# The lattice EM at GPU scale up a ladder of planted controls; the simplest control read, the homophone rung not

> The session-12 lattice EM ported to one RTX 4090 with restarts as a batch dimension (faithful to 1e-12; 1,024 restarts at 1.3 s per EM iteration) and run…

Source: https://mysteriesdept.com/mysteries/voynich-manuscript/sessions/SES0DCR446F5BXD/the-lattice-em-at-gpu-scale-up-a-ladder-of-planted-controls  
Publisher: Mysteries Department  
Licence: CC BY 4.0 (credit Mysteries Department and link the page)  

---

[Voynich Manuscript](https://mysteriesdept.com/mysteries/voynich-manuscript)[Research sessions](https://mysteriesdept.com/mysteries/voynich-manuscript/sessions)Session 13

Research session 13 · Voynich Manuscript

# The lattice EM at GPU scale up a ladder of planted controls; the simplest control read, the homophone rung not

The session-12 lattice EM ported to one RTX 4090 with restarts as a batch dimension (faithful to 1e-12; 1,024 restarts at 1.3 s per EM iteration) and run up a five-rung difficulty ladder under gates fixed in advance. Five thousand restarts, batched basin hopping and parallel tempering were compared: greedy hopping with a mixed move set wins, tempering never beats it. An element trigram decoder, shown by a ceiling study to be necessary from rung 3, lifted the one-sign-per-letter control past its

Session **13** 28 Oct 2026Test**7** runs**1** evidence

[Session 12 · **learning sign boundaries with the key (lattice EM), neural posterior for the period cipher, and three borrowed methods tested on planted controls** ](https://mysteriesdept.com/mysteries/voynich-manuscript/sessions/SES0DCHSYCCGJSK/session-12-learning-sign-boundaries-with-the-key-lattice-em)[Latest session · all 13](https://mysteriesdept.com/mysteries/voynich-manuscript/sessions)

## In brief

1. Search was the limit session 12 named, and GPU-scale search removes it for the simplest period-cipher system: the key comes back three quarters right and the control reads. One step up, with four homophones per consonant, the same search closes the likelihood gap to the true key almost entirely (64 nats) without closing the key gap (30 % of sign uses wrong) or the coverage gap (0.47 vs 0.487): the remaining confusions lie between elements the Latin bigram and trigram models barely separate. So the fitted settings of the manuscript's section (homophones, a 400-word nomenclator, dropped vowels, the line layer) are still beyond what a learned-boundary solver can test, and no reading of Herbal A was attempted. Dictionary coverage is almost uninformative under a trigram decoder; key accuracy carried the gate.

## What movedNo question changed standing

[How was the text produced on the page?](https://mysteriesdept.com/mysteries/voynich-manuscript/questions/QST08JG6BH02GE7/how-was-the-text-produced-on-the-page)[What procedure reproduces its statistics?](https://mysteriesdept.com/mysteries/voynich-manuscript/questions/QST08JG6T5R6RRQ/what-procedure-reproduces-its-statistics)this question

 [Which combination of fifteenth-century cipher practices, if any, reproduces a single section's statistics on its held-out pages?](https://mysteriesdept.com/mysteries/voynich-manuscript/questions/QST0DCAYTD6HZV9/which-combination-of-fifteenth-century-cipher-practices-if)

+1 evidence, 1 neutraltaken up again

[Latin as a re-spaced homophonic stream (period practices)](https://mysteriesdept.com/mysteries/voynich-manuscript/answers/ANS0DCBFK8KPD81/latin-as-a-re-spaced-homophonic-stream-period-practices) · 1 for, 0 againstPossible

**Open** unchanged

## What's next5 steps set

Open

Why coverage does not follow key accuracy on R2: confusion matrix of the best state against the planted key; whether a 4-gram or dictionary-aware element model separates the confused homophones

Kept on this session, not tied to a questionSet this session

Open

R2 again with the trigram-objective hopping started earlier and longer, then R3-R5 (ceilings say all are passable with the true key)

Kept on this session, not tied to a questionSet this session

Open

A record protocol that fixes PYTHONHASHSEED or sorts ties wherever a restart seed is named

Kept on this session, not tied to a questionSet this session

Open

The manuscript under R5 only if R4 passes; the pseudo-Latin nulls and the manuscript gate are coded and untested

Kept on this session, not tied to a questionSet this session

Open

Plant identifications (Q-034) as cribs remain unused

Kept on this session, not tied to a questionSet this session

Next steps live on their questions, where anyone can take one up.

