Liu's factored Selberg main term #
This module separates the exact finite factorization of Liu's M₁ from the two
analytic estimates needed to bound its factors. The component bounds below are
transparent propositions; no Selberg or logarithmic-integral estimate is
asserted.
Equations
Instances For
The quadratic Selberg coefficient factor on Liu's finite source carrier.
Equations
- MathlibNt.SieveTheory.LiuWeight.liuSelbergCoefficientFactor N epsilon lambda = ∑ d1 ∈ MathlibNt.SieveTheory.LiuWeight.liuSelbergLambdaSourceCarrier N epsilon, ∑ d2 ∈ MathlibNt.SieveTheory.LiuWeight.liuSelbergLambdaSourceCarrier N epsilon, lambda d1 * lambda d2 / ↑(d1.lcm d2).totient
Instances For
Equations
- MathlibNt.SieveTheory.LiuWeight.liuSelbergBoundingSieve N epsilon hNeven = { support := ∅, prodPrimes := MathlibNt.SieveTheory.LiuWeight.liuPaperQModulus N epsilon, prodPrimes_squarefree := ⋯, weights := fun (x : ℕ) => 0, weights_nonneg := MathlibNt.SieveTheory.LiuWeight.liuSelbergBoundingSieve._proof_1, totalMass := 0, nu := MathlibNt.SieveTheory.LiuWeight.liuSelbergReciprocalTotient, nu_mult := MathlibNt.SieveTheory.LiuWeight.liuSelbergReciprocalTotient_isMultiplicative, nu_pos_of_prime := ⋯, nu_lt_one_of_prime := ⋯ }
Instances For
Expanding the source carrier back to all divisors of the source modulus loses only terms whose lambda coefficient vanishes off the source support.
The coefficient/diagonal-main-sum identity needs only source support, not the separate absolute bound used by Liu's remainder estimate.
Under the source support hypotheses and Even N, the Selberg coefficient
factor is the diagonal main sum of a BoundingSieve with ν(d) = 1/φ(d).
The admissible-weight specialization of the support-only carrier identity.
Under the source support hypotheses and Even N, the Selberg coefficient
factor is a nonnegative diagonal sum of squares.
Exact finite factorization of Liu's arbitrary-model Selberg main term.
Source-facing specialization of the finite factorization to Liu's genuine logarithmic-integral family.
The sharp source Selberg coefficient upper estimate needed for Liu's M₁.
Its sign is a theorem, not part of this input.
Equations
- MathlibNt.SieveTheory.LiuWeight.LiuSelbergCoefficientFactorBound delta N epsilon lambda = (MathlibNt.SieveTheory.LiuWeight.liuSelbergCoefficientFactor N epsilon lambda ≤ (8 + delta) * MathlibNt.SieveTheory.SingularSeries.liuSingularSeries N / Real.log ↑N)
Instances For
Multiplying the two component estimates gives the M₁ coefficient
(8 + delta) * K, with no numerical approximation.
Exact decimal margin after writing K = 0.49254 + eta: the base product is
3.94032, leaving precisely 0.00001 for the linear and quadratic errors.
The printed 3.94033 bound follows only from the two explicit analytic
component hypotheses, positivity, and the exact finite-algebra margin.