OpenAI · 235-03 · 2026-09-27 · Probability and statistical mechanics
Variance of the Random k-SAT Hitting Time
preprints/Variance-of-the-Random-k-SAT-Hitting-Time-September-27-2026
Family 235. Random-SAT thresholds, sharp variance and computability.
The authors are OpenAI. This companion does not verify the proof and does not adopt it as a theorem of Ngo Cheung’s series. It is not a premise. O.1 stays NOT_CLOSED. Anti-de Sitter results are not a de Sitter state, not Em02-E’s relational lapse, not XVI-P’s QdS scheme, and not XVI-Q’s sigma-image record. No quantum coefficient is admitted. No compilation is asserted.
Read against the standing problems
Standing problems. No standing problem is named in this text. It was still read against the nine problems and does not close any of them. The authors are OpenAI. The companion does not verify the proof. This is not a premise of a manuscript by Ngo Cheung. O.1 stays NOT_CLOSED. No quantum coefficient is admitted. No compilation is asserted. XVI-P · XVI-N
For random -SAT with independent uniformly signed proper clauses sampled with replacement, proves finite positive limiting thresholds and hitting-time variance for every fixed , and computability of the 3-SAT threshold. We credit Gaia Carenini with priority for resolving the threshold-existence conjecture in her concurrent ECCC TR26-229, made public October 5, 2026; this family supplies another proof and the sharper variance and computability results.
Let Hn be the index of the first unsatisfiable prefix in random k-SAT on n variables, with independent uniformly signed clauses using k distinct variables and sampled with replacement. For every fixed k ≥ 4, we prove . For k = 3, the variance is bounded below by a positive multiple of n and above by a constant multiple of ; the companion paper on random 3-SAT sharpens this to . The same upper bounds proved here hold after clipping at any fixed positive multiple of n.
Preprint source and Lean scope
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This preprint is named in the Lean scope note for 235: Limiting random SAT thresholds, sharp variance and computability. The authors are OpenAI. This companion does not verify the formalization. It is not a premise. The OAI library is not imported. No compilation is asserted. O.1 stays NOT_CLOSED.