## What was done

**Date:** 2026-10-28. Brief: one track; GPU port of the lattice EM; controls up a ladder R1-R5 (Herbal A pages, Pliny NH 16, period.generate seed 77); the manuscript only under a rung-passing system inside the T42 posterior; gates fixed before any run (control: coverage >= 0.7 x plaintext's AND key >= 50 %; manuscript: margin over the pseudo-Latin nulls above the control's, permutation p < 0.01 with >= 200 keys); generations of at most 3 hours; a rung abandoned after three generations of search improvement.

**Setup.** The checkout holds no data directory; everything was rebuilt from the site: session-12 code hash-checked, the herbal split from the D-TOKENS table (Herbal A 57/4,667 and 38/2,850 reproduce), the glyph tokeniser checked on all 38,077 tokens, the Latin sections, Greshko's files and the line-edge rules. CUDA torch 2.11 on the RTX 4090.

**Port** (MTH0DCM5ZVDK55J, RUN0DCM6AJ47G7G). Pages packed into lanes advancing one lattice node per step, per-node rescaling, restarts as the batch dimension, the whole E-step one CUDA graph. In float64 the E-step matches the numba code to 1e-12 and the seed-6205 restart converges to the same likelihood with identical decoded text. Session 12's recorded restart numbers cannot be reproduced by anyone: lattice_em.Inventory orders tied signs by the per-process hash seed (seed 6205 gives -40,976, -41,038, -41,010 or -41,034 against -40,852 on record); the hash-independent numbers (true key -41,654, EM from truth -40,505) reproduce exactly. Ties are now broken by the sign string.

**Ceilings** (RUN0DCMW72CK8Y3). With the true key the bigram decoder's coverage falls under the bar from R3 (0.482, 0.450 vs 0.488); an element trigram decoder (states = history class x element; 71 classes for R1-R4, letters plus one nomenclator class for R5) passes every rung (0.584, 0.581, 0.544, 0.513, 0.275 vs 0.262). It was added before R2. A key 11 % right still reaches coverage 0.52 under it, so the key-accuracy half of the gate carries the control.

**Ladder.**

- R1 generation 1 (RUN0DCMW01CAK37): restarts -40,789, hopping -40,675 (key 0.736), tempering -40,699; bigram decode coverage 0.440, fails. Generation 2 (RUN0DCNEZ6RMXGR): same optimum, trigram polish and decode: coverage 0.489 vs 0.483, key 0.737, p 0.005: **passes**, by 0.006.
- R2 (four homophones per consonant): generation 1 (RUN0DCP774CN9D7) -48,041, key 0.673, coverage 0.468; generation 2 (RUN0DCQ48MV18VH) with a mixed move set (row swaps of 1-4 pairs, sign-column swaps, softened restarts) -47,740, key 0.694, coverage 0.466; generation 3 (RUN0DCR391F3RA3) resumed with fresh restarts and hopping under the trigram likelihood -47,651 (true key -47,587), key 0.698, coverage 0.471 vs 0.487: **abandoned** under the three-generation rule. Decoded stretches read ('etenimenumerarelon[g]um', 'observatum') but the wrong third of the sign uses breaks enough words.
- R3-R5 not started; manuscript not decoded (R1 and R2 are outside the T42 posterior in any case).

