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In statistical mechanics, the generally called Stirling approximation is actually an approximation of Stirling's formula. In this article, it is shown that the term that is dropped is in fact the one that takes fluctuations into account.…

Classical Physics · Physics 2023-11-01 Didier Lairez

We study convergence rates of variational posterior distributions for nonparametric and high-dimensional inference. We formulate general conditions on prior, likelihood, and variational class that characterize the convergence rates. Under…

Statistics Theory · Mathematics 2019-06-18 Fengshuo Zhang , Chao Gao

We show, assuming the Strong Exponential Time Hypothesis, that for every $\varepsilon > 0$, approximating directed Diameter on $m$-arc graphs within ratio $7/4 - \varepsilon$ requires $m^{4/3 - o(1)}$ time. Our construction uses nonnegative…

Data Structures and Algorithms · Computer Science 2021-02-09 Édouard Bonnet

It is well known that exact notions of model abstraction and reduction for dynamical systems may not be robust enough in practice because they are highly sensitive to the specific choice of parameters. In this paper we consider this problem…

Systems and Control · Computer Science 2018-07-19 Luca Cardelli , Mirco Tribastone , Max Tschaikowski , Andrea Vandin

The fractional diffusion equation is rigorously derived as a scaling limit from a deterministic Rayleigh gas, where particles interact via short range potentials with support of size $\varepsilon$ and the background is distributed in space…

Analysis of PDEs · Mathematics 2025-11-04 Karsten Matthies , Theodora Syntaka

The problem of calculating the period of second order nonlinear autonomous oscillators is formulated as an eigenvalue problem. We show that the period can be obtained from two integral variational principles dual to each other. Upper and…

Chaotic Dynamics · Physics 2009-11-10 R. D. Benguria , M. C. Depassier

We consider evolutionary reaction-diffusion problem with mixed Dirichlet--Robin boundary conditions. For this class of problems, we derive two-sided estimates of the distance between any function in the admissible energy space and exact…

Numerical Analysis · Mathematics 2013-12-17 Svetlana Matculevich , Pekka Neittaanmäki , Sergey Repin

Given a finite metric space $(V,d)$, an approximate distance oracle is a data structure which, when queried on two points $u,v \in V$, returns an approximation to the the actual distance between $u$ and $v$ which is within some bounded…

Data Structures and Algorithms · Computer Science 2016-12-19 Michael Dinitz , Zeyu Zhang

Suppose $x$ is an approximation of $y$. This paper proposes using $\frac{|x-y|}{1+|y|}$, named Hyb Error, to measure the error. This metric equals half the harmonic mean of absolute error and relative error, effectively combining their…

Numerical Analysis · Mathematics 2024-05-22 Peichen Xie

The paper is concerned with the Barenblatt-Biott model in the theory of poroelasticity. We derive a guaranteed estimate of the difference between exact and approximate solutions expressed in a combined norm that encompasses errors for the…

Numerical Analysis · Mathematics 2010-03-30 J. M. Nordbotten , T. Rahman , S. I. Repin , J. Valdman

We give an explicit $O(x/T)$ error term for the truncated Riemann--von Mangoldt explicit formula. For large $x$, this provides a modest improvement over previous work, which we demonstrate via an application to a result on primes between…

Number Theory · Mathematics 2026-02-24 Michaela Cully-Hugill , Daniel R. Johnston

For any $T \geq 1$, there are constants $R=R(T) \geq 1$ and $\zeta=\zeta(T)>0$ and a randomized algorithm that takes as input an integer $n$ and two strings $x,y$ of length at most $n$, and runs in time $O(n^{1+\frac{1}{T}})$ and outputs an…

Data Structures and Algorithms · Computer Science 2019-05-10 Michal Koucký , Michael E. Saks

Linear fixed point equations in Hilbert spaces arise in a variety of settings, including reinforcement learning, and computational methods for solving differential and integral equations. We study methods that use a collection of random…

Machine Learning · Computer Science 2020-12-11 Wenlong Mou , Ashwin Pananjady , Martin J. Wainwright

We develop a simple method to obtain approximate analytical expressions for the period of a particle moving in a given potential. The method is inspired to the Linear Delta Expansion (LDