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A “Riemann hypothesis” for triangulable manifolds [PDF]
, 1984 K. S. Sarkaria
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Debiasing piecewise deterministic Markov process samplers using couplings
Scandinavian Journal of Statistics, EarlyView.Abstract Monte Carlo methods—such as Markov chain Monte Carlo (MCMC) and piecewise deterministic Markov process (PDMP) samplers—provide asymptotically exact estimators of expectations under a target distribution. There is growing interest in alternatives to this asymptotic regime, in particular in constructing estimators that are exact in the limit of ...
Adrien Corenflos +2 more
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Slide Presentation on the Riemann Hypothesis
, 2022 The Riemann Hypothesis is a conjecture that the Riemann zeta function has its zeros only at the negative even integers and complex numbers with real part 1/2. In 2011, Patrick Solé and Michel Planat stated a new criterion for the Riemann Hypothesis. We prove the Riemann Hypothesis is true using this criterion.
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The generalized divisor problem and the Riemann hypothesis [PDF]
, 1991 Hideki Nakaya
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Transactions of the London Mathematical Society, Volume 12, Issue 1, December 2025.Abstract We study convergence problems for the intermediate long wave (ILW) equation, with the depth parameter δ>0$\delta > 0$, in the deep‐water limit (δ→∞$\delta \rightarrow \infty$) and the shallow‐water limit (δ→0$\delta \rightarrow 0$) from a statistical point of view.
Guopeng Li, Tadahiro Oh, Guangqu Zheng
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Explicit height estimates for CM curves of genus 2
Transactions of the London Mathematical Society, Volume 12, Issue 1, December 2025.Abstract In this paper, we make explicit the constants of Habegger and Pazuki's work from 2017 on bounding the discriminant of cyclic Galois CM fields corresponding to genus 2 curves with CM and potentially good reduction outside a predefined set of primes. We also simplify some of the arguments.
Linda Frey +2 more
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Riemann hypothesis solution updated
, 2020 It has been converted to pdf in the hope that the presentation of the mathmatical lines are no altered as it happened with the latest ...
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Fractional Gaussian Noise: Spectral Density and Estimation Methods
Journal of Time Series Analysis, Volume 46, Issue 6, Page 1146-1174, November 2025.The fractional Brownian motion (fBm) process, governed by a fractional parameter H∈(0,1)$$ H\in \left(0,1\right) $$, is a continuous‐time Gaussian process with its increment being the fractional Gaussian noise (fGn). This article first provides a computationally feasible expression for the spectral density of fGn.
Shuping Shi, Jun Yu, Chen Zhang
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