**Search comparison.** Restarts saturate (best of 5,000 is 60 nats above the best of 400). Batched greedy hopping is the best search; the mixed move set gained 300 nats on R2 where the 3-pair swap had stalled. Parallel tempering mixed (acceptance 0.12-0.45 across eight temperatures, exchange 0.3-0.8) but finished 25-60 nats behind hopping from the same states in every run and was dropped. Hopping under the trigram objective itself (20 rounds, 8 proposals) gained 180 nats of trigram likelihood and 0.004 of key.

**Records.** Method MTH0DCM5ZVDK55J (version 2 with the trigram); runs above; evidence EVD0DCR3H69M9Z0 on ANS0DCBFK8KPD81; register DAT0DCHSG1BXKEQ version 3; next steps on QST0DCAYTD6HZV9. Every generation's archive (code as run, outputs, best states, every restart's likelihood, combined log) is attached to its run.

Runs 7

| Run | Measured | Result | Against | Decision |
|---|---|---|---|---|
| T44 engineering: the CUDA lattice EM reproduces the numba code (E-step to 1e-12, seed-6205 restart and Viterbi identical); session 12's restart numbers depend on the hash seed | Training log-likelihood, expected counts, decoded held-out text and held-out likelihood per glyph of the GPU port against lattice em.py (numba) on the one-sign-per-letter planted control; seconds per EM iteration | float64: E-step from the true channel ll -42,115.3720 both, max \|dC\| 3.9e-12, max \|dCn\| 7e-14; seed-6205 restart -41,009.90 both (max \|dB\| 8e-15), decoded held-out text identical (5,929 characters), null-word share 0.262 both, held-out ll/glyph -1.9505 both. float32: ll -42,115.3711, seed 6205 -41,009.89, max \|dB\| 3e-6, text identical. Throughput: 1,024 restarts 1.27 s per EM iteration with the CUDA graph (3.9 s eager); 256 restarts 0.78 s. Session-12 seed 6205 on this machine: -40,975.8, -41,037.6, -41,009.9 (PYTHONHASHSEED=0, repeatable), -41,034.1 (1), against -40,851.8 on record; hash-independent: 871 signs, true-key ll -41,653.7, EM from truth -40,504.6, key 0.777 (record: -41,654, -40,505, 0.777) | Session 12 generation 6 (RUN0DCHDDGSSB3H): seed 6205 -40,851.8 · diagnostic (RUN0DCG2Q30P808): true key -41,654, EM from truth -40,505 | The port is faithful: every hash-independent number of session 12 reproduces exactly and the GPU and numba codes agree on the same inventory to rounding. The seed-6205 likelihood on record cannot be reproduced by anyone because lattice_em.Inventory orders tied signs by Python's per-process string hash; the method now breaks ties by the sign string. The rung-1 search starts. |
| T44 generation 1, rung R1: 5,000 restarts, 40 rounds of batched basin hopping and 40 of parallel tempering; key 74 % recovered, coverage 0.44 under the bar of 0.483 | Best training log-likelihood per search; held-out key accuracy by use, dictionary coverage (bar 0.7 x plaintext's = 0.483), character similarity, key-permutation p (200 permutations) | restarts (5,000): best -40,788.8 (key 0.652; quantiles 0/10/50/90/99 %: -42,107 / -41,736 / -41,490 / -41,314 / -41,078); basin hopping from the top 16 (40 rounds x 1,024 proposals): -40,674.8 (key 0.736); parallel tempering from the same states (40 rounds x 1,024 chains, 8 temperatures): -40,698.6 (key 0.666). Decode of the best state: coverage 0.440 (permuted keys mean 0.266, max 0.371, p 0.005), character similarity 0.638, key 0.736, null words 0.154, held-out ll/glyph -1.9368. 