000000", + "gft4_bits_hex": "0x3", + "gft4_bits_int": 3, + "decoded_f64": 0.75, + "decoded_f64_hex": "0x3FE8000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x04", + "input_f64": "Inf", + "input_f64_hex": "0x7FF0000000000000", + "gft4_bits_hex": "0x4", + "gft4_bits_int": 4, + "decoded_f64": "Inf", + "decoded_f64_hex": "0x7FF0000000000000", + "abs_error": 0.0, + "category": "inf" + }, + { + "name": "code_0x05", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "gft4_bits_hex": "0x5", + "gft4_bits_int": 5, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0x06", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "gft4_bits_hex": "0x6", + "gft4_bits_int": 6, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0x07", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "gft4_bits_hex": "0x7", + "gft4_bits_int": 7, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0x08", + "input_f64": -0.0, + "input_f64_hex": "0x8000000000000000", + "gft4_bits_hex": "0x8", + "gft4_bits_int": 8, + "decoded_f64": -0.0, + "decoded_f64_hex": "0x8000000000000000", + "abs_error": 0.0, + "category": "zero" + }, + { + "name": "code_0x09", + "input_f64": -0.25, + "input_f64_hex": "0xBFD0000000000000", + "gft4_bits_hex": "0x9", + "gft4_bits_int": 9, + "decoded_f64": -0.25, + "decoded_f64_hex": "0xBFD0000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0A", + "input_f64": -0.5, + "input_f64_hex": "0xBFE0000000000000", + "gft4_bits_hex": "0xA", + "gft4_bits_int": 10, + "decoded_f64": -0.5, + "decoded_f64_hex": "0xBFE0000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0B", + "input_f64": -0.75, + "input_f64_hex": "0xBFE8000000000000", + "gft4_bits_hex": "0xB", + "gft4_bits_int": 11, + "decoded_f64": -0.75, + "decoded_f64_hex": "0xBFE8000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0C", + "input_f64": "-Inf", + "input_f64_hex": "0xFFF0000000000000", + "gft4_bits_hex": "0xC", + "gft4_bits_int": 12, + "decoded_f64": "-Inf", + "decoded_f64_hex": "0xFFF0000000000000", + "abs_error": 0.0, + "category": "inf" + }, + { + "name": "code_0x0D", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "gft4_bits_hex": "0xD", + "gft4_bits_int": 13, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0x0E", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "gft4_bits_hex": "0xE", + "gft4_bits_int": 14, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0x0F", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "gft4_bits_hex": "0xF", + "gft4_bits_int": 15, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + } + ] +} \ No newline at end of file diff --git a/conformance/vectors/gft512_conformance_v0.json b/conformance/vectors/gft512_conformance_v0.json new file mode 100644 index 0000000000..0be4240ae5 --- /dev/null +++ b/conformance/vectors/gft512_conformance_v0.json @@ -0,0 +1,30 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "GFT512", + "format_name": "GF-T512", + "bitexact": false, + "format_notes": "GF-T512 -- this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6171 against 1/phi = 0.6180", + "catalog": { + "id": "gft512", + "bits": 512, + "s": 1, + "e": 195, + "m": 316, + "bias": 546530841308384299050990374559217339154801342908219127519701567364387841360704080235359463053, + "storage": "u512_software", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6171 against 1/phi = 0.6180", + "use_case": "phi-derived ternary ladder; huge range at the cost of mantissa", + "gf_relation": "self", + "source": "specs/numeric/gft512.t27", + "phi_distance": 0.0009 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "structural_reason": "No fixed bit-precise round-trip is defined for this entry; recorded structurally with catalog metadata.", + "anchor_note": "Anchor identity phi^2 + 1/phi^2 = 3 recorded per shared schema.", + "n_vectors": 0, + "vectors": [] +} \ No newline at end of file diff --git a/conformance/vectors/gft64_conformance_v0.json b/conformance/vectors/gft64_conformance_v0.json new file mode 100644 index 0000000000..ab8c44751f --- /dev/null +++ b/conformance/vectors/gft64_conformance_v0.json @@ -0,0 +1,48 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "GFT64", + "format_name": "GF-T64", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E24M39, bias 141214768240. IEEE-style specials at top exponent", + "catalog": { + "id": "gft64", + "bits": 64, + "s": 1, + "e": 24, + "m": 39, + "bias": 141214768240, + "storage": "u64", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.6154 against 1/phi = 0.6180", + "use_case": "phi-derived ternary ladder; huge range at the cost of mantissa", + "gf_relation": "self", + "source": "specs/numeric/gft64.t27", + "phi_distance": 0.0026 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": null, + "expected": 3.0, + "ieee754_exact": false, + "note": "3.0 is not an exact grid point of this format at this width" + }, + "round_trip_policy": "decode: exact bits->f64 (curated_named). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "curated_named", + "n_vectors": 1, + "vectors": [ + { + "name": "pos_zero", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "gft64_bits_hex": "0x0000000000000000", + "gft64_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + } + ] +} \ No newline at end of file diff --git a/conformance/vectors/gft8_conformance_v0.json b/conformance/vectors/gft8_conformance_v0.json new file mode 100644 index 0000000000..a25c0de1c9 --- /dev/null +++ b/conformance/vectors/gft8_conformance_v0.json @@ -0,0 +1,2854 @@ +{ + "schema": "t27-conformance/v0.1", + "format": "GFT8", + "format_name": "GF-T8", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E3M4, bias 13. IEEE-style specials at top exponent", + "catalog": { + "id": "gft8", + "bits": 8, + "s": 1, + "e": 3, + "m": 4, + "bias": 13, + "storage": "u8", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; GOLDEN RATIO axis: E_t = round((N-1)/phi^2), a trit is a position; every position spent; E_t/M = 0.7500 against 1/phi = 0.6180", + "use_case": "phi-derived ternary ladder; huge range at the cost of mantissa", + "gf_relation": "self", + "source": "specs/numeric/gft8.t27", + "phi_distance": 0.132 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": null, + "expected": 3.0, + "ieee754_exact": false, + "note": "3.0 is not an exact grid point of this format at this width" + }, + "round_trip_policy": "decode: exact bits->f64 (exhaustive). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "exhaustive", + "n_vectors": 256, + "max_finite": 0.01513671875, + "vectors": [ + { + "name": "code_0x00", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "gft8_bits_hex": "0x00", + "gft8_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + }, + { + "name": "code_0x01", + "input_f64": 1.52587890625e-05, + "input_f64_hex": "0x3EF0000000000000", + "gft8_bits_hex": "0x01", + "gft8_bits_int": 1, + "decoded_f64": 1.52587890625e-05, + "decoded_f64_hex": "0x3EF0000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x02", + "input_f64": 3.0517578125e-05, + "input_f64_hex": "0x3F00000000000000", + "gft8_bits_hex": "0x02", + "gft8_bits_int": 2, + "decoded_f64": 3.0517578125e-05, + "decoded_f64_hex": "0x3F00000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x03", + "input_f64": 4.57763671875e-05, + "input_f64_hex": "0x3F08000000000000", + "gft8_bits_hex": "0x03", + "gft8_bits_int": 3, + "decoded_f64": 4.57763671875e-05, + "decoded_f64_hex": "0x3F08000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x04", + "input_f64": 6.103515625e-05, + "input_f64_hex": "0x3F10000000000000", + "gft8_bits_hex": "0x04", + "gft8_bits_int": 4, + "decoded_f64": 6.103515625e-05, + "decoded_f64_hex": "0x3F10000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x05", + "input_f64": 7.62939453125e-05, + "input_f64_hex": "0x3F14000000000000", + "gft8_bits_hex": "0x05", + "gft8_bits_int": 5, + "decoded_f64": 7.62939453125e-05, + "decoded_f64_hex": "0x3F14000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x06", + "input_f64": 9.1552734375e-05, + "input_f64_hex": "0x3F18000000000000", + "gft8_bits_hex": "0x06", + "gft8_bits_int": 6, + "decoded_f64": 9.1552734375e-05, + "decoded_f64_hex": "0x3F18000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x07", + "input_f64": 0.0001068115234375, + "input_f64_hex": "0x3F1C000000000000", + "gft8_bits_hex": "0x07", + "gft8_bits_int": 7, + "decoded_f64": 0.0001068115234375, + "decoded_f64_hex": "0x3F1C000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x08", + "input_f64": 0.0001220703125, + "input_f64_hex": "0x3F20000000000000", + "gft8_bits_hex": "0x08", + "gft8_bits_int": 8, + "decoded_f64": 0.0001220703125, + "decoded_f64_hex": "0x3F20000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x09", + "input_f64": 0.0001373291015625, + "input_f64_hex": "0x3F22000000000000", + "gft8_bits_hex": "0x09", + "gft8_bits_int": 9, + "decoded_f64": 0.0001373291015625, + "decoded_f64_hex": "0x3F22000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0A", + "input_f64": 0.000152587890625, + "input_f64_hex": "0x3F24000000000000", + "gft8_bits_hex": "0x0A", + "gft8_bits_int": 10, + "decoded_f64": 0.000152587890625, + "decoded_f64_hex": "0x3F24000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0B", + "input_f64": 0.0001678466796875, + "input_f64_hex": "0x3F26000000000000", + "gft8_bits_hex": "0x0B", + "gft8_bits_int": 11, + "decoded_f64": 0.0001678466796875, + "decoded_f64_hex": "0x3F26000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0C", + "input_f64": 0.00018310546875, + "input_f64_hex": "0x3F28000000000000", + "gft8_bits_hex": "0x0C", + "gft8_bits_int": 12, + "decoded_f64": 0.00018310546875, + "decoded_f64_hex": "0x3F28000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0D", + "input_f64": 0.0001983642578125, + "input_f64_hex": "0x3F2A000000000000", + "gft8_bits_hex": "0x0D", + "gft8_bits_int": 13, + "decoded_f64": 0.0001983642578125, + "decoded_f64_hex": "0x3F2A000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0E", + "input_f64": 0.000213623046875, + "input_f64_hex": "0x3F2C000000000000", + "gft8_bits_hex": "0x0E", + "gft8_bits_int": 14, + "decoded_f64": 0.000213623046875, + "decoded_f64_hex": "0x3F2C000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0F", + "input_f64": 0.0002288818359375, + "input_f64_hex": "0x3F2E000000000000", + "gft8_bits_hex": "0x0F", + "gft8_bits_int": 15, + "decoded_f64": 0.0002288818359375, + "decoded_f64_hex": "0x3F2E000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x10", + "input_f64": 0.000244140625, + "input_f64_hex": "0x3F30000000000000", + "gft8_bits_hex": "0x10", + "gft8_bits_int": 16, + "decoded_f64": 0.000244140625, + "decoded_f64_hex": "0x3F30000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x11", + "input_f64": 0.0002593994140625, + "input_f64_hex": "0x3F31000000000000", + "gft8_bits_hex": "0x11", + "gft8_bits_int": 17, + "decoded_f64": 0.0002593994140625, + "decoded_f64_hex": "0x3F31000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x12", + "input_f64": 0.000274658203125, + "input_f64_hex": "0x3F32000000000000", + "gft8_bits_hex": "0x12", + "gft8_bits_int": 18, + "decoded_f64": 0.000274658203125, + "decoded_f64_hex": "0x3F32000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x13", + "input_f64": 0.0002899169921875, + "input_f64_hex": "0x3F33000000000000", + "gft8_bits_hex": "0x13", + "gft8_bits_int": 19, + "decoded_f64": 0.0002899169921875, + "decoded_f64_hex": "0x3F33000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x14", + "input_f64": 0.00030517578125, + "input_f64_hex": "0x3F34000000000000", + "gft8_bits_hex": "0x14", + "gft8_bits_int": 20, + "decoded_f64": 0.00030517578125, + "decoded_f64_hex": "0x3F34000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x15", + "input_f64": 0.0003204345703125, + "input_f64_hex": "0x3F35000000000000", + "gft8_bits_hex": "0x15", + "gft8_bits_int": 21, + "decoded_f64": 0.0003204345703125, + "decoded_f64_hex": "0x3F35000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x16", + "input_f64": 