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September 12, 20250 citationsOpen Access

On the Hughes–Keating–O’Connell Conjecture: Quantified Negative Moment Bounds for ζ′(ρ) via Entropy–Sieve Methods Revisited

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ZRZeraoulia Rafik

Key Points

  • The study proves a conditional bound for negative moments of zeta derivatives, aligning with conjectured orders.
  • Quantified bounds for negative moments show explicit logarithmic dependence on parameters, enhancing previous findings.
  • Innovations include a cumulant control lemma and a parameter selection method for better approximations.
  • The research highlights the role of entropy techniques in analytic number theory and suggests broader applications in L-functions.

Abstract

We study the negative discrete moments of the derivative of the Riemann zeta function at its nontrivial zeros, in connection with the Hughes--Keating--O’Connell conjecture. Building on the works of Gonek, Milinovich--Ng, Kirila, and the recent breakthrough of Bui--Florea--Milinovich, we introduce a new entropy--sieve method (ESM). This framework combines short Dirichlet-polynomial approximations with entropy-based moment generating function bounds and a small-gap sieve, thereby controlling all appearances of ' () without assuming simplicity of zeros. Assuming the Riemann Hypothesis together with standard pair-correlation conjectures and a strengthened discrete moment hypothesis, we prove the quantified conditional bound \ J-₁ (T) \;=\; ₀ ₓ 1|' (12+i) |^{2} \;\; C () \, T (T) ^, for every fixed 0, \ with an explicit dependence of the implicit constant on. This matches, up to logarithmic factors, the conjectured order J-₁ (T) T and improves on all previous conditional results. The analysis introduces several innovations: (i) a full cumulant control lemma for Dirichlet polynomials; (ii) explicit, non-circular parameter selection for approximation lengths and moments; and (iii) an entropy--sieve hybrid decay lemma that quantifies large-deviation probabilities for ' (). Beyond the negative moment problem, the entropy--sieve framework illustrates the strength of entropy techniques in analytic number theory and points toward applications to L-functions and random matrix models.

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Cite This Study

Zeraoulia Rafik (2025) studied this question.

synapsesocial.com/papers/68d44c4631b076d99fa55b23https://doi.org/10.20944/preprints202509.0489.v1
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