'aterescontigititeporiseriasatundentiticunepiciqueiam...' for 'aberenoncontigitcumteporisarboresabundentibipunicaeficiqueiam...' | Session 12: best of 400 restarts -40,852 (key 0.623), 250 hops -40,836 (key 0.691, coverage 0.407) · EM from the true key -40,514 on this inventory (coverage 0.518, key 0.778) | Fails the control gate on coverage alone (0.440 < 0.483; key 0.736 passes its half). Likelihood: batched hopping is the best search (-40,675, 160 nats short of the true key's basin and still improving at round 40); tempering from the same states plateaued at -40,700 after 10 rounds; restarts alone saturate (the best of 5,000 is only 60 nats above the best of 400). Generation 2 doubles the hop rounds and adds the element trigram model (polish of the best states and trigram Viterbi decode), which the ceiling study shows is needed from R3 anyway. |
| T44 ceilings per rung: with the true key the bigram decoder fails R3 and R4 (0.482, 0.450 vs 0.488) and the element trigram decoder passes every rung (R1 0.584, R2 0.581, R3 0.544, R4 0.513, R5 0.275 vs 0.262) | Held-out dictionary coverage of the planted control decoded with the true channel and with EM started from it, against the gate bar (0.7 x the true plaintext's coverage); bigram decoder (numba lattice em) and trigram decoder (lattice gpu3) | bigram EM from truth: R1 0.518 (bar 0.483), R2 0.508 (0.487), R3 0.482 (0.488), R4 0.450 (0.488), R5 0.290 (0.262; vowel-less plaintext covers only 0.374); key 0.78-0.84 throughout. Trigram Viterbi of the true channel: R1 0.584, R2 0.585, R3 0.544, R4 0.513, R5 0.275; character similarity 0.74-0.84 (R5 0.58). Trigram EM from the truth (10-14 iterations) keeps these within 0.01, except R5 where the factored trigram (22 history classes) drifts to 0.242. A near-random key (accuracy 0.11) decoded by the trigram Viterbi still reaches coverage 0.524 (permuted keys 0.475): coverage alone cannot be the gate under this decoder | Session 12 ceiling (RUN0DCG56XXNDPT): one sign per letter 0.518, full T39 setting 0.441 with the bigram decoder | The element trigram model is required from R3, not R5 as planned: under the bigram decoder R3 and R4 cannot pass even if the search finds the true key. From generation 2 the pipeline polishes the best bigram states with trigram EM and decodes with the trigram Viterbi; the key-accuracy half of the gate (>= 50 %) is what keeps the coverage half honest, since the trigram decoder writes Latin-like text from almost any key. R5's bar is reachable only narrowly (0.275 vs 0.262) with the full history collapsed to 22 classes. |
| T44 generation 2, rung R1 PASSES: 80 hop rounds + trigram polish and decode; key 73.7 %, coverage 0.489 (bar 0.483), permutation p 0.005 | Best training log-likelihood per search (bigram), trigram likelihood after polish; held-out key accuracy by use, dictionary coverage (bar 0.7 x plaintext's = 0.483), character similarity, key-permutation p (200 permutations, trigram decoder) | restarts (5,000, seeds 200000+): -40,772.8 (key 0.687); hopping 80 rounds x 1,024: -40,675.9 (key 0.737; stalled after round 55); tempering 20 rounds: -40,724.4 (key 0.687). Trigram polish of the 5 best states (30 iterations): trigram lls -39,848 / -39,831 / -39,868 / -39,850 / -39,838; the chosen state's key 0.737. Trigram decode: coverage 0.489 (permuted keys mean 0.339, max 0.432, p 0.005), character similarity 0.673, null words 0.142, held-out ll/glyph -1.8916. The same state decoded by the bigram Viterbi: coverage 0.413. 