0.000335693359375, + "input_f64_hex": "0x3F36000000000000", + "gft8_bits_hex": "0x16", + "gft8_bits_int": 22, + "decoded_f64": 0.000335693359375, + "decoded_f64_hex": "0x3F36000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x17", + "input_f64": 0.0003509521484375, + "input_f64_hex": "0x3F37000000000000", + "gft8_bits_hex": "0x17", + "gft8_bits_int": 23, + "decoded_f64": 0.0003509521484375, + "decoded_f64_hex": "0x3F37000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x18", + "input_f64": 0.0003662109375, + "input_f64_hex": "0x3F38000000000000", + "gft8_bits_hex": "0x18", + "gft8_bits_int": 24, + "decoded_f64": 0.0003662109375, + "decoded_f64_hex": "0x3F38000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x19", + "input_f64": 0.0003814697265625, + "input_f64_hex": "0x3F39000000000000", + "gft8_bits_hex": "0x19", + "gft8_bits_int": 25, + "decoded_f64": 0.0003814697265625, + "decoded_f64_hex": "0x3F39000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x1A", + "input_f64": 0.000396728515625, + "input_f64_hex": "0x3F3A000000000000", + "gft8_bits_hex": "0x1A", + "gft8_bits_int": 26, + "decoded_f64": 0.000396728515625, + "decoded_f64_hex": "0x3F3A000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x1B", + "input_f64": 0.0004119873046875, + "input_f64_hex": "0x3F3B000000000000", + "gft8_bits_hex": "0x1B", + "gft8_bits_int": 27, + "decoded_f64": 0.0004119873046875, + "decoded_f64_hex": "0x3F3B000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x1C", + "input_f64": 0.00042724609375, + "input_f64_hex": "0x3F3C000000000000", + "gft8_bits_hex": "0x1C", + "gft8_bits_int": 28, + "decoded_f64": 0.00042724609375, + "decoded_f64_hex": "0x3F3C000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x1D", + "input_f64": 0.0004425048828125, + "input_f64_hex": "0x3F3D000000000000", + "gft8_bits_hex": "0x1D", + "gft8_bits_int": 29, + "decoded_f64": 0.0004425048828125, + "decoded_f64_hex": "0x3F3D000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x1E", + "input_f64": 0.000457763671875, + "input_f64_hex": "0x3F3E000000000000", + "gft8_bits_hex": "0x1E", + "gft8_bits_int": 30, + "decoded_f64": 0.000457763671875, + "decoded_f64_hex": "0x3F3E000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x1F", + "input_f64": 0.0004730224609375, + "input_f64_hex": "0x3F3F000000000000", + "gft8_bits_hex": "0x1F", + "gft8_bits_int": 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"abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFA", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "gft8_bits_hex": "0xFA", + "gft8_bits_int": 250, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFB", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "gft8_bits_hex": "0xFB", + "gft8_bits_int": 251, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFC", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "gft8_bits_hex": "0xFC", + "gft8_bits_int": 252, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFD", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "gft8_bits_hex": "0xFD", + "gft8_bits_int": 253, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFE", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "gft8_bits_hex": "0xFE", + "gft8_bits_int": 254, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFF", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "gft8_bits_hex": "0xFF", + "gft8_bits_int": 255, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + } + ] +} \ No newline at end of file diff --git a/conformance/vectors/tnf1024_conformance_v0.json b/conformance/vectors/tnf1024_conformance_v0.json index c2f49950cc..8899082960 100644 --- a/conformance/vectors/tnf1024_conformance_v0.json +++ b/conformance/vectors/tnf1024_conformance_v0.json @@ -1,262 +1,30 @@ { - "schema": "t27-conformance/v0.1", - "format": "TNF1024", - "ssot": "specs/numeric/tnf1024.t27", - "anchor_identity": "phi^2 + 1/phi^2 = 3", - "anchor_check": { - "value": 3.0, - "expected": 3.0, - "ieee754_exact": true - }, - "exp_trits": 11, - "mant_bits": 1012, - "exp_offset": 88573, - "offset_max": 177146, - "width_rule": "1 + 11 + 1012 = 1024", - "note": "probes are exactly representable in both the rung and f64 (powers of two and 1.5*2^e within range), so every abs_error is exactly zero by construction", - "n_vectors": 22, - "vectors": [ - { - "name": "pos_zero", - "input_f64": 0.0, - "input_f64_hex": "0x0000000000000000", - "tnf1024_bits_int": 0, - "tnf1024_bits_hex": "0x0", - "decoded_f64": 0.0, - "decoded_f64_hex": "0x0000000000000000", - "abs_error": 0.0, - "category": "zero" - }, - { - "name": "pow2_-1000", - "input_f64": 9.332636185032189e-302, - "input_f64_hex": "0x0170000000000000", - "tnf1024_bits_int": 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3887445570650932626200423403846251739937634324251106775553084161012107639925377211669454839988668530103199103235514826894030389252405406525632986998334008991625635321328307599024861071794573282124877220688343101433582709378208612913845487502343384306182907668123019793323781087738738191367831852836499228721152, - "tnf1024_bits_hex": "0x159fe8000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 3.0, - "decoded_f64_hex": "0x4008000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_500", - "input_f64": 3.273390607896142e+150, - "input_f64_hex": "0x5f30000000000000", - "tnf1024_bits_int": 3909324233437281856669248077615986330506691002083204915848690824942070955083834787382749560678419544924128882720162260875669282489650032181471044723962372724780497942146739104007829005503367515015147572702897392296806786066477098691778775023242945433557402353078162925568071542353077092387841722253080692523008, - "tnf1024_bits_hex": "0x15bf10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 3.273390607896142e+150, - "decoded_f64_hex": "0x5f30000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_500", - "input_f64": -3.273390607896142e+150, - "input_f64_hex": "0xdf30000000000000", - "tnf1024_bits_int": 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3931268729712456611402271822620735167586988572626934244129138832895895744610873479171410263476564996098582021621513749322649115225101010773083941138835355405978955936949579129065971366294535251113713622867946831477573161882192731367739946057244511258406444163464464963927440102648301667132084319461286774571008, - "tnf1024_bits_hex": "0x15de50000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 1.0715086071862673e+301, - "decoded_f64_hex": "0x7e70000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_1000", - "input_f64": -1.0715086071862673e+301, - "input_f64_hex": "0xfe70000000000000", - "tnf1024_bits_int": 15436504792831278420869825043670493462742041237857696309628664026990786996162935119664752812110647301450269309933282924212811660429223674612626176699761699366156101116140970186749313420774285274758710931801387200683214805552110355782070385131857454436860876847277988051284063842711003510641547124557237119352832, - "tnf1024_bits_hex": "0x55de50000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": -1.0715086071862673e+301, - "decoded_f64_hex": "0xfe70000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e1000", - "input_f64": 1.607262910779401e+301, - "input_f64_hex": "0x7e78000000000000", - "tnf1024_bits_int": 3931290674208731786157004846365739916424068870197477973457419280903849569400400517863198924179363141549756474760415100811096095057836461751675554035250228388660154394944381969091029508655326418849812188918111880916753928258008447000415907228278512824231293205274851265965799471208596891706828562058494980653056, - "tnf1024_bits_hex": "0x15de58000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 1.607262910779401e+301, - "decoded_f64_hex": "0x7e78000000000000", - "abs_error": 0.0, - "category": "normal" - } - ] -} + "schema": "t27-conformance/v0.1", + "format": "TNF1024", + "format_name": "TNF1024", + "bitexact": false, + "format_notes": "TNF1024 -- this work; e is 11 balanced-ternary TRITS not bits (17.43 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised", + "catalog": { + "id": "tnf1024", + "bits": 1024, + "s": 1, + "e": 11, + "m": 1012, + "bias": 88573, + "storage": "u1024_software", + "cluster": "GoldenFloat", + "status": "Open", + "standard": "this work; e is 11 balanced-ternary TRITS not bits (17.43 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised", + "use_case": "fixed-field ternary-exponent ladder; no regime codec", + "gf_relation": "self", + "source": "specs/numeric/tnf1024.t27", + "phi_distance": 0.601 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "structural_reason": "No fixed bit-precise round-trip is defined for this entry; recorded structurally with catalog metadata.", + "anchor_note": "Anchor identity phi^2 + 1/phi^2 = 3 recorded per shared schema.", + "n_vectors": 0, + "vectors": [] +} \ No newline at end of file diff --git a/conformance/vectors/tnf128_conformance_v0.json b/conformance/vectors/tnf128_conformance_v0.json index 8bfcf1a72f..eaed5d8185 100644 --- a/conformance/vectors/tnf128_conformance_v0.json +++ b/conformance/vectors/tnf128_conformance_v0.json @@ -1,262 +1,30 @@ { - "schema": "t27-conformance/v0.1", - "format": "TNF128", - "ssot": "specs/numeric/tnf128.t27", - "anchor_identity": "phi^2 + 1/phi^2 = 3", - "anchor_check": { - "value": 3.0, - "expected": 3.0, - "ieee754_exact": true - }, - "exp_trits": 8, - "mant_bits": 119, - "exp_offset": 3280, - "offset_max": 6560, - "width_rule": "1 + 8 + 119 = 128", - "note": "probes are exactly representable in both the rung and f64 (powers of two and 1.5*2^e within range), so every abs_error is exactly zero by construction", - "n_vectors": 22, - "vectors": [ - { - "name": "pos_zero", - "input_f64": 0.0, - "input_f64_hex": "0x0000000000000000", - "tnf128_bits_int": 0, - "tnf128_bits_hex": "0x0", - "decoded_f64": 0.0, - "decoded_f64_hex": "0x0000000000000000", - "abs_error": 0.0, - "category": "zero" - }, - { - "name": "pow2_-1000", - "input_f64": 9.332636185032189e-302, - "input_f64_hex": "0x0170000000000000", - "tnf128_bits_int": 1515319915194804095110340048719592816640, - "tnf128_bits_hex": "0x474000000000000000000000000000000", - "decoded_f64": 9.332636185032189e-302, - "decoded_f64_hex": "0x0170000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-1000", - "input_f64": -9.332636185032189e-302, - "input_f64_hex": "0x8170000000000000", - "tnf128_bits_int": 6959837785929819510524333767627884199936, - "tnf128_bits_hex": "0x1474000000000000000000000000000000", - "decoded_f64": -9.332636185032189e-302, - "decoded_f64_hex": "0x8170000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-1000", - "input_f64": 1.3998954277548283e-301, - "input_f64_hex": "0x0178000000000000", - "tnf128_bits_int": 1515652222193750324078566000484662902784, - "tnf128_bits_hex": "0x474400000000000000000000000000000", - "decoded_f64": 1.3998954277548283e-301, - "decoded_f64_hex": "0x0178000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_-500", - "input_f64": 3.054936363499605e-151, - "input_f64_hex": "0x20b0000000000000", - "tnf128_bits_int": 1847626914141033063336291813789678960640, - "tnf128_bits_hex": "0x56e000000000000000000000000000000", - "decoded_f64": 3.054936363499605e-151, - "decoded_f64_hex": "0x20b0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-500", - "input_f64": -3.054936363499605e-151, - "input_f64_hex": "0xa0b0000000000000", - "tnf128_bits_int": 7292144784876048478750285532697970343936, - "tnf128_bits_hex": "0x156e000000000000000000000000000000", - "decoded_f64": -3.054936363499605e-151, - "decoded_f64_hex": "0xa0b0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-500", - "input_f64": 4.582404545249407e-151, - "input_f64_hex": "0x20b8000000000000", - "tnf128_bits_int": 1847959221139979292304517765554749046784, - "tnf128_bits_hex": "0x56e400000000000000000000000000000", - "decoded_f64": 4.582404545249407e-151, - "decoded_f64_hex": "0x20b8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_-1", - "input_f64": 