Alphabeta Math
TheoremStatement: AI-adaptedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-07
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

Chebyshev psi prime number theorem error

Statement

There is an absolute c>0 such that for x2, ψ(x)=x+O(xeclogx).

Facts & Assumptions

Given: The data and hypotheses of the statement.

[F1]

Zeta explicit formula zero free error balance: For x2 and finite T3, the classical region and truncated explicit formula give ψ(x)x=O(xec0logx/log(T+2)log2T+xlog2(xT)T+logx). Constants may be enlarged and the positive region constant decreased. The zero sum used in the proof is finite.

[F2]

Zeta bounds in classical zero free region: There are 0<c2<c1<c0 and C>0 such that for t3 and σ1c1/log(t+2), ζ/ζ(σ+it)Clog(t+2)Clog2(t+2). In the narrower c2 region, 1/ζ(s)Clog(t+2). For t3 and 1c2/log(t+2)σ2, ζ/ζ(s)+1/(s1)=O(1),1/ζ(s)=O(s1), with removable interpretations at one.

Proof

1.1

Put u=logx and choose a fixed A>0. For sufficiently large x take T=eAu3. Then log(T+2)=Au+O(eAu), so the finite-zero term is O(xu2e(c0/A)u+o(1)), the truncation term is O(xu4eAu), and the remaining error is O(u2).

F1
2.1

Choose 0<c<min(A,c0/A). For any fixed k and positive epsilon, ukeϵu is bounded; thus each error above is O(xecu). Enlarging the constant over the initial compact x-range proves the assertion for all x2.

step 1.1algebra
3.1

The contour interpretation is consistent with the same bound: take σ1=1c1/log(T+2) with a sufficiently small region constant and σ0=1+1/logx. Throughout tT the left edge stays in the proved region. At high heights the derivative is O(logT); integrating 1/s gives a vertical contribution O(xσ1log2T), and horizontal edges give O(xlog2(xT)/T). At bounded height the pole-subtracted estimate bounds the derivative by O(1+1/s1); on the left edge its integral is O(loglog(T+2)). Only the pole at one is crossed. These edge bounds explain the scale used in the finite-zero proof.

F2step 1.1step 2.1

Depends on

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Sources