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Records the full compression investigation as a repo doc plus the scripts that back every number (real coders, byte-exact lossless round-trips, no straw baselines). One law: recoverable <=> sparse/structured; no method beats K(data), schemes only relocate bits between model and residual columns. Findings (all measured): char-poly = integrity receipt not compressor; Braille/T9 = 4.167 b/B, loses to xz; "16D/583x" GW ringdown = zero-noise self-fit artifact, ~1.5x tying/losing to LPC on noisy strain; frozen-model conservation law (k=3 smallest tape, worst total); Semantic Mass Number = base conversion (1.00-1.10x, bijection); capstone superposition/compressed-sensing cliff (recoverable iff k <= ~d/log N). Honest home for all: receipts/addresses/ recoverability gates (GCCL/RRC), never the ratio column. docs/research/COMPRESSION_HONEST_FINDINGS.md + scripts/compression/ (7 scripts + README). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
19 lines
1.3 KiB
Markdown
19 lines
1.3 KiB
Markdown
# Compression — honest-measurement scripts
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Reproducible experiments behind [`docs/research/COMPRESSION_HONEST_FINDINGS.md`](../../docs/research/COMPRESSION_HONEST_FINDINGS.md).
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Every claim is checked with a real coder and a byte-exact lossless round-trip; no
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straw baselines. Python 3 + numpy only (stdlib `lzma`/`gzip` for baselines).
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| script | what it measures |
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|---|---|
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| `spectral_vs_empirical.py` | Wall 1: rank-k reconstruction of the byte transition matrix never beats raw counts |
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| `entropy_full.py` | order-0/1/2 empirical entropy of a corpus (adaptive-AC target rate) |
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| `ac_roundtrip.py` | real Witten–Neal–Cleary order-2 arithmetic coder; lossless round-trip + bits/byte |
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| `gw_honest_test.py` | GW ringdown parametric fit (handed TRUE params) vs LPC/xz across SNRs — the "583×" gate |
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| `frozen_model_compress.py` | conservation law: frozen model + AC, model-column vs tape-column, self-contained vs amortized |
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| `mass_number_compress.py` | Semantic Mass Number = base conversion (bijection), M1/M2/M3 vs xz |
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| `superposition_recovery.py` | capstone: compressed-sensing recovery vs sparsity — recoverable ⟺ sparse cliff |
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Most default to a local text corpus path; pass a directory as `argv[1]` to point
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elsewhere. `entropy_full.py`/`ac_roundtrip.py` expect an `enwik8` file
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(re-fetch from `mattmahoney.net/dc/enwik8.zip`).
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