A Limiting Satisfiability Threshold for Every Fixed Clause Size

OpenAI

For every fixed k≥3, random k-SAT with independent uniformly signed proper clauses sampled with replacement has a positive finite limiting density αₖ: satisfiability probability tends to one below αₖ and zero above it. The claim makes no assertion at αₖ.

Sources for this record

What was already known

Friedgut proved a sharp transition around a density that could depend on formula size. Gaia Carenini established the fixed-k limiting threshold first; the OpenAI manuscript credits her priority and gives another proof.

AI involvement AI-led

OpenAI is the credited author and attributes the proof artifacts to its internal model. No named person is documented as checking or explaining its concentration-and-comparison proof.

OpenAI authorship and release provenance credit the internal model with the alternative proof; session-level autonomy is not documented.

Importance Modest

The contribution is a distinct formalized proof of the threshold-existence theorem.

Limitations

The result does not compute αₖ, give a convergence rate, or cover the threshold point. Carenini’s separate proof confirms the conclusion but does not check OpenAI’s argument.

Technical verification Formal (Lean 4 with Mathlib)

The release maps the fixed-k threshold theorem to a Lean 4 proof, with proper clauses sampled independently with replacement and strict-side limits. The separate challenge target is a statement to prove, not the proof file.

Formal checking

Lean proof of OAI.FixedClauseThreshold.main using formalized random-SAT convergence, matched to the fixed-clause comparator statement; Final main theorem and preceding strict-side limits; see lean/docs/235.md, Scope

Checker
Lean 4 kernel, as reported by the OpenAI math release
Scope
For each fixed k ≥ 3, proper random k-SAT with replacement has a positive finite limiting threshold with strict-side limits
Basis
Reported by the linked checker
Evidence source

Checking a formal statement does not establish that it matches the original problem.

Human understanding Few

Carenini's independent proof establishes the conclusion by another method, but no named person explains OpenAI's capped-index concentration and system-size comparison mechanism. Few is the evidence default.

Correction and publication history