0.5, - "input_f64_hex": "0x3fe0000000000000", - "tnf128_bits_int": 2179269299089369573625791675329624932352, - "tnf128_bits_hex": "0x667800000000000000000000000000000", - "decoded_f64": 0.5, - "decoded_f64_hex": "0x3fe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-1", - "input_f64": -0.5, - "input_f64_hex": "0xbfe0000000000000", - "tnf128_bits_int": 7623787169824384989039785394237916315648, - "tnf128_bits_hex": "0x1667800000000000000000000000000000", - "decoded_f64": -0.5, - "decoded_f64_hex": "0xbfe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-1", - "input_f64": 0.75, - "input_f64_hex": "0x3fe8000000000000", - "tnf128_bits_int": 2179601606088315802594017627094695018496, - "tnf128_bits_hex": "0x667c00000000000000000000000000000", - "decoded_f64": 0.75, - "decoded_f64_hex": "0x3fe8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_0", - "input_f64": 1.0, - "input_f64_hex": "0x3ff0000000000000", - "tnf128_bits_int": 2179933913087262031562243578859765104640, - "tnf128_bits_hex": "0x668000000000000000000000000000000", - "decoded_f64": 1.0, - "decoded_f64_hex": "0x3ff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "neg_pow2_0", - "input_f64": -1.0, - "input_f64_hex": "0xbff0000000000000", - "tnf128_bits_int": 7624451783822277446976237297768056487936, - "tnf128_bits_hex": "0x1668000000000000000000000000000000", - "decoded_f64": -1.0, - "decoded_f64_hex": "0xbff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "onehalf_2e0", - "input_f64": 1.5, - "input_f64_hex": "0x3ff8000000000000", - "tnf128_bits_int": 2180266220086208260530469530624835190784, - "tnf128_bits_hex": "0x668400000000000000000000000000000", - "decoded_f64": 1.5, - "decoded_f64_hex": "0x3ff8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_1", - "input_f64": 2.0, - "input_f64_hex": "0x4000000000000000", - "tnf128_bits_int": 2180598527085154489498695482389905276928, - "tnf128_bits_hex": "0x668800000000000000000000000000000", - "decoded_f64": 2.0, - "decoded_f64_hex": "0x4000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_1", - "input_f64": -2.0, - "input_f64_hex": "0xc000000000000000", - "tnf128_bits_int": 7625116397820169904912689201298196660224, - "tnf128_bits_hex": "0x1668800000000000000000000000000000", - "decoded_f64": -2.0, - "decoded_f64_hex": "0xc000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e1", - "input_f64": 3.0, - "input_f64_hex": "0x4008000000000000", - "tnf128_bits_int": 2180930834084100718466921434154975363072, - "tnf128_bits_hex": "0x668c00000000000000000000000000000", - "decoded_f64": 3.0, - "decoded_f64_hex": "0x4008000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_500", - "input_f64": 3.273390607896142e+150, - "input_f64_hex": "0x5f30000000000000", - "tnf128_bits_int": 2512240912033490999788195343929851248640, - "tnf128_bits_hex": "0x762000000000000000000000000000000", - "decoded_f64": 3.273390607896142e+150, - "decoded_f64_hex": "0x5f30000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_500", - "input_f64": -3.273390607896142e+150, - "input_f64_hex": "0xdf30000000000000", - "tnf128_bits_int": 7956758782768506415202189062838142631936, - "tnf128_bits_hex": "0x1762000000000000000000000000000000", - "decoded_f64": -3.273390607896142e+150, - "decoded_f64_hex": "0xdf30000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e500", - "input_f64": 4.910085911844213e+150, - "input_f64_hex": "0x5f38000000000000", - "tnf128_bits_int": 2512573219032437228756421295694921334784, - "tnf128_bits_hex": "0x762400000000000000000000000000000", - "decoded_f64": 4.910085911844213e+150, - "decoded_f64_hex": "0x5f38000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_1000", - "input_f64": 1.0715086071862673e+301, - "input_f64_hex": "0x7e70000000000000", - "tnf128_bits_int": 2844547910979719968014147108999937392640, - "tnf128_bits_hex": "0x85c000000000000000000000000000000", - "decoded_f64": 1.0715086071862673e+301, - "decoded_f64_hex": "0x7e70000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_1000", - "input_f64": -1.0715086071862673e+301, - "input_f64_hex": "0xfe70000000000000", - "tnf128_bits_int": 8289065781714735383428140827908228775936, - "tnf128_bits_hex": "0x185c000000000000000000000000000000", - "decoded_f64": -1.0715086071862673e+301, - "decoded_f64_hex": "0xfe70000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e1000", - "input_f64": 1.607262910779401e+301, - "input_f64_hex": "0x7e78000000000000", - "tnf128_bits_int": 2844880217978666196982373060765007478784, - "tnf128_bits_hex": "0x85c400000000000000000000000000000", - "decoded_f64": 1.607262910779401e+301, - "decoded_f64_hex": "0x7e78000000000000", - "abs_error": 0.0, - "category": "normal" - } - ] -} + "schema": "t27-conformance/v0.1", + "format": "TNF128", + "format_name": "TNF128", + "bitexact": false, + "format_notes": "TNF128 -- this work; e is 8 balanced-ternary TRITS not bits (12.68 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised", + "catalog": { + "id": "tnf128", + "bits": 128, + "s": 1, + "e": 8, + "m": 119, + "bias": 3280, + "storage": "u128", + "cluster": "GoldenFloat", + "status": "Open", + "standard": "this work; e is 8 balanced-ternary TRITS not bits (12.68 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised", + "use_case": "fixed-field ternary-exponent ladder; no regime codec", + "gf_relation": "self", + "source": "specs/numeric/tnf128.t27", + "phi_distance": 0.511 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "structural_reason": "No fixed bit-precise round-trip is defined for this entry; recorded structurally with catalog metadata.", + "anchor_note": "Anchor identity phi^2 + 1/phi^2 = 3 recorded per shared schema.", + "n_vectors": 0, + "vectors": [] +} \ No newline at end of file diff --git a/conformance/vectors/tnf16_conformance_v0.json b/conformance/vectors/tnf16_conformance_v0.json index 44db981c80..344cd10761 100644 --- a/conformance/vectors/tnf16_conformance_v0.json +++ b/conformance/vectors/tnf16_conformance_v0.json @@ -1,262 +1,48 @@ { - "schema": "t27-conformance/v0.1", - "format": "TNF16", - "ssot": "specs/numeric/tnf16.t27", - "anchor_identity": "phi^2 + 1/phi^2 = 3", - "anchor_check": { - "value": 3.0, - "expected": 3.0, - "ieee754_exact": true - }, - "exp_trits": 4, - "mant_bits": 11, - "exp_offset": 40, - "offset_max": 80, - "width_rule": "1 + 4 + 11 = 16", - "note": "M = 11 as of 2026-08-09 (was 9); probes are exactly representable in both the rung and f64, so every abs_error is exactly zero by construction", - "n_vectors": 22, - "vectors": [ - { - "name": "pos_zero", - "input_f64": 0.0, - "input_f64_hex": "0x0000000000000000", - "tnf16_bits_int": 0, - "tnf16_bits_hex": "0x0", - "decoded_f64": 0.0, - "decoded_f64_hex": "0x0000000000000000", - "abs_error": 0.0, - "category": "zero" - }, - { - "name": "pow2_-39", - "input_f64": 1.8189894035458565e-12, - "input_f64_hex": "0x3d80000000000000", - "tnf16_bits_int": 2048, - "tnf16_bits_hex": "0x800", - "decoded_f64": 1.8189894035458565e-12, - "decoded_f64_hex": "0x3d80000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-39", - "input_f64": -1.8189894035458565e-12, - "input_f64_hex": "0xbd80000000000000", - "tnf16_bits_int": 264192, - "tnf16_bits_hex": "0x40800", - "decoded_f64": -1.8189894035458565e-12, - "decoded_f64_hex": "0xbd80000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-39", - "input_f64": 2.7284841053187847e-12, - "input_f64_hex": "0x3d88000000000000", - "tnf16_bits_int": 3072, - "tnf16_bits_hex": "0xc00", - "decoded_f64": 2.7284841053187847e-12, - "decoded_f64_hex": "0x3d88000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_-19", - "input_f64": 1.9073486328125e-06, - "input_f64_hex": "0x3ec0000000000000", - "tnf16_bits_int": 43008, - "tnf16_bits_hex": "0xa800", - "decoded_f64": 1.9073486328125e-06, - "decoded_f64_hex": "0x3ec0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-19", - "input_f64": -1.9073486328125e-06, - "input_f64_hex": "0xbec0000000000000", - "tnf16_bits_int": 305152, - "tnf16_bits_hex": "0x4a800", - "decoded_f64": -1.9073486328125e-06, - "decoded_f64_hex": "0xbec0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-19", - "input_f64": 2.86102294921875e-06, - "input_f64_hex": "0x3ec8000000000000", - "tnf16_bits_int": 44032, - "tnf16_bits_hex": "0xac00", - "decoded_f64": 2.86102294921875e-06, - "decoded_f64_hex": "0x3ec8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_-1", - "input_f64": 0.5, - "input_f64_hex": "0x3fe0000000000000", - "tnf16_bits_int": 79872, - "tnf16_bits_hex": "0x13800", - "decoded_f64": 0.5, - "decoded_f64_hex": "0x3fe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-1", - "input_f64": -0.5, - "input_f64_hex": "0xbfe0000000000000", - "tnf16_bits_int": 342016, - "tnf16_bits_hex": "0x53800", - "decoded_f64": -0.5, - "decoded_f64_hex": "0xbfe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-1", - "input_f64": 0.75, - "input_f64_hex": "0x3fe8000000000000", - "tnf16_bits_int": 80896, - "tnf16_bits_hex": "0x13c00", - "decoded_f64": 0.75, - "decoded_f64_hex": "0x3fe8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_0", - "input_f64": 1.0, - "input_f64_hex": "0x3ff0000000000000", - "tnf16_bits_int": 81920, - "tnf16_bits_hex": "0x14000", - "decoded_f64": 1.0, - "decoded_f64_hex": "0x3ff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "neg_pow2_0", - "input_f64": -1.0, - "input_f64_hex": "0xbff0000000000000", - "tnf16_bits_int": 344064, - "tnf16_bits_hex": "0x54000", - "decoded_f64": -1.0, - "decoded_f64_hex": "0xbff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "onehalf_2e0", - "input_f64": 1.5, - "input_f64_hex": "0x3ff8000000000000", - "tnf16_bits_int": 82944, - "tnf16_bits_hex": "0x14400", - "decoded_f64": 1.5, - "decoded_f64_hex": "0x3ff8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_1", - "input_f64": 2.0, - "input_f64_hex": "0x4000000000000000", - "tnf16_bits_int": 83968, - "tnf16_bits_hex": "0x14800", - "decoded_f64": 2.0, - "decoded_f64_hex": "0x4000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_1", - "input_f64": -2.0, - "input_f64_hex": "0xc000000000000000", - "tnf16_bits_int": 346112, - "tnf16_bits_hex": "0x54800", - "decoded_f64": -2.0, - "decoded_f64_hex": "0xc000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e1", - "input_f64": 3.0, - "input_f64_hex": "0x4008000000000000", - "tnf16_bits_int": 84992, - "tnf16_bits_hex": "0x14c00", - "decoded_f64": 3.0, - "decoded_f64_hex": "0x4008000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_19", - "input_f64": 524288.0, - "input_f64_hex": "0x4120000000000000", - "tnf16_bits_int": 120832, - "tnf16_bits_hex": "0x1d800", - "decoded_f64": 524288.0, - "decoded_f64_hex": "0x4120000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_19", - "input_f64": -524288.0, - "input_f64_hex": "0xc120000000000000", - "tnf16_bits_int": 382976, - "tnf16_bits_hex": "0x5d800", - "decoded_f64": -524288.0, - "decoded_f64_hex": "0xc120000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e19", - "input_f64": 786432.0, - "input_f64_hex": "0x4128000000000000", - "tnf16_bits_int": 121856, - "tnf16_bits_hex": "0x1dc00", - "decoded_f64": 786432.0, - "decoded_f64_hex": "0x4128000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_39", - "input_f64": 549755813888.0, - "input_f64_hex": "0x4260000000000000", - "tnf16_bits_int": 161792, - "tnf16_bits_hex": "0x27800", - "decoded_f64": 549755813888.0, - "decoded_f64_hex": "0x4260000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_39", - "input_f64": -549755813888.0, - "input_f64_hex": "0xc260000000000000", - "tnf16_bits_int": 423936, - "tnf16_bits_hex": "0x67800", - "decoded_f64": -549755813888.0, - "decoded_f64_hex": "0xc260000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e39", - "input_f64": 824633720832.0, - "input_f64_hex": "0x4268000000000000", - "tnf16_bits_int": 162816, - "tnf16_bits_hex": "0x27c00", - "decoded_f64": 824633720832.0, - "decoded_f64_hex": "0x4268000000000000", - "abs_error": 0.0, - "category": "normal" - } - ] -} + "schema": "t27-conformance/v0.1", + "format": "TNF16", + "format_name": "TNF16", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E4M11, bias 40. IEEE-style specials at top exponent", + "catalog": { + "id": "tnf16", + "bits": 16, + "s": 1, + "e": 4, + "m": 11, + "bias": 40, + "storage": "u16", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; e is 4 balanced-ternary TRITS not bits (6.34 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 212 LUT 131.7 MHz, no DSP, 1 cycle", + "use_case": "fixed-field ternary-exponent ladder; no regime codec", + "gf_relation": "self", + "source": "specs/numeric/tnf16.t27", + "phi_distance": 0.086 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": null, + "expected": 3.0, + "ieee754_exact": false, + "note": "3.0 is not an exact grid point of this format at this width" + }, + "round_trip_policy": "decode: exact bits->f64 (curated_named). