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research: restore-only optimum for PR #3042's six-skip words (scoped exact negative, no new κ) - #3114

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mdumitrean:research/rank7-skip-restore-optimum
Oct 17, 2026
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Mister-Meeseeks merged 1 commit into
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mdumitrean:research/rank7-skip-restore-optimum

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Summary

A scoped exact negative on dcharb78's PR #3042 six-skip words (both providers). These are also the words of Nick Petalas's PR #3054. Keep A (with its prelude), B, warps, cut, initial corrections, compensation, start frames, helper ends, removed helpers and buffers fixed. Replace the restore by any scalar gate sequence that PR2833's auditor accepts, and re-solve all frames. Then

cert(W') >= LB_forced + forced restore-phase visits = 10,867,765,164 + 337,923 = 10,868,103,087 = cert(PR3042 words)

PR #3042's restore is optimal in this class. No new κ; no selected-record change.

Proof outline

  1. Auditor semantics. We use only the auditor's forward end-of-restore requirements: restored helpers hold their own input rows, no register keeps a restored input, and targets are untouched. Other final rows are free; appending 0 += 1 or 62 += 70 at FULL passes forward and dual at delta 0.
  2. Forced coordinates come from independence (rank 632).
  3. Forced caps follow from the gate-path argument.
  4. Merge: restore-phase climbs collapse into one end climb.
  5. Delivery and cleaning lemmas.
  6. Departure lemma (dual vectors): if M[O][{r} ∪ {y : L_y ⊆ G}] has full column rank, r cannot leave G.
  7. Carriers and lifts.

Lane K's original screen used a partner-only rank test. The package replaces it with the sound departure lemma and enumerates every entry frame and every first frame. On these words the bound is unchanged. The ablation shows that the full-row lemma is load-bearing: restricting its rows lets eight (1,3) splits through and drops the bound by 15,048.

Verification

python3 -B research/rank7-skip-restore-optimum/run_registered.py      # ~70 s, Python standard library
python3 -B scripts/research_package.py --package research/rank7-skip-restore-optimum

verify.py uses only the standard library:

  • frames_exact.py, a numpy-free port of the certified frame solver. It reproduces both certified optima, the 743/210/94 frame graph that PR Prove the complete joint A/B/restore frame optimum #3065 reports, and LB_forced.
  • Free-algebra restore-entry rows from the vendored PR2833 auditor, the caps, and the classification.

Controls:

census.py adds two empirical controls:

  • a complete single-gate deletion census: 10 exact deletions, all at delta 0;
  • lane K's tail-exchange census: 8,098 candidates per provider, minimum delta 0. The candidate list is re-derived and the records are re-checked on a sample.

Lane K's current bound.py/lbforced.py (the version that takes the supplied M) are pinned in evidence/laneK/ and agree on all eight cross-check cases. Lane K's A/B censuses are cited as local evidence only.

Scope

Open next questions:

  • A/B-phase re-synthesis: 161,558 forced-cap units and 192,384 kernel/preload visit units are forced by A/B.
  • The fixed target port hyperplanes look like the common wall.

Credit

Marius-Paul Dumitrean, with substantial AI assistance (Claude Code); author-checked, not independently reviewed.

…kip words

Every exact restore-only rewrite of dcharb78's six-skip words (both
providers; A/B, warps, cut, helper ends, start frames and buffers
fixed; any restore gate sequence; all frames re-solved; exactness =
PR2833's auditor) costs at least LB_forced + forced restore-phase
visits = 10,867,765,164 + 337,923 = 10,868,103,087, the certified cost
of the words, which attain it. No new kappa.

The stdlib verifier recomputes the exact frame optimum (numpy-free port
of the certified solver), the free-algebra restore-entry rows and the
forced coordinates, the 88 entry caps and LB_forced, and the sound
classification (dual-vector departure lemma; 42 blocked registers, 9
payer groups). It also checks the PR2979 calibration (29,976 = the six
PR3042 skips), the per-block erratum of PR3042's README, the
auditor-semantics and attainment controls, twelve rejection controls,
and the deletion and tail-exchange censuses.
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