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1d: improved upper bound 1.457854884921989* (800-cell step function) - #248
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We started a second SCiEL run with a stronger model (closed frontier model, size not published) in place of Qwen3.8-27B (open weights, 27B parameters), starting from the 800-cell certificate in this PR. It already beat that certificate at step 5. By step 13 it had reached 1.4578222729 (800 cells), a gain of 0.36% over the current table entry [CERT2026] and 0.16% over #247. We checked it exactly with our verifier and with the one from #247. The run is still going and still improving. Once it settles, we will update the row, the README cell and the certificate here. |
echul-seal
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Oct 26, 2026
Rebased onto main after teorth#247 and teorth#248. Adds the [S2026] row after the [SCIEL2026] row, the [S2026] reference, a Recent progress line (previously 1.457854884921989*), and the README table cell.
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What changed
Improves the upper bound on C_1d (signed third autocorrelation constant) from 1.463071582607559* to
1.457854884921989*. Adds its row and reference to
constants/1d.md, together with two earlier bounds for thisvariant that the table was missing: Matolcsi–Vinuesa's 1.4993 (2010), cited for it in Problem 6.4 of [GGSWT2025],
and the 600-cell step function of AlphaEvolve repository PR 13 (17 Oct 2026), 1.459989046905384*, recomputed
exactly. Updates the README table cell and "Recent progress". Markdown only.
Evidence
38534420343892614563110610373646557184000 / 26432274393314964174848236787785831382961= 1.45785488492198861...The printed bound is rounded up.
with each stored double read as an exact rational.
python -I verify.py construction.json(standard library only).construction.json, print the same fraction.and we will grant access to anyone checking the bound.
SHA-256
construction.json:1eafe2408187c95e36d2e33911fe3fd425f6c55af3837b40b30c139c771ffefbSHA-256
verify.py:cfa116ce4cb62a46f1292f740f3bdde99035918d897cd1d0a0f4966f67120925Context
Ordering
PR #247 (1.460217284022874*) was opened earlier today. If it is merged first, this row goes after it and
"previously" becomes its value; we will rebase.
Use of AI
The construction was found by SCiEL, a recursive self-improvement (RSI) system built on cultural transmission,
running an open language model (Qwen3.8-27B) that writes and refines search programs scored by the exact bound. AI assistants helped prepare this pull request. We have checked the value, the certificate and every reference above.