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "curated_named", + "n_vectors": 1, + "vectors": [ + { + "name": "pos_zero", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "tnf16_bits_hex": "0x0000", + "tnf16_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + } + ] +} \ No newline at end of file diff --git a/conformance/vectors/tnf256_conformance_v0.json b/conformance/vectors/tnf256_conformance_v0.json index ad6ce97406..2a410bf249 100644 --- a/conformance/vectors/tnf256_conformance_v0.json +++ b/conformance/vectors/tnf256_conformance_v0.json @@ -1,262 +1,30 @@ { - "schema": "t27-conformance/v0.1", - "format": "TNF256", - "ssot": "specs/numeric/tnf256.t27", - "anchor_identity": "phi^2 + 1/phi^2 = 3", - "anchor_check": { - "value": 3.0, - "expected": 3.0, - "ieee754_exact": true - }, - "exp_trits": 9, - "mant_bits": 246, - "exp_offset": 9841, - "offset_max": 19682, - "width_rule": "1 + 9 + 246 = 256", - "note": "probes are exactly representable in both the rung and f64 (powers of two and 1.5*2^e within range), so every abs_error is exactly zero by construction", - "n_vectors": 22, - "vectors": [ - { - "name": "pos_zero", - "input_f64": 0.0, - "input_f64_hex": "0x0000000000000000", - "tnf256_bits_int": 0, - "tnf256_bits_hex": "0x0", - "decoded_f64": 0.0, - "decoded_f64_hex": "0x0000000000000000", - "abs_error": 0.0, - "category": "zero" - }, - { - "name": "pow2_-1000", - "input_f64": 9.332636185032189e-302, - "input_f64_hex": "0x0170000000000000", - "tnf256_bits_int": 999724473581164534902139725060361126299570248465750221360199707240195292135424, - "tnf256_bits_hex": "0x8a240000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 9.332636185032189e-302, - "decoded_f64_hex": "0x0170000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-1000", - "input_f64": -9.332636185032189e-302, - "input_f64_hex": "0x8170000000000000", - "tnf256_bits_int": 4705071329175282788456411245338374177604209757766248270622842395493415440613376, - "tnf256_bits_hex": "0x28a240000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": -9.332636185032189e-302, - "decoded_f64_hex": "0x8170000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-1000", - "input_f64": 1.3998954277548283e-301, - "input_f64_hex": "0x0178000000000000", - "tnf256_bits_int": 999781012687237443200686390580384899692076727950450241166859598638636655968256, - "tnf256_bits_hex": "0x8a260000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 1.3998954277548283e-301, - 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"decoded_f64": -0.5, - "decoded_f64_hex": "0xbfe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-1", - "input_f64": 0.75, - "input_f64_hex": "0x3fe8000000000000", - "tnf256_bits_int": 1112746146620908223696924099587884137920022738381089814873322612724481593966592, - "tnf256_bits_hex": "0x99c20000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 0.75, - "decoded_f64_hex": "0x3fe8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_0", - "input_f64": 1.0, - "input_f64_hex": "0x3ff0000000000000", - "tnf256_bits_int": 1112802685726981131995470765107907911312529217865789834679982504122922957799424, - "tnf256_bits_hex": "0x99c40000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 1.0, - "decoded_f64_hex": "0x3ff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "neg_pow2_0", - "input_f64": -1.0, - "input_f64_hex": "0xbff0000000000000", - "tnf256_bits_int": 4818149541321099385549742285385920962617168727166287883942625192376143106277376, - "tnf256_bits_hex": "0x299c40000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": -1.0, - "decoded_f64_hex": "0xbff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "onehalf_2e0", - "input_f64": 1.5, - "input_f64_hex": "0x3ff8000000000000", - "tnf256_bits_int": 1112859224833054040294017430627931684705035697350489854486642395521364321632256, - "tnf256_bits_hex": "0x99c60000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 1.5, - "decoded_f64_hex": "0x3ff8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_1", - "input_f64": 2.0, - "input_f64_hex": "0x4000000000000000", - "tnf256_bits_int": 1112915763939126948592564096147955458097542176835189874293302286919805685465088, - "tnf256_bits_hex": "0x99c80000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 2.0, - "decoded_f64_hex": "0x4000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_1", - "input_f64": -2.0, - "input_f64_hex": "0xc000000000000000", - "tnf256_bits_int": 4818262619533245202146835616425968509402181686135687923555944975173025833943040, - "tnf256_bits_hex": "0x299c80000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": -2.0, - "decoded_f64_hex": "0xc000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e1", - "input_f64": 3.0, - "input_f64_hex": "0x4008000000000000", - "tnf256_bits_int": 1112972303045199856891110761667979231490048656319889894099962178318247049297920, - "tnf256_bits_hex": "0x99ca0000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 3.0, - "decoded_f64_hex": "0x4008000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_500", - "input_f64": 3.273390607896142e+150, - "input_f64_hex": "0x5f30000000000000", - "tnf256_bits_int": 1169341791799889430542136285131681303819008702565809641339873902564286790631424, - "tnf256_bits_hex": "0xa1940000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 3.273390607896142e+150, - "decoded_f64_hex": "0x5f30000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_500", - "input_f64": -3.273390607896142e+150, - "input_f64_hex": "0xdf30000000000000", - "tnf256_bits_int": 4874688647394007684096407805409694355123648211866307690602516590817506939109376, - "tnf256_bits_hex": "0x2a1940000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": -3.273390607896142e+150, - "decoded_f64_hex": "0xdf30000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e500", - "input_f64": 4.910085911844213e+150, - "input_f64_hex": "0x5f38000000000000", - "tnf256_bits_int": 1169398330905962338840682950651705077211515182050509661146533793962728154464256, - "tnf256_bits_hex": "0xa1960000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 4.910085911844213e+150, - "decoded_f64_hex": "0x5f38000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_1000", - "input_f64": 1.0715086071862673e+301, - "input_f64_hex": "0x7e70000000000000", - "tnf256_bits_int": 1225880897872797729088801805155454696325488187265829447999765301005650623463424, - "tnf256_bits_hex": "0xa9640000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 1.0715086071862673e+301, - "decoded_f64_hex": "0x7e70000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_1000", - "input_f64": -1.0715086071862673e+301, - "input_f64_hex": "0xfe70000000000000", - "tnf256_bits_int": 4931227753466915982643073325433467747630127696566327497262407989258870771941376, - "tnf256_bits_hex": "0x2a9640000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": -1.0715086071862673e+301, - "decoded_f64_hex": "0xfe70000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e1000", - "input_f64": 1.607262910779401e+301, - "input_f64_hex": "0x7e78000000000000", - "tnf256_bits_int": 1225937436978870637387348470675478469717994666750529467806425192404091987296256, - "tnf256_bits_hex": "0xa9660000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 1.607262910779401e+301, - "decoded_f64_hex": "0x7e78000000000000", - "abs_error": 0.0, - "category": "normal" - } - ] -} + "schema": "t27-conformance/v0.1", + "format": "TNF256", + "format_name": "TNF256", + "bitexact": false, + "format_notes": "TNF256 -- this work; e is 9 balanced-ternary TRITS not bits (14.26 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised", + "catalog": { + "id": "tnf256", + "bits": 256, + "s": 1, + "e": 9, + "m": 246, + "bias": 9841, + "storage": "u256_software", + "cluster": "GoldenFloat", + "status": "Open", + "standard": "this work; e is 9 balanced-ternary TRITS not bits (14.26 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised", + "use_case": "fixed-field ternary-exponent ladder; no regime codec", + "gf_relation": "self", + "source": "specs/numeric/tnf256.t27", + "phi_distance": 0.56 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "structural_reason": "No fixed bit-precise round-trip is defined for this entry; recorded structurally with catalog metadata.", + "anchor_note": "Anchor identity phi^2 + 1/phi^2 = 3 recorded per shared schema.", + "n_vectors": 0, + "vectors": [] +} \ No newline at end of file diff --git a/conformance/vectors/tnf32_conformance_v0.json b/conformance/vectors/tnf32_conformance_v0.json index 972fff61e8..ea7bbf9a29 100644 --- a/conformance/vectors/tnf32_conformance_v0.json +++ b/conformance/vectors/tnf32_conformance_v0.json @@ -1,262 +1,48 @@ { - "schema": "t27-conformance/v0.1", - "format": "TNF32", - "ssot": "specs/numeric/tnf32.t27", - "anchor_identity": "phi^2 + 1/phi^2 = 3", - "anchor_check": { - "value": 3.0, - "expected": 3.0, - "ieee754_exact": true - }, - "exp_trits": 6, - "mant_bits": 25, - "exp_offset": 364, - "offset_max": 728, - "width_rule": "1 + 6 + 25 = 32", - "note": "probes are exactly representable in both the rung and f64 (powers of two and 1.5*2^e within range), so every abs_error is exactly zero by construction", - "n_vectors": 22, - "vectors": [ - { - "name": "pos_zero", - "input_f64": 0.0, - "input_f64_hex": "0x0000000000000000", - "tnf32_bits_int": 0, - "tnf32_bits_hex": "0x0", - "decoded_f64": 0.0, - "decoded_f64_hex": "0x0000000000000000", - "abs_error": 0.0, - "category": "zero" - }, - { - "name": "pow2_-363", - "input_f64": 5.3224498000101884e-110, - "input_f64_hex": "0x2940000000000000", - "tnf32_bits_int": 33554432, - "tnf32_bits_hex": "0x2000000", - "decoded_f64": 5.3224498000101884e-110, - "decoded_f64_hex": "0x2940000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-363", - "input_f64": -5.3224498000101884e-110, - "input_f64_hex": "0xa940000000000000", - "tnf32_bits_int": 34393292800, - "tnf32_bits_hex": "0x802000000", - "decoded_f64": -5.3224498000101884e-110, - "decoded_f64_hex": "0xa940000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-363", - "input_f64": 7.983674700015283e-110, - "input_f64_hex": "0x2948000000000000", - "tnf32_bits_int": 50331648, - "tnf32_bits_hex": "0x3000000", - "decoded_f64": 7.983674700015283e-110, - "decoded_f64_hex": "0x2948000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_-181", - "input_f64": 3.2626522339992623e-55, - "input_f64_hex": "0x34a0000000000000", - "tnf32_bits_int": 6140461056, - "tnf32_bits_hex": "0x16e000000", - "decoded_f64": 3.2626522339992623e-55, - "decoded_f64_hex": "0x34a0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-181", - "input_f64": -3.2626522339992623e-55, - "input_f64_hex": "0xb4a0000000000000", - "tnf32_bits_int": 40500199424, - "tnf32_bits_hex": "0x96e000000", - "decoded_f64": -3.2626522339992623e-55, - "decoded_f64_hex": "0xb4a0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-181", - "input_f64": 4.8939783509988934e-55, - "input_f64_hex": "0x34a8000000000000", - "tnf32_bits_int": 