Method · simulation-based inference

Naibbe-family hyper-simulation, section by section

72 variants of the Naibbe cipher (when the table card is drawn, a 150-word codebook, words shuffled within lines, the S-007 line layer) laid into six sections taken separately, scored on statistics that need no page order, each also computed with the first glyph of every word removed. 4,320 simulated sections.

Simulation-based inferenceVersion 1.0Licence MIT4 runsUsed on 1 mystery

Questions it answers

Is it a cipher of a known language?

Code Python

Download module (.py)hyper.pyView source

Runs and results 4 runs

Run	Mystery	Measured	Result	Against
RUN0DC8YG3NV5XE	Voynich	Share of words beginning with the four commonest glyphs / entropy of word-initial glyphs (bits)	top-4 share manuscript vs Naibbe: stars B 0.644 vs 0.638, pharmaceutical A 0.661 vs 0.650, text B 0.616 vs 0.632, biological B 0.688 vs 0.637, herbal B 0.603 vs 0.644, herbal A 0.596 vs 0.642. Whole book: o 20 %, ch 16 %, q 16 %, d 9 % begin words (61 %); qo- 15 %	Plain Latin: top-4 share about 0.37, entropy 4.05 bits
RUN0DC8YCJ2NKDG	Voynich	Held-out statistics (of 12) with \|z\| > 2 for each section's best variant, re-scored on fresh seeds	text B 5 (stay95, codebook, shuffle, layer); herbal B 6 (stay90, codebook, layer); pharmaceutical A 7 (per-unit, codebook, layer); stars B 8 (per-unit, codebook, layer); herbal A 9 (stay50, codebook, layer); biological B 10 (stay95, shuffle, layer)	Picked from the grid on the selection seeds: 4, 5, 7, 8, 7, 9 · plain Latin in the same pages 9-12 · the section's words shuffled across its pages 10-12
RUN0DC8YCX968A6	Voynich	Burst z (topical clustering of the 200 commonest words over pages, no page order used)	manuscript: stars B 38.7, biological B 17.2, herbal A 15.2, text B 14.1, herbal B 6.3, pharmaceutical A 6.0. Naibbe per unit (published) -0.7 to 2.2; keep table p = 0.90: 3.4 to 13.5; p = 0.95: 6.8 to 28.3; p = 0.99: 39 to 94; one table per page: 87 to 265	Plain Latin and published Naibbe · the section's own words shuffled across pages give 0 by construction
RUN0DC8YFNJRFFC	Voynich	MI between a word's last glyph and the next word's first (edge MI, bits); share of words with a one-glyph variant within the next 10 words (twin10); edge MI on word bodies	edge MI: manuscript 0.19-0.32 by section, the 72 variants 0.01-0.10; on bodies 0.11-0.27 against 0.01-0.12. twin10: manuscript 0.24-0.33, variants 0.13-0.19	The section's own words shuffled across its pages: edge MI 0.02-0.08, twin10 0.18-0.27

Applied to

Voynich Manuscript

3 datasetsLatin genre texts, Naibbe cipher tables and example plaintexts (greshko/naibbe-cipher, commit 719f2f4c), ZL3b transcription