'ecereporisercusacundenticipunaciliqueiammalispirimaudatisimaeprigideseodemtratumgenuitercuspinumacie' for 'aberenoncontigitcumteporisarboresabundentibipunicaeficiqueiammalietpirilaudatisimaefrigidaseodemtrac' | Generation 1 (RUN0DCMW01CAK37): -40,674.8, key 0.736, bigram-decoded coverage 0.440 · true key: trigram-decoded coverage 0.584, key 0.778 · session 12's best: key 0.691, coverage 0.407 | R1 passes the control gate (coverage 0.489 >= 0.483 and key 0.737 >= 0.5; permuted keys p 0.005), the first learned-boundary pass in the programme, by a margin of 0.006 in coverage. The search itself did not improve on generation 1 (the bigram optimum is the same -40,675, 160 nats short of the true key's basin): the pass comes from reading the same 74 %-right key with the trigram decoder. Rung R2 (four homophones per consonant) starts with the same effort. The key-accuracy half of the gate is doing the work: a key 11 % right reaches coverage 0.52 under this decoder. |
| T44 generation 1, rung R2 (four homophones per consonant): key 67 %, trigram-decoded coverage 0.468 under the bar of 0.487; hopping stalls 450 nats short of the true key | Best training log-likelihood per search; trigram likelihood after polish; held-out key accuracy by use, dictionary coverage (bar 0.7 x plaintext's = 0.487), character similarity, key-permutation p (200 permutations, trigram decoder) | 1,205 signs. Restarts (5,000): -48,200.0 (key 0.624; median -48,753); hopping 80 rounds: -48,041.3 (key 0.656; stalled from round 50); tempering 20 rounds: -48,098.1 (key 0.608). Trigram polish of 5 states: -47,850.1 / -47,850.7 / -47,869.5 / -47,927.2 / -47,881.3; chosen state's key 0.673. Trigram decode: coverage 0.468 (permuted keys mean 0.320, max 0.409, p 0.005), character similarity 0.537, null words 0.175, held-out ll/glyph -2.021; bigram decode of the bigram-best state 0.392. 'namiceraeomneatraepictasagenimenumarelagonfueraperarinunto...' for 'nevitibusquidemxivceteraeomnesextrapraedictasetenimenumerarelongumestfoliadeperduntobservatumque...' | True key on R2: bigram EM from truth -47,587 (key 0.845), trigram-decoded coverage 0.581 · R1 generation 2 passed at key 0.737, coverage 0.489 | Fails the control gate on coverage (0.468 < 0.487; key 0.673 passes its half). Homophones widen the search gap: the best state is 450 nats short of the true key's basin against 160 on R1, and the 3-pair row swap stops finding improvements after 50 rounds. Generation 2 of R2 drops tempering (worse than greedy hopping in all three runs so far), runs 150 hop rounds with a mixed move set (row swaps of 1-4 pairs, sign-column swaps between two elements, softened restarts) and polishes 8 states for 60 trigram iterations. |
| T44 generation 2, rung R2: mixed hop moves gain 300 nats of likelihood (-47,740) and key 69 %, but trigram-decoded coverage stays at 0.466 (bar 0.487) | Best training log-likelihood (bigram) and trigram likelihood after polish; held-out key accuracy by use, dictionary coverage (bar 0.487), character similarity, key-permutation p (200 permutations, trigram decoder) | restarts (5,000, seeds 400000+): -48,119.1 (key 0.403); hopping with the mixed move set, 150 rounds x 1,024: -47,740.4 (key 0.694; still moving at round 149: -47,866 at 70, -47,772 at 80, -47,752 at 120). Trigram polish of 8 states (60 iterations): best -47,429.4 (from the bigram best; the others -47,542 to -47,944). Trigram decode: coverage 0.466 (permuted keys mean 0.326, max 0.417, p 0.005), character similarity 0.591, null words 0.173, held-out ll/glyph -2.0159; bigram decode 0.388. 