GPT-5.2 Pro sieve proof gives near-one lower density for Erdős #851

For every ε>0, there is an r such that integers 2^k+n with n having at most r prime factors have lower density at least 1−ε. The claim neither establishes a natural density nor fixes one r for all ε.

Sources for this record

What was already known

Romanoff proved positive lower density when n is prime.

AI involvement AI-led

Price reports that GPT-5.2 Pro developed the sieve argument through an interactive exchange; Price posed and managed the problem.

Price's first-person account credits GPT-5.2 Pro with producing the central sieve proof across an interactive exchange.

Importance Notable

This answers Erdős #851 by making the lower density arbitrarily close to one.

Limitations

Terence Tao checked the moment and singular-series steps and confirmed Price’s argument. A later Lean theorem states the lower-density result. Green and Sawhney’s stronger quantitative variant is separate human work.

Technical verification Formal (Lean 4 + human)

Tao explicitly confirmed the submitted argument after checking the first and second moments and singular-series averaging. The later Lean file reports a proof of the lower-density formulation, which is narrower than a natural-density assertion.

Formal checking

Price and GPT-5.2 Pro's near-one lower-density sieve argument; Mathematical review of the moment estimates and average singular-series bound, followed by explicit confirmation

Checker
Terence Tao
Scope
Price and GPT-5.2 Pro's near-one lower-density sieve argument
Basis
Reported by the linked checker
Evidence source

Formal checking

erdos_851: for every 0<ε<1 some r gives lower density at least 1−ε; Proof-bearing Lean theorem importing the uniform beta estimates development

Checker
Lean 4 in the plby/lean-proofs release
Scope
erdos_851: for every 0<ε<1 some r gives lower density at least 1−ε
Basis
Reported by the linked checker
Evidence source

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

Human understanding Full

Tao explains the central sieve, moment and singular-series argument and the remaining prime-order estimate; Green and Sawhney describe a related stronger method.

Correction and publication history