Alphabeta Math
TheoremStatement: Literature-sourcedProof: AI-generatedprecheck passaudited 2026-09-01
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  • 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.

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Chebyshev's theta function has linear lower and upper bounds

Statement

There exist positive constants c<C and a real number x0 such that

cxθ(x)Cx

for every real xx0.

Facts & Assumptions

Given: A real number x2.

[L1]

The central binomial coefficient satisfies 4n2n+1(2nn)4n for every natural number n (Central binomial coefficient bounds).

[L2]

For every prime p and natural n1, primes p with n<p2n divide (2nn), and in general vp(2nn)log(2n)logp (Prime valuations in the central binomial coefficient).

[L5]

The logarithm satisfies log(ab)=loga+logb and log(4n)=2nlog2 (Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm).

[L6]

Induction on N is valid (The principle of mathematical induction).

Proof

technique · direct
1.1

Put P(y):=pyp for real y2. We claim that P(y)4y1(y2). Let q be the largest prime with qy. Then P(y)=P(q) and 4q14y1, so it suffices to prove the claim when y=q is prime. For q=2 this is immediate. Let q=2m+1 be an odd prime, and assume inductively that P(r)4r1 for every integer r with 2r2m. Then P(q)=P(m+1)m+1<p2m+1p. Every prime in the second product divides (2m+1m)=(2m+1)!m!(m+1)! by [L4], because it appears in the numerator and in neither denominator factorial. Also [L3] gives k=02m+1(2m+1k)=22m+1, and the two equal middle terms (2m+1m)=(2m+1m+1) therefore satisfy (2m+1m)22m. Thus P(q)P(m+1)(2m+1m)4m22m=42m=4q1. So the claim holds for every real y2.

L3L4L6constructalgebra
1.2

Again by [L2], the factorization of (2nn) can be written as log(2nn)θ(2n)+Rn, where Rn:=k=2log2(2n)θ((2n)1/k). Using the trivial estimate θ(y)ylogy on each layer and (2n)1/k2n for k2, we get 0Rn2nlog(2n)log2(2n)=o(n).

L2givenalgebra
2.1

By definition of θ and the logarithm law in [L5], θ(y)=logP(y)log(4y1)=2(y1)log2<2ylog2 for every real y2.

step 1.1L5algebra
2.2

The lower bound in [L1] and [L5] give log(2nn)2nlog2log(2n+1). Combining this with step 1.2 shows θ(2n)2nlog2log(2n+1)Rn. Since log(2n+1)+Rn=o(n), choose n0 so large that log(2n+1)+Rnnlog2 for every nn0. Then θ(2n)nlog2(nn0).

L1L5step 1.2choosealgebra
3.1

Let x4n0, and put n=x/2. Then nn0 and 2nx, so by monotonicity of θ and step 2.2, θ(x)θ(2n)nlog2log24x. Step 2.1 also gives θ(x)2xlog2 for every x2. Thus the theorem holds with c=log24, C=2log2, and x0=4n0.

step 2.2step 2.1givenalgebra

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