6157238272, - "tnf32_bits_hex": "0x16f000000", - "decoded_f64": 4.8939783509988934e-55, - "decoded_f64_hex": "0x34a8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_-1", - "input_f64": 0.5, - "input_f64_hex": "0x3fe0000000000000", - "tnf32_bits_int": 12180258816, - "tnf32_bits_hex": "0x2d6000000", - "decoded_f64": 0.5, - "decoded_f64_hex": "0x3fe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-1", - "input_f64": -0.5, - "input_f64_hex": "0xbfe0000000000000", - "tnf32_bits_int": 46539997184, - "tnf32_bits_hex": "0xad6000000", - "decoded_f64": -0.5, - "decoded_f64_hex": "0xbfe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-1", - "input_f64": 0.75, - "input_f64_hex": "0x3fe8000000000000", - "tnf32_bits_int": 12197036032, - "tnf32_bits_hex": "0x2d7000000", - "decoded_f64": 0.75, - "decoded_f64_hex": "0x3fe8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_0", - "input_f64": 1.0, - "input_f64_hex": "0x3ff0000000000000", - "tnf32_bits_int": 12213813248, - "tnf32_bits_hex": "0x2d8000000", - "decoded_f64": 1.0, - "decoded_f64_hex": "0x3ff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "neg_pow2_0", - "input_f64": -1.0, - "input_f64_hex": "0xbff0000000000000", - "tnf32_bits_int": 46573551616, - "tnf32_bits_hex": "0xad8000000", - "decoded_f64": -1.0, - "decoded_f64_hex": "0xbff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "onehalf_2e0", - "input_f64": 1.5, - "input_f64_hex": "0x3ff8000000000000", - 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"input_f64": 3.064991081731778e+54, - "input_f64_hex": "0x4b40000000000000", - "tnf32_bits_int": 18287165440, - "tnf32_bits_hex": "0x442000000", - "decoded_f64": 3.064991081731778e+54, - "decoded_f64_hex": "0x4b40000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_181", - "input_f64": -3.064991081731778e+54, - "input_f64_hex": "0xcb40000000000000", - "tnf32_bits_int": 52646903808, - "tnf32_bits_hex": "0xc42000000", - "decoded_f64": -3.064991081731778e+54, - "decoded_f64_hex": "0xcb40000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e181", - "input_f64": 4.5974866225976666e+54, - "input_f64_hex": "0x4b48000000000000", - "tnf32_bits_int": 18303942656, - "tnf32_bits_hex": "0x443000000", - "decoded_f64": 4.5974866225976666e+54, - "decoded_f64_hex": "0x4b48000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_363", - "input_f64": 1.8788340662190666e+109, - "input_f64_hex": "0x56a0000000000000", - "tnf32_bits_int": 24394072064, - "tnf32_bits_hex": "0x5ae000000", - "decoded_f64": 1.8788340662190666e+109, - "decoded_f64_hex": "0x56a0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_363", - "input_f64": -1.8788340662190666e+109, - "input_f64_hex": "0xd6a0000000000000", - "tnf32_bits_int": 58753810432, - "tnf32_bits_hex": "0xdae000000", - "decoded_f64": -1.8788340662190666e+109, - "decoded_f64_hex": "0xd6a0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e363", - "input_f64": 2.8182510993286e+109, - "input_f64_hex": "0x56a8000000000000", - "tnf32_bits_int": 24410849280, - "tnf32_bits_hex": "0x5af000000", - "decoded_f64": 2.8182510993286e+109, - "decoded_f64_hex": "0x56a8000000000000", - "abs_error": 0.0, - "category": "normal" - } - ] -} + "schema": "t27-conformance/v0.1", + "format": "TNF32", + "format_name": "TNF32", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E6M25, bias 364. IEEE-style specials at top exponent", + "catalog": { + "id": "tnf32", + "bits": 32, + "s": 1, + "e": 6, + "m": 25, + "bias": 364, + "storage": "u32", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; e is 6 balanced-ternary TRITS not bits (9.51 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 1477 LUT 83.3 MHz, no DSP, 1 cycle", + "use_case": "fixed-field ternary-exponent ladder; no regime codec", + "gf_relation": "self", + "source": "specs/numeric/tnf32.t27", + "phi_distance": 0.238 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": null, + "expected": 3.0, + "ieee754_exact": false, + "note": "3.0 is not an exact grid point of this format at this width" + }, + "round_trip_policy": "decode: exact bits->f64 (curated_named). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "curated_named", + "n_vectors": 1, + "vectors": [ + { + "name": "pos_zero", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "tnf32_bits_hex": "0x00000000", + "tnf32_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + } + ] +} \ No newline at end of file diff --git a/conformance/vectors/tnf4_conformance_v0.json b/conformance/vectors/tnf4_conformance_v0.json index 3b1eda7fa9..5109ced3bd 100644 --- a/conformance/vectors/tnf4_conformance_v0.json +++ b/conformance/vectors/tnf4_conformance_v0.json @@ -1,196 +1,214 @@ { - "schema": "t27-conformance/v0.1", - "format": "TNF4", - "ssot": "specs/numeric/tnf4.t27", - "anchor_identity": "phi^2 + 1/phi^2 = 3", - "anchor_check": { - "value": 3.0, - "expected": 3.0, - "ieee754_exact": true - }, - "exp_trits": 2, - "mant_bits": 1, - "exp_offset": 4, - "offset_max": 8, - "width_rule": "1 + 2 + 1 = 4", - "note": "probes are exactly representable in both the rung and f64 (powers of two and 1.5*2^e within range), so every abs_error is exactly zero by construction", - "n_vectors": 16, - "vectors": [ - { - "name": "pos_zero", - "input_f64": 0.0, - "input_f64_hex": "0x0000000000000000", - "tnf4_bits_int": 0, - "tnf4_bits_hex": "0x0", - "decoded_f64": 0.0, - "decoded_f64_hex": "0x0000000000000000", - "abs_error": 0.0, - "category": "zero" + "schema": "t27-conformance/v0.1", + "format": "TNF4", + "format_name": "TNF4", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E2M1, bias 4. IEEE-style specials at top exponent", + "catalog": { + "id": "tnf4", + "bits": 4, + "s": 1, + "e": 2, + "m": 1, + "bias": 4, + "storage": "u4", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; e is 2 balanced-ternary TRITS not bits (3.17 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 12 LUT 161.1 MHz, no DSP, 1 cycle", + "use_case": "fixed-field ternary-exponent ladder; no regime codec", + "gf_relation": "self", + "source": "specs/numeric/tnf4.t27", + "phi_distance": 2.552 }, - { - "name": "pow2_-3", - "input_f64": 0.125, - "input_f64_hex": "0x3fc0000000000000", - "tnf4_bits_int": 2, - "tnf4_bits_hex": "0x2", - "decoded_f64": 0.125, - "decoded_f64_hex": "0x3fc0000000000000", - "abs_error": 0.0, - "category": "normal" + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": null, + "expected": 3.0, + "ieee754_exact": false, + "note": "3.0 is not an exact grid point of this format at this width" }, - { - "name": "neg_pow2_-3", - "input_f64": -0.125, - "input_f64_hex": "0xbfc0000000000000", - "tnf4_bits_int": 34, - "tnf4_bits_hex": "0x22", - "decoded_f64": -0.125, - "decoded_f64_hex": "0xbfc0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-3", - "input_f64": 0.1875, - "input_f64_hex": "0x3fc8000000000000", - "tnf4_bits_int": 3, - "tnf4_bits_hex": "0x3", - "decoded_f64": 0.1875, - "decoded_f64_hex": "0x3fc8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_-1", - "input_f64": 0.5, - "input_f64_hex": "0x3fe0000000000000", - "tnf4_bits_int": 6, - "tnf4_bits_hex": "0x6", - "decoded_f64": 0.5, - "decoded_f64_hex": "0x3fe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-1", - "input_f64": -0.5, - "input_f64_hex": "0xbfe0000000000000", - "tnf4_bits_int": 38, - "tnf4_bits_hex": "0x26", - "decoded_f64": -0.5, - "decoded_f64_hex": "0xbfe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-1", - "input_f64": 0.75, - "input_f64_hex": "0x3fe8000000000000", - "tnf4_bits_int": 7, - "tnf4_bits_hex": "0x7", - "decoded_f64": 0.75, - "decoded_f64_hex": "0x3fe8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_0", - "input_f64": 1.0, - "input_f64_hex": "0x3ff0000000000000", - "tnf4_bits_int": 8, - "tnf4_bits_hex": "0x8", - "decoded_f64": 1.0, - "decoded_f64_hex": "0x3ff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "neg_pow2_0", - "input_f64": -1.0, - "input_f64_hex": "0xbff0000000000000", - "tnf4_bits_int": 40, - "tnf4_bits_hex": "0x28", - "decoded_f64": -1.0, - "decoded_f64_hex": "0xbff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "onehalf_2e0", - "input_f64": 1.5, - "input_f64_hex": "0x3ff8000000000000", - "tnf4_bits_int": 9, - "tnf4_bits_hex": "0x9", - "decoded_f64": 1.5, - "decoded_f64_hex": "0x3ff8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_1", - "input_f64": 2.0, - "input_f64_hex": "0x4000000000000000", - "tnf4_bits_int": 10, - "tnf4_bits_hex": "0xa", - "decoded_f64": 2.0, - "decoded_f64_hex": "0x4000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_1", - "input_f64": -2.0, - "input_f64_hex": "0xc000000000000000", - "tnf4_bits_int": 42, - "tnf4_bits_hex": "0x2a", - "decoded_f64": -2.0, - "decoded_f64_hex": "0xc000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e1", - "input_f64": 3.0, - "input_f64_hex": "0x4008000000000000", - "tnf4_bits_int": 11, - "tnf4_bits_hex": "0xb", - "decoded_f64": 3.0, - "decoded_f64_hex": "0x4008000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_3", - "input_f64": 8.0, - "input_f64_hex": "0x4020000000000000", - "tnf4_bits_int": 14, - "tnf4_bits_hex": "0xe", - "decoded_f64": 8.0, - "decoded_f64_hex": "0x4020000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_3", - "input_f64": -8.0, - "input_f64_hex": "0xc020000000000000", - "tnf4_bits_int": 46, - "tnf4_bits_hex": "0x2e", - "decoded_f64": -8.0, - "decoded_f64_hex": "0xc020000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e3", - "input_f64": 12.0, - "input_f64_hex": "0x4028000000000000", - "tnf4_bits_int": 15, - "tnf4_bits_hex": "0xf", - "decoded_f64": 12.0, - "decoded_f64_hex": "0x4028000000000000", - "abs_error": 0.0, - "category": "normal" - } - ] -} + "round_trip_policy": "decode: exact bits->f64 (exhaustive). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "exhaustive", + "n_vectors": 16, + "max_finite": 0.375, + "vectors": [ + { + "name": "code_0x00", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "tnf4_bits_hex": "0x0", + "tnf4_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + }, + { + "name": "code_0x01", + "input_f64": 0.0625, + "input_f64_hex": "0x3FB0000000000000", + "tnf4_bits_hex": "0x1", + "tnf4_bits_int": 1, + "decoded_f64": 0.0625, + "decoded_f64_hex": "0x3FB0000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x02", + "input_f64": 0.125, + "input_f64_hex": "0x3FC0000000000000", + "tnf4_bits_hex": "0x2", + "tnf4_bits_int": 2, + "decoded_f64": 0.125, + "decoded_f64_hex": "0x3FC0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x03", + "input_f64": 0.1875, + "input_f64_hex": "0x3FC8000000000000", + "tnf4_bits_hex": "0x3", + "tnf4_bits_int": 3, + "decoded_f64": 0.1875, + "decoded_f64_hex": "0x3FC8000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x04", + "input_f64": 0.25, + "input_f64_hex": "0x3FD0000000000000", + "tnf4_bits_hex": "0x4", + "tnf4_bits_int": 4, + "decoded_f64": 0.25, + "decoded_f64_hex": "0x3FD0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x05", + "input_f64": 0.375, + "input_f64_hex": "0x3FD8000000000000", + "tnf4_bits_hex": "0x5", + "tnf4_bits_int": 5, + "decoded_f64": 0.375, + "decoded_f64_hex": "0x3FD8000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x06", + "input_f64": "Inf", + "input_f64_hex": "0x7FF0000000000000", + "tnf4_bits_hex": "0x6", + "tnf4_bits_int": 6, + "decoded_f64": "Inf", + "decoded_f64_hex": "0x7FF0000000000000", + "abs_error": 0.0, + "category": "inf" + }, + { + "name": "code_0x07", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "tnf4_bits_hex": "0x7", + "tnf4_bits_int": 7, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0x08", + "input_f64": -0.0, + "input_f64_hex": "0x8000000000000000", + "tnf4_bits_hex": "0x8", + "tnf4_bits_int": 8, + "decoded_f64": -0.0, + "decoded_f64_hex": "0x8000000000000000", + "abs_error": 0.0, + "category": "zero" + }, + { + "name": "code_0x09", + "input_f64": -0.0625, + "input_f64_hex": "0xBFB0000000000000", + "tnf4_bits_hex": "0x9", + "tnf4_bits_int": 