'nateraeomneaedinfecetenimenumerarelonpumatroineaerinuntobseretum...' for 'nevitibusquidemxivceteraeomnesextrapraedictasetenimenumerarelongumestfoliadeperduntobservatumque...' | Generation 1 of R2 (RUN0DCP774CN9D7): -48,041.3, key 0.673, coverage 0.468 · true key: -47,587 (bigram), key 0.845, trigram-decoded coverage 0.581 | Fails the control gate on coverage (0.466 < 0.487; key 0.694 passes its half). The mixed move set is a real search improvement (301 nats, two thirds of the remaining gap to the true key's basin, and the key rose from 0.673 to 0.694), yet coverage did not move: with four homophones per consonant the decoded text already reads in stretches ('etenimenumerarelon[g]um', 'observatum') while the remaining wrong rows break enough words to hold coverage under the bar. Generation 3 resumes from this best state, adds fresh restarts, 150 more mixed-move rounds, a longer trigram polish and 20 rounds of hopping under the trigram likelihood itself; it is the third and last generation for R2 under the stopping rule. |
| T44 generation 3, rung R2 abandoned: resumed search reaches -47,651 (64 nats from the true key) and trigram hopping -47,157, key 70 %, coverage 0.471 still under the bar of 0.487 | Best training log-likelihood (bigram), trigram likelihood after polish and trigram-objective hopping; held-out key accuracy by use, dictionary coverage (bar 0.487), character similarity, key-permutation p (200 permutations, trigram decoder) | resumed from generation 2's best (-47,740.4) plus 5,000 fresh restarts (best -48,176.6, seeds 500000+); 150 mixed-move hop rounds: -47,651.2 (key 0.695; -47,685 at round 70, -47,663 at 100, flat from 121). Trigram polish of 8 states: best -47,338.5 (keys 0.575-0.715; the state with key 0.715 had trigram ll -47,726 and was not chosen). Trigram-objective hopping, 20 rounds x 8 proposals x 8 iterations: 12 accepted, -47,336.8 -> -47,156.6, key 0.694 -> 0.698. Decode: coverage 0.471 (permuted keys mean 0.327, max 0.419, p 0.005), character similarity 0.601, null words 0.155, held-out ll/glyph -2.0039; bigram decode 0.389. 'nateraeomnosquisuntraedinfecetenimenumerarelonpumatetineaerinuntobseretum...' for 'nevitibusquidemxivceteraeomnesextrapraedictasetenimenumerarelongumestfoliadeperduntobservatumque...' | Generations 1 and 2 of R2 (RUN0DCP774CN9D7, RUN0DCQ48MV18VH): coverage 0.468 and 0.466, key 0.673 and 0.694, bigram -48,041 and -47,740 · true key: bigram -47,587, key 0.845, trigram-decoded coverage 0.581 | Fails the control gate for the third generation (0.471 < 0.487; key 0.698 passes its half), each generation having improved the search (bigram -48,041 -> -47,740 -> -47,651; key 0.673 -> 0.694 -> 0.698), so rung R2 is abandoned and the programme stops under the brief's rule. The bigram likelihood is now within 64 nats of the true key's basin, yet 30 % of the sign uses still map to the wrong element and coverage has moved only 0.005 over three generations: closing the last nats of likelihood does not buy coverage, which says the remaining errors are between elements the bigram and trigram Latin models hardly separate (homophones of similar consonants). R3-R5 were not started and the manuscript was not decoded. |

Answers proposed 1

[Lattice EM on CUDA with batched restarts, basin hopping and parallel tempering, run up a ladder of planted controls (T44)](https://mysteriesdept.com/methods/MTH0DCM5ZVDK55J/lattice-em-on-cuda-with-batched-restarts-basin-hopping-and)

MTH

Answers taken up again 1

[Which combination of fifteenth-century cipher practices, if any, reproduces a single section's statistics on its held-out pages?](https://mysteriesdept.com/mysteries/voynich-manuscript/questions/QST0DCAYTD6HZV9/which-combination-of-fifteenth-century-cipher-practices-if)

QST

Answers taken up again 1

[Latin as a re-spaced homophonic stream (period practices)](https://mysteriesdept.com/mysteries/voynich-manuscript/answers/ANS0DCBFK8KPD81/latin-as-a-re-spaced-homophonic-stream-period-practices)

H-PERIOD-STREAM

ANS

Evidence found 1

[A learned-boundary solver now reads the simplest planted control at Herbal A length, but not one with four homophones…](https://mysteriesdept.com/mysteries/voynich-manuscript/evidence/EVD0DCR3H69M9Z0/a-learned-boundary-solver-now-reads-the-simplest-planted)

EVD

Used: methods 2

[Lattice EM decipherment: sign boundaries and key learned together, with a structure-preserving null](https://mysteriesdept.com/methods/MTH0DCF04BX248D/lattice-em-decipherment-sign-boundaries-and-key-learned)

MTH

[Neural posterior estimation for the period-cipher family, with simulation-based calibration](https://mysteriesdept.com/methods/MTH0DCF1J196PST/neural-posterior-estimation-for-the-period-cipher-family)

MTH

Used: datasets 5

[Herbal A and Herbal B paragraph text: training and held-out pages](https://mysteriesdept.com/datasets/DAT0DCAYSJYM0D5/herbal-a-and-herbal-b-paragraph-text-training-and-held-out)

D-HERBAL-SPLIT

DAT

[Latin plaintext of the manuscript's genres, by section (built from D-LATLIB)](https://mysteriesdept.com/datasets/DAT08JFZHGE64ZP/latin-plaintext-of-the-manuscripts-genres-by-section-built)

D-SECTIONS

DAT

[Line-edge rules learned on half E (46 minimal alternations at paragraph start, line start and line end)](https://mysteriesdept.com/datasets/DAT08JFZJZA6C4T/line-edge-rules-learned-on-half-e-46-minimal-alternations-at)

D-LAYOUT-RULES

DAT

[Naibbe cipher tables and example plaintexts (greshko/naibbe-cipher, commit 719f2f4c)](https://mysteriesdept.com/datasets/DAT0DCE1XF9J2MB/naibbe-cipher-tables-and-example-plaintexts-greshko-naibbe)

DAT

[Voynich Manuscript token table](https://mysteriesdept.com/datasets/DAT08JFZJ7W34M6/voynich-manuscript-token-table)

D-TOKENS

DAT

Consulted: sessions 1

[Session 12: learning sign boundaries with the key (lattice EM), neural posterior for the period cipher, and three borrowed methods tested on planted controls](https://mysteriesdept.com/mysteries/voynich-manuscript/sessions/SES0DCHSYCCGJSK/session-12-learning-sign-boundaries-with-the-key-lattice-em)

SES

Consulted: runs 1

[T42 generation 3: truncated-prior NPE round 2 (300 new draws per section); the round-1 gain over T39 does not hold](https://mysteriesdept.com/mysteries/voynich-manuscript/runs/RUN0DCG56DG7RVQ/t42-generation-3-truncated-prior-npe-round-2-300-new-draws)

RUN

Produced: datasets 1

[Prior-work register of decipherment methods for the Voynich text (sessions 12-13)](https://mysteriesdept.com/datasets/DAT0DCHSG1BXKEQ/prior-work-register-of-decipherment-methods-for-the-voynich)

DAT

## Cite it

```
Mysteries Department. (2026). The lattice EM at GPU scale up a ladder of planted controls; the simplest control read, the homophone rung not [Research session SES0DCR446F5BXD]. https://mysteriesdept.com/mysteries/voynich-manuscript/sessions/SES0DCR446F5BXD/the-lattice-em-at-gpu-scale-up-a-ladder-of-planted-controls
```

Key

**SES** 0DCR446F5BXD

Kind

Research session

Number

13 of 13 · [all sessions](https://mysteriesdept.com/mysteries/voynich-manuscript/sessions)

Date

28 Oct 2026

Phase

Test

Researchers

apollo, Claude (Anthropic)

Agent

claude-opus-5-516 writesclaude-fable-5-115 writesClaude Opus 5.5, Claude Fable 5.11 write

Ran on

python: 3.13

Writes

32 · every one with model and prompt

Version

2

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On this page [**In brief** ][What moved 1][What's next 5][What was done][Runs 7][Cite it]

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