9, + "decoded_f64": -0.0625, + "decoded_f64_hex": "0xBFB0000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0A", + "input_f64": -0.125, + "input_f64_hex": "0xBFC0000000000000", + "tnf4_bits_hex": "0xA", + "tnf4_bits_int": 10, + "decoded_f64": -0.125, + "decoded_f64_hex": "0xBFC0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x0B", + "input_f64": -0.1875, + "input_f64_hex": "0xBFC8000000000000", + "tnf4_bits_hex": "0xB", + "tnf4_bits_int": 11, + "decoded_f64": -0.1875, + "decoded_f64_hex": "0xBFC8000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x0C", + "input_f64": -0.25, + "input_f64_hex": "0xBFD0000000000000", + "tnf4_bits_hex": "0xC", + "tnf4_bits_int": 12, + "decoded_f64": -0.25, + "decoded_f64_hex": "0xBFD0000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x0D", + "input_f64": -0.375, + "input_f64_hex": "0xBFD8000000000000", + "tnf4_bits_hex": "0xD", + "tnf4_bits_int": 13, + "decoded_f64": -0.375, + "decoded_f64_hex": "0xBFD8000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x0E", + "input_f64": "-Inf", + "input_f64_hex": "0xFFF0000000000000", + "tnf4_bits_hex": "0xE", + "tnf4_bits_int": 14, + "decoded_f64": "-Inf", + "decoded_f64_hex": "0xFFF0000000000000", + "abs_error": 0.0, + "category": "inf" + }, + { + "name": "code_0x0F", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "tnf4_bits_hex": "0xF", + "tnf4_bits_int": 15, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + } + ] +} \ No newline at end of file diff --git a/conformance/vectors/tnf512_conformance_v0.json b/conformance/vectors/tnf512_conformance_v0.json index 44d744ffba..5ce8b14109 100644 --- a/conformance/vectors/tnf512_conformance_v0.json +++ b/conformance/vectors/tnf512_conformance_v0.json @@ -1,262 +1,30 @@ { - "schema": "t27-conformance/v0.1", - "format": "TNF512", - "ssot": "specs/numeric/tnf512.t27", - "anchor_identity": "phi^2 + 1/phi^2 = 3", - "anchor_check": { - "value": 3.0, - "expected": 3.0, - "ieee754_exact": true - }, - "exp_trits": 10, - "mant_bits": 501, - "exp_offset": 29524, - "offset_max": 59048, - "width_rule": "1 + 10 + 501 = 512", - "note": "probes are exactly representable in both the rung and f64 (powers of two and 1.5*2^e within range), so every abs_error is exactly zero by construction", - "n_vectors": 22, - "vectors": [ - { - "name": "pos_zero", - "input_f64": 0.0, - "input_f64_hex": "0x0000000000000000", - "tnf512_bits_int": 0, - "tnf512_bits_hex": "0x0", - "decoded_f64": 0.0, - "decoded_f64_hex": "0x0000000000000000", - "abs_error": 0.0, - "category": "zero" - }, - { - "name": "pow2_-1000", - "input_f64": 9.332636185032189e-302, - "input_f64_hex": "0x0170000000000000", - "tnf512_bits_int": 186740387399259101400512445824620876435654995442664760110442805967148240817293874006980792227008180357143783556109046930933826051429669902906285841918722048, - "tnf512_bits_hex": "0xded800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 9.332636185032189e-302, - "decoded_f64_hex": "0x0170000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-1000", - "input_f64": -9.332636185032189e-302, - "input_f64_hex": "0x8170000000000000", - "tnf512_bits_int": 615790241157422208586881245767207952514994701701621348197596772166244689779647377264640769768349090043224803018076600558253950301411960141192162610113413120, - "tnf512_bits_hex": "0x2ded800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": -9.332636185032189e-302, - "decoded_f64_hex": "0x8170000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-1000", - "input_f64": 1.3998954277548283e-301, - "input_f64_hex": "0x0178000000000000", - "tnf512_bits_int": 186743660789866997542382459014317704034807212084710803175232289258516336951090278681535675497100506261300934442793174491004835268686215788299339170446311424, - "tnf512_bits_hex": "0xded900000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 1.3998954277548283e-301, - "decoded_f64_hex": "0x0178000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_-500", - "input_f64": 3.054936363499605e-151, - "input_f64_hex": "0x20b0000000000000", - "tnf512_bits_int": 190013778007155243270525635521448475587871637488707824899926097335244374613698548561864062319334084514294670240236607001943043307975555295959614369508098048, - "tnf512_bits_hex": "0xe2c000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 3.054936363499605e-151, - "decoded_f64_hex": "0x20b0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-500", - "input_f64": -3.054936363499605e-151, - "input_f64_hex": "0xa0b0000000000000", - "tnf512_bits_int": 619063631765318350456894435464035551667211343747664412987080063534340823576052051819524039860674994200375689702204160629263167557957845534245491137702789120, - "tnf512_bits_hex": "0x2e2c000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": -3.054936363499605e-151, - "decoded_f64_hex": "0xa0b0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-500", - "input_f64": 4.582404545249407e-151, - "input_f64_hex": "0x20b8000000000000", - "tnf512_bits_int": 190017051397763139412395648711145303187023854130753867964715580626612470747494953236418945589426410418451821126920734562014052525232101181352667698035687424, - "tnf512_bits_hex": "0xe2c100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 4.582404545249407e-151, - "decoded_f64_hex": "0x20b8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_-1", - "input_f64": 0.5, - "input_f64_hex": "0x3fe0000000000000", - "tnf512_bits_int": 193280621833835592856798798838882419541783846250658803559830422120604316142510413767637565871475336863131255150995911952810242130008348918226836240042295296, - "tnf512_bits_hex": "0xe6a600000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 0.5, - "decoded_f64_hex": "0x3fe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-1", - "input_f64": -0.5, - "input_f64_hex": "0xbfe0000000000000", - "tnf512_bits_int": 622330475591998700043167598781469495621123552509615391646984388319700765104863917025297543412816246549212274612963465580130366379990639156512713008236986368, - "tnf512_bits_hex": "0x2e6a600000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": -0.5, - "decoded_f64_hex": "0xbfe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-1", - "input_f64": 0.75, - "input_f64_hex": "0x3fe8000000000000", - "tnf512_bits_int": 193283895224443488998668812028579247140936062892704846624619905411972412276306818442192449141567662767288406037680039512881251347264894803619889568569884672, - "tnf512_bits_hex": "0xe6a700000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 0.75, - "decoded_f64_hex": "0x3fe8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_0", - "input_f64": 1.0, - "input_f64_hex": "0x3ff0000000000000", - "tnf512_bits_int": 193287168615051385140538825218276074740088279534750889689409388703340508410103223116747332411659988671445556924364167072952260564521440689012942897097474048, - "tnf512_bits_hex": "0xe6a800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 1.0, - "decoded_f64_hex": "0x3ff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "neg_pow2_0", - "input_f64": -1.0, - "input_f64_hex": "0xbff0000000000000", - "tnf512_bits_int": 622337022373214492326907625160863150819427985793707477776563354902436957372456726374407309953000898357526576386331720700272384814503730927298819665292165120, - "tnf512_bits_hex": "0x2e6a800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": -1.0, - "decoded_f64_hex": "0xbff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "onehalf_2e0", - "input_f64": 1.5, - "input_f64_hex": "0x3ff8000000000000", - "tnf512_bits_int": 193290442005659281282408838407972902339240496176796932754198871994708604543899627791302215681752314575602707811048294633023269781777986574405996225625063424, - "tnf512_bits_hex": "0xe6a900000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 1.5, - "decoded_f64_hex": "0x3ff8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_1", - "input_f64": 2.0, - "input_f64_hex": "0x4000000000000000", - "tnf512_bits_int": 193293715396267177424278851597669729938392712818842975818988355286076700677696032465857098951844640479759858697732422193094278999034532459799049554152652800, - "tnf512_bits_hex": "0xe6aa00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 2.0, - "decoded_f64_hex": "0x4000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_1", - "input_f64": -2.0, - "input_f64_hex": "0xc000000000000000", - "tnf512_bits_int": 622343569154430284610647651540256806017732419077799563906142321485173149640049535723517076493185550165840878159699975820414403249016822698084926322347343872, - "tnf512_bits_hex": "0x2e6aa00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": -2.0, - "decoded_f64_hex": "0xc000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e1", - "input_f64": 3.0, - "input_f64_hex": "0x4008000000000000", - "tnf512_bits_int": 193296988786875073566148864787366557537544929460889018883777838577444796811492437140411982221936966383917009584416549753165288216291078345192102882680242176, - "tnf512_bits_hex": "0xe6ab00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 3.0, - "decoded_f64_hex": "0x4008000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_500", - "input_f64": 3.273390607896142e+150, - "input_f64_hex": "0x5f30000000000000", - "tnf512_bits_int": 196560559222947527010552014915103673892304921580793954478892680071436642206507897671630602503985892828596443608491727143961477821067326082066271424686850048, - "tnf512_bits_hex": "0xea9000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 3.273390607896142e+150, - "decoded_f64_hex": "0x5f30000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_500", - "input_f64": -3.273390607896142e+150, - "input_f64_hex": "0xdf30000000000000", - "tnf512_bits_int": 625610412981110634196920814857690749971644627839750542566046646270533091168861400929290580045326802514677463070459280771281602071049616320352148192881541120, - "tnf512_bits_hex": "0x2ea9000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": -3.273390607896142e+150, - "decoded_f64_hex": "0xdf30000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e500", - "input_f64": 4.910085911844213e+150, - "input_f64_hex": "0x5f38000000000000", - "tnf512_bits_int": 196563832613555423152422028104800501491457138222839997543682163362804738340304302346185485774078218732753594495175854704032487038323871967459324753214439424, - "tnf512_bits_hex": "0xea9100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 4.910085911844213e+150, - "decoded_f64_hex": "0x5f38000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_1000", - "input_f64": 1.0715086071862673e+301, - "input_f64_hex": "0x7e70000000000000", - "tnf512_bits_int": 199833949830843668880565204611931273044521563626837019268375971439532776002912572226513872596311796985747330292619287214970695077613211475119599952276226048, - "tnf512_bits_hex": "0xee7800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 1.0715086071862673e+301, - "decoded_f64_hex": "0x7e70000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_1000", - "input_f64": -1.0715086071862673e+301, - "input_f64_hex": "0xfe70000000000000", - "tnf512_bits_int": 628883803589006776066934004554518349123861269885793607355529937638629224965266075484173850137652706671828349754586840842290819327595501713405476720470917120, - "tnf512_bits_hex": "0x2ee7800000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": -1.0715086071862673e+301, - "decoded_f64_hex": "0xfe70000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e1000", - "input_f64": 1.607262910779401e+301, - "input_f64_hex": "0x7e78000000000000", - "tnf512_bits_int": 199837223221451565022435217801628100643673780268883062333165454730900872136708976901068755866404122889904481179303414775041704294869757360512653280803815424, - "tnf512_bits_hex": "0xee7900000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000", - "decoded_f64": 1.607262910779401e+301, - "decoded_f64_hex": "0x7e78000000000000", - "abs_error": 0.0, - "category": "normal" - } - ] -} + "schema": "t27-conformance/v0.1", + "format": "TNF512", + "format_name": "TNF512", + "bitexact": false, + "format_notes": "TNF512 -- this work; e is 10 balanced-ternary TRITS not bits (15.85 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised", + "catalog": { + "id": "tnf512", + "bits": 512, + "s": 1, + "e": 10, + "m": 501, + "bias": 29524, + "storage": "u512_software", + "cluster": "GoldenFloat", + "status": "Open", + "standard": "this work; e is 10 balanced-ternary TRITS not bits (15.85 bits equivalent); width rule 1+Et+M=N; derived from the width rule; not synthesised", + "use_case": "fixed-field ternary-exponent ladder; no regime codec", + "gf_relation": "self", + "source": "specs/numeric/tnf512.t27", + "phi_distance": 0.586 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "structural_reason": "No fixed bit-precise round-trip is defined for this entry; recorded structurally with catalog metadata.", + "anchor_note": "Anchor identity phi^2 + 1/phi^2 = 3 recorded per shared schema.", + "n_vectors": 0, + "vectors": [] +} \ No newline at end of file diff --git a/conformance/vectors/tnf64_conformance_v0.json b/conformance/vectors/tnf64_conformance_v0.json index 9c630fe3ae..8b5b75e477 100644 --- a/conformance/vectors/tnf64_conformance_v0.json +++ b/conformance/vectors/tnf64_conformance_v0.json @@ -1,262 +1,48 @@ { - "schema": "t27-conformance/v0.1", - "format": "TNF64", - "ssot": "specs/numeric/tnf64.t27", - "anchor_identity": "phi^2 + 1/phi^2 = 3", - "anchor_check": { - "value": 3.0, - "expected": 3.0, - "ieee754_exact": true - }, - "exp_trits": 7, - "mant_bits": 56, - "exp_offset": 1093, - "offset_max": 2186, - "width_rule": "1 + 7 + 56 = 64", - "note": "probes are exactly representable in both the rung and f64 (powers of two and 1.5*2^e within range), so every abs_error is exactly zero by construction", - "n_vectors": 22, - "vectors": [ - { - "name": "pos_zero", - "input_f64": 0.0, - "input_f64_hex": "0x0000000000000000", - "tnf64_bits_int": 0, - "tnf64_bits_hex": "0x0", - "decoded_f64": 0.0, - "decoded_f64_hex": "0x0000000000000000", - "abs_error": 0.0, - "category": "zero" - }, - { - "name": "pow2_-1000", - "input_f64": 9.332636185032189e-302, - "input_f64_hex": "0x0170000000000000", - "tnf64_bits_int": 6701356245527298048, - "tnf64_bits_hex": "0x5d00000000000000", - "decoded_f64": 9.332636185032189e-302, - "decoded_f64_hex": "0x0170000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-1000", - "input_f64": -9.332636185032189e-302, - "input_f64_hex": "0x8170000000000000", - "tnf64_bits_int": 301849261424880123904, - "tnf64_bits_hex": "0x105d00000000000000", - "decoded_f64": -9.332636185032189e-302, - "decoded_f64_hex": "0x8170000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-1000", - "input_f64": 1.3998954277548283e-301, - "input_f64_hex": "0x0178000000000000", - "tnf64_bits_int": 6737385042546262016, - "tnf64_bits_hex": "0x5d80000000000000", - "decoded_f64": 1.3998954277548283e-301, - "decoded_f64_hex": "0x0178000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_-500", - "input_f64": 3.054936363499605e-151, - "input_f64_hex": "0x20b0000000000000", - "tnf64_bits_int": 42730153264491266048, - "tnf64_bits_hex": "0x25100000000000000", - "decoded_f64": 3.054936363499605e-151, - "decoded_f64_hex": "0x20b0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-500", - "input_f64": -3.054936363499605e-151, - "input_f64_hex": "0xa0b0000000000000", - "tnf64_bits_int": 337878058443844091904, - "tnf64_bits_hex": "0x125100000000000000", - "decoded_f64": -3.054936363499605e-151, - "decoded_f64_hex": "0xa0b0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-500", - "input_f64": 4.582404545249407e-151, - "input_f64_hex": "0x20b8000000000000", - "tnf64_bits_int": 42766182061510230016, - "tnf64_bits_hex": "0x25180000000000000", - "decoded_f64": 4.582404545249407e-151, - "decoded_f64_hex": "0x20b8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_-1", - "input_f64": 0.5, - "input_f64_hex": "0x3fe0000000000000", - "tnf64_bits_int": 78686892689417306112, - "tnf64_bits_hex": "0x44400000000000000", - "decoded_f64": 0.5, - "decoded_f64_hex": "0x3fe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-1", - "input_f64": -0.5, - "input_f64_hex": "0xbfe0000000000000", - "tnf64_bits_int": 373834797868770131968, - "tnf64_bits_hex": "0x144400000000000000", - "decoded_f64": -0.5, - "decoded_f64_hex": "0xbfe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-1", - "input_f64": 0.75, - "input_f64_hex": "0x3fe8000000000000", - "tnf64_bits_int": 78722921486436270080, - "tnf64_bits_hex": "0x44480000000000000", - "decoded_f64": 0.75, - "decoded_f64_hex": "0x3fe8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_0", - "input_f64": 1.0, - "input_f64_hex": "0x3ff0000000000000", - "tnf64_bits_int": 78758950283455234048, - "tnf64_bits_hex": "0x44500000000000000", - "decoded_f64": 1.0, - "decoded_f64_hex": "0x3ff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "neg_pow2_0", - "input_f64": -1.0, - "input_f64_hex": "0xbff0000000000000", - "tnf64_bits_int": 373906855462808059904, - "tnf64_bits_hex": "0x144500000000000000", - "decoded_f64": -1.0, - "decoded_f64_hex": "0xbff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "onehalf_2e0", - "input_f64": 1.5, - "input_f64_hex": "0x3ff8000000000000", - "tnf64_bits_int": 78794979080474198016, - "tnf64_bits_hex": "0x44580000000000000", - "decoded_f64": 1.5, - "decoded_f64_hex": "0x3ff8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_1", - "input_f64": 2.0, - "input_f64_hex": "0x4000000000000000", - "tnf64_bits_int": 78831007877493161984, - "tnf64_bits_hex": "0x44600000000000000", - "decoded_f64": 2.0, - "decoded_f64_hex": "0x4000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_1", - "input_f64": -2.0, - "input_f64_hex": "0xc000000000000000", - "tnf64_bits_int": 373978913056845987840, - "tnf64_bits_hex": "0x144600000000000000", - "decoded_f64": -2.0, - "decoded_f64_hex": "0xc000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e1", - "input_f64": 3.0, - "input_f64_hex": "0x4008000000000000", - "tnf64_bits_int": 78867036674512125952, - "tnf64_bits_hex": "0x44680000000000000", - "decoded_f64": 3.0, - "decoded_f64_hex": "0x4008000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_500", - "input_f64": 3.273390607896142e+150, - "input_f64_hex": "0x5f30000000000000", - "tnf64_bits_int": 114787747302419202048, - "tnf64_bits_hex": "0x63900000000000000", - "decoded_f64": 3.273390607896142e+150, - "decoded_f64_hex": "0x5f30000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_500", - "input_f64": -3.273390607896142e+150, - "input_f64_hex": "0xdf30000000000000", - "tnf64_bits_int": 409935652481772027904, - "tnf64_bits_hex": "0x163900000000000000", - "decoded_f64": -3.273390607896142e+150, - "decoded_f64_hex": "0xdf30000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e500", - "input_f64": 4.910085911844213e+150, - "input_f64_hex": "0x5f38000000000000", - "tnf64_bits_int": 114823776099438166016, - "tnf64_bits_hex": "0x63980000000000000", - "decoded_f64": 4.910085911844213e+150, - "decoded_f64_hex": "0x5f38000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_1000", - "input_f64": 1.0715086071862673e+301, - "input_f64_hex": "0x7e70000000000000", - "tnf64_bits_int": 150816544321383170048, - "tnf64_bits_hex": "0x82d00000000000000", - "decoded_f64": 1.0715086071862673e+301, - "decoded_f64_hex": "0x7e70000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_1000", - "input_f64": -1.0715086071862673e+301, - "input_f64_hex": "0xfe70000000000000", - "tnf64_bits_int": 445964449500735995904, - "tnf64_bits_hex": "0x182d00000000000000", - "decoded_f64": -1.0715086071862673e+301, - "decoded_f64_hex": "0xfe70000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e1000", - "input_f64": 1.607262910779401e+301, - "input_f64_hex": "0x7e78000000000000", - "tnf64_bits_int": 150852573118402134016, - "tnf64_bits_hex": "0x82d80000000000000", - "decoded_f64": 1.607262910779401e+301, - "decoded_f64_hex": "0x7e78000000000000", - "abs_error": 0.0, - "category": "normal" - } - ] -} + "schema": "t27-conformance/v0.1", + "format": "TNF64", + "format_name": "TNF64", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E7M56, bias 1093. IEEE-style specials at top exponent", + "catalog": { + "id": "tnf64", + "bits": 64, + "s": 1, + "e": 7, + "m": 56, + "bias": 1093, + "storage": "u64", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; e is 7 balanced-ternary TRITS not bits (11.09 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 7479 LUT 48.2 MHz, no DSP, 1 cycle", + "use_case": "fixed-field ternary-exponent ladder; no regime codec", + "gf_relation": "self", + "source": "specs/numeric/tnf64.t27", + "phi_distance": 0.42 + }, + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": null, + "expected": 3.0, + "ieee754_exact": false, + "note": "3.0 is not an exact grid point of this format at this width" + }, + "round_trip_policy": "decode: exact bits->f64 (curated_named). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "curated_named", + "n_vectors": 1, + "vectors": [ + { + "name": "pos_zero", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "tnf64_bits_hex": "0x0000000000000000", + "tnf64_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + } + ] +} \ No newline at end of file diff --git a/conformance/vectors/tnf8_conformance_v0.json b/conformance/vectors/tnf8_conformance_v0.json index b215615909..e8e24c2b6f 100644 --- a/conformance/vectors/tnf8_conformance_v0.json +++ b/conformance/vectors/tnf8_conformance_v0.json @@ -1,262 +1,2854 @@ { - "schema": "t27-conformance/v0.1", - "format": "TNF8", - "ssot": "specs/numeric/tnf8.t27", - "anchor_identity": "phi^2 + 1/phi^2 = 3", - "anchor_check": { - "value": 3.0, - "expected": 3.0, - "ieee754_exact": true - }, - "exp_trits": 3, - "mant_bits": 4, - "exp_offset": 13, - "offset_max": 26, - "width_rule": "1 + 3 + 4 = 8", - "note": "probes are exactly representable in both the rung and f64 (powers of two and 1.5*2^e within range), so every abs_error is exactly zero by construction", - "n_vectors": 22, - "vectors": [ - { - "name": "pos_zero", - "input_f64": 0.0, - "input_f64_hex": "0x0000000000000000", - "tnf8_bits_int": 0, - "tnf8_bits_hex": "0x0", - "decoded_f64": 0.0, - "decoded_f64_hex": "0x0000000000000000", - "abs_error": 0.0, - "category": "zero" + "schema": "t27-conformance/v0.1", + "format": "TNF8", + "format_name": "TNF8", + "bitexact": true, + "format_notes": "GoldenFloat phi-aligned radix-2 float S1E3M4, bias 13. IEEE-style specials at top exponent", + "catalog": { + "id": "tnf8", + "bits": 8, + "s": 1, + "e": 3, + "m": 4, + "bias": 13, + "storage": "u8", + "cluster": "GoldenFloat", + "status": "Verified", + "standard": "this work; e is 3 balanced-ternary TRITS not bits (4.75 bits equivalent); width rule 1+Et+M=N; post-route XC7A200T 50 LUT 153.2 MHz, no DSP, 1 cycle", + "use_case": "fixed-field ternary-exponent ladder; no regime codec", + "gf_relation": "self", + "source": "specs/numeric/tnf8.t27", + "phi_distance": 0.571 }, - { - "name": "pow2_-12", - "input_f64": 0.000244140625, - "input_f64_hex": "0x3f30000000000000", - "tnf8_bits_int": 16, - "tnf8_bits_hex": "0x10", - "decoded_f64": 0.000244140625, - "decoded_f64_hex": "0x3f30000000000000", - "abs_error": 0.0, - "category": "normal" + "ssot": "https://github.com/gHashTag/t27/blob/master/conformance/FORMAT-SPEC-001.json", + "preprint": "https://arxiv.org/abs/2606.05017", + "anchor_identity": "phi^2 + 1/phi^2 = 3", + "anchor_check": { + "value": null, + "expected": 3.0, + "ieee754_exact": false, + "note": "3.0 is not an exact grid point of this format at this width" }, - { - "name": "neg_pow2_-12", - "input_f64": -0.000244140625, - "input_f64_hex": "0xbf30000000000000", - "tnf8_bits_int": 528, - "tnf8_bits_hex": "0x210", - "decoded_f64": -0.000244140625, - "decoded_f64_hex": "0xbf30000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-12", - "input_f64": 0.0003662109375, - "input_f64_hex": "0x3f38000000000000", - "tnf8_bits_int": 24, - "tnf8_bits_hex": "0x18", - "decoded_f64": 0.0003662109375, - "decoded_f64_hex": "0x3f38000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_-6", - "input_f64": 0.015625, - "input_f64_hex": "0x3f90000000000000", - "tnf8_bits_int": 112, - "tnf8_bits_hex": "0x70", - "decoded_f64": 0.015625, - "decoded_f64_hex": "0x3f90000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-6", - "input_f64": -0.015625, - "input_f64_hex": "0xbf90000000000000", - "tnf8_bits_int": 624, - "tnf8_bits_hex": "0x270", - "decoded_f64": -0.015625, - "decoded_f64_hex": "0xbf90000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-6", - "input_f64": 0.0234375, - "input_f64_hex": "0x3f98000000000000", - "tnf8_bits_int": 120, - "tnf8_bits_hex": "0x78", - "decoded_f64": 0.0234375, - "decoded_f64_hex": "0x3f98000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_-1", - "input_f64": 0.5, - "input_f64_hex": "0x3fe0000000000000", - "tnf8_bits_int": 192, - "tnf8_bits_hex": "0xc0", - "decoded_f64": 0.5, - "decoded_f64_hex": "0x3fe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_-1", - "input_f64": -0.5, - "input_f64_hex": "0xbfe0000000000000", - "tnf8_bits_int": 704, - "tnf8_bits_hex": "0x2c0", - "decoded_f64": -0.5, - "decoded_f64_hex": "0xbfe0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e-1", - "input_f64": 0.75, - "input_f64_hex": "0x3fe8000000000000", - "tnf8_bits_int": 200, - "tnf8_bits_hex": "0xc8", - "decoded_f64": 0.75, - "decoded_f64_hex": "0x3fe8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_0", - "input_f64": 1.0, - "input_f64_hex": "0x3ff0000000000000", - "tnf8_bits_int": 208, - "tnf8_bits_hex": "0xd0", - "decoded_f64": 1.0, - "decoded_f64_hex": "0x3ff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "neg_pow2_0", - "input_f64": -1.0, - "input_f64_hex": "0xbff0000000000000", - "tnf8_bits_int": 720, - "tnf8_bits_hex": "0x2d0", - "decoded_f64": -1.0, - "decoded_f64_hex": "0xbff0000000000000", - "abs_error": 0.0, - "category": "unity" - }, - { - "name": "onehalf_2e0", - "input_f64": 1.5, - "input_f64_hex": "0x3ff8000000000000", - "tnf8_bits_int": 216, - "tnf8_bits_hex": "0xd8", - "decoded_f64": 1.5, - "decoded_f64_hex": "0x3ff8000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_1", - "input_f64": 2.0, - "input_f64_hex": "0x4000000000000000", - "tnf8_bits_int": 224, - "tnf8_bits_hex": "0xe0", - "decoded_f64": 2.0, - "decoded_f64_hex": "0x4000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_1", - "input_f64": -2.0, - "input_f64_hex": "0xc000000000000000", - "tnf8_bits_int": 736, - "tnf8_bits_hex": "0x2e0", - "decoded_f64": -2.0, - "decoded_f64_hex": "0xc000000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e1", - "input_f64": 3.0, - "input_f64_hex": "0x4008000000000000", - "tnf8_bits_int": 232, - "tnf8_bits_hex": "0xe8", - "decoded_f64": 3.0, - "decoded_f64_hex": "0x4008000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_6", - "input_f64": 64.0, - "input_f64_hex": "0x4050000000000000", - "tnf8_bits_int": 304, - "tnf8_bits_hex": "0x130", - "decoded_f64": 64.0, - "decoded_f64_hex": "0x4050000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_6", - "input_f64": -64.0, - "input_f64_hex": "0xc050000000000000", - "tnf8_bits_int": 816, - "tnf8_bits_hex": "0x330", - "decoded_f64": -64.0, - "decoded_f64_hex": "0xc050000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e6", - "input_f64": 96.0, - "input_f64_hex": "0x4058000000000000", - "tnf8_bits_int": 312, - "tnf8_bits_hex": "0x138", - "decoded_f64": 96.0, - "decoded_f64_hex": "0x4058000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "pow2_12", - "input_f64": 4096.0, - "input_f64_hex": "0x40b0000000000000", - "tnf8_bits_int": 400, - "tnf8_bits_hex": "0x190", - "decoded_f64": 4096.0, - "decoded_f64_hex": "0x40b0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "neg_pow2_12", - "input_f64": -4096.0, - "input_f64_hex": "0xc0b0000000000000", - "tnf8_bits_int": 912, - "tnf8_bits_hex": "0x390", - "decoded_f64": -4096.0, - "decoded_f64_hex": "0xc0b0000000000000", - "abs_error": 0.0, - "category": "normal" - }, - { - "name": "onehalf_2e12", - "input_f64": 6144.0, - "input_f64_hex": "0x40b8000000000000", - "tnf8_bits_int": 408, - "tnf8_bits_hex": "0x198", - "decoded_f64": 6144.0, - "decoded_f64_hex": "0x40b8000000000000", - "abs_error": 0.0, - "category": "normal" - } - ] -} + "round_trip_policy": "decode: exact bits->f64 (exhaustive). encode (reference): round-nearest-ties-even; overflow per format convention. abs_error 0 for representable values.", + "vector_mode": "exhaustive", + "n_vectors": 256, + "max_finite": 0.01513671875, + "vectors": [ + { + "name": "code_0x00", + "input_f64": 0.0, + "input_f64_hex": "0x0000000000000000", + "tnf8_bits_hex": "0x00", + "tnf8_bits_int": 0, + "decoded_f64": 0.0, + "decoded_f64_hex": "0x0000000000000000", + "abs_error": 0.0, + "category": "zero" + }, + { + "name": "code_0x01", + "input_f64": 1.52587890625e-05, + "input_f64_hex": "0x3EF0000000000000", + "tnf8_bits_hex": "0x01", + "tnf8_bits_int": 1, + "decoded_f64": 1.52587890625e-05, + "decoded_f64_hex": "0x3EF0000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x02", + "input_f64": 3.0517578125e-05, + "input_f64_hex": "0x3F00000000000000", + "tnf8_bits_hex": "0x02", + "tnf8_bits_int": 2, + "decoded_f64": 3.0517578125e-05, + "decoded_f64_hex": "0x3F00000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x03", + "input_f64": 4.57763671875e-05, + "input_f64_hex": "0x3F08000000000000", + "tnf8_bits_hex": "0x03", + "tnf8_bits_int": 3, + "decoded_f64": 4.57763671875e-05, + "decoded_f64_hex": "0x3F08000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x04", + "input_f64": 6.103515625e-05, + "input_f64_hex": "0x3F10000000000000", + "tnf8_bits_hex": "0x04", + "tnf8_bits_int": 4, + "decoded_f64": 6.103515625e-05, + "decoded_f64_hex": "0x3F10000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x05", + "input_f64": 7.62939453125e-05, + "input_f64_hex": "0x3F14000000000000", + "tnf8_bits_hex": "0x05", + "tnf8_bits_int": 5, + "decoded_f64": 7.62939453125e-05, + "decoded_f64_hex": "0x3F14000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x06", + "input_f64": 9.1552734375e-05, + "input_f64_hex": "0x3F18000000000000", + "tnf8_bits_hex": "0x06", + "tnf8_bits_int": 6, + "decoded_f64": 9.1552734375e-05, + "decoded_f64_hex": "0x3F18000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x07", + "input_f64": 0.0001068115234375, + "input_f64_hex": "0x3F1C000000000000", + "tnf8_bits_hex": "0x07", + "tnf8_bits_int": 7, + "decoded_f64": 0.0001068115234375, + "decoded_f64_hex": "0x3F1C000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x08", + "input_f64": 0.0001220703125, + "input_f64_hex": "0x3F20000000000000", + "tnf8_bits_hex": "0x08", + "tnf8_bits_int": 8, + "decoded_f64": 0.0001220703125, + "decoded_f64_hex": "0x3F20000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x09", + "input_f64": 0.0001373291015625, + "input_f64_hex": "0x3F22000000000000", + "tnf8_bits_hex": "0x09", + "tnf8_bits_int": 9, + "decoded_f64": 0.0001373291015625, + "decoded_f64_hex": "0x3F22000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0A", + "input_f64": 0.000152587890625, + "input_f64_hex": "0x3F24000000000000", + "tnf8_bits_hex": "0x0A", + "tnf8_bits_int": 10, + "decoded_f64": 0.000152587890625, + "decoded_f64_hex": "0x3F24000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0B", + "input_f64": 0.0001678466796875, + "input_f64_hex": "0x3F26000000000000", + "tnf8_bits_hex": "0x0B", + "tnf8_bits_int": 11, + "decoded_f64": 0.0001678466796875, + "decoded_f64_hex": "0x3F26000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0C", + "input_f64": 0.00018310546875, + "input_f64_hex": "0x3F28000000000000", + "tnf8_bits_hex": "0x0C", + "tnf8_bits_int": 12, + "decoded_f64": 0.00018310546875, + "decoded_f64_hex": "0x3F28000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0D", + "input_f64": 0.0001983642578125, + "input_f64_hex": "0x3F2A000000000000", + "tnf8_bits_hex": "0x0D", + "tnf8_bits_int": 13, + "decoded_f64": 0.0001983642578125, + "decoded_f64_hex": "0x3F2A000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0E", + "input_f64": 0.000213623046875, + "input_f64_hex": "0x3F2C000000000000", + "tnf8_bits_hex": "0x0E", + "tnf8_bits_int": 14, + "decoded_f64": 0.000213623046875, + "decoded_f64_hex": "0x3F2C000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x0F", + "input_f64": 0.0002288818359375, + "input_f64_hex": "0x3F2E000000000000", + "tnf8_bits_hex": "0x0F", + "tnf8_bits_int": 15, + "decoded_f64": 0.0002288818359375, + "decoded_f64_hex": "0x3F2E000000000000", + "abs_error": 0.0, + "category": "subnormal" + }, + { + "name": "code_0x10", + "input_f64": 0.000244140625, + "input_f64_hex": "0x3F30000000000000", + "tnf8_bits_hex": "0x10", + "tnf8_bits_int": 16, + "decoded_f64": 0.000244140625, + "decoded_f64_hex": "0x3F30000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x11", + "input_f64": 0.0002593994140625, + "input_f64_hex": "0x3F31000000000000", + "tnf8_bits_hex": "0x11", + "tnf8_bits_int": 17, + "decoded_f64": 0.0002593994140625, + "decoded_f64_hex": "0x3F31000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x12", + "input_f64": 0.000274658203125, + "input_f64_hex": "0x3F32000000000000", + "tnf8_bits_hex": "0x12", + "tnf8_bits_int": 18, + "decoded_f64": 0.000274658203125, + "decoded_f64_hex": "0x3F32000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x13", + "input_f64": 0.0002899169921875, + "input_f64_hex": "0x3F33000000000000", + "tnf8_bits_hex": "0x13", + "tnf8_bits_int": 19, + "decoded_f64": 0.0002899169921875, + "decoded_f64_hex": "0x3F33000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x14", + "input_f64": 0.00030517578125, + "input_f64_hex": "0x3F34000000000000", + "tnf8_bits_hex": "0x14", + "tnf8_bits_int": 20, + "decoded_f64": 0.00030517578125, + "decoded_f64_hex": "0x3F34000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x15", + "input_f64": 0.0003204345703125, + "input_f64_hex": "0x3F35000000000000", + "tnf8_bits_hex": "0x15", + "tnf8_bits_int": 21, + "decoded_f64": 0.0003204345703125, + "decoded_f64_hex": "0x3F35000000000000", + "abs_error": 0.0, + "category": "normal" + }, + { + "name": "code_0x16", + "input_f64": 0.000335693359375, + "input_f64_hex": "0x3F36000000000000", + "tnf8_bits_hex": "0x16", + "tnf8_bits_int": 22, + "decoded_f64": 0.000335693359375, + 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"0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xF8", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "tnf8_bits_hex": "0xF8", + "tnf8_bits_int": 248, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xF9", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "tnf8_bits_hex": "0xF9", + "tnf8_bits_int": 249, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFA", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "tnf8_bits_hex": "0xFA", + "tnf8_bits_int": 250, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFB", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "tnf8_bits_hex": "0xFB", + "tnf8_bits_int": 251, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFC", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "tnf8_bits_hex": "0xFC", + "tnf8_bits_int": 252, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFD", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "tnf8_bits_hex": "0xFD", + "tnf8_bits_int": 253, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFE", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "tnf8_bits_hex": "0xFE", + "tnf8_bits_int": 254, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + }, + { + "name": "code_0xFF", + "input_f64": "NaN", + "input_f64_hex": "0x7FF8000000000000", + "tnf8_bits_hex": "0xFF", + "tnf8_bits_int": 255, + "decoded_f64": "NaN", + "decoded_f64_hex": "0x7FF8000000000000", + "abs_error": "NaN", + "category": "nan" + } + ] +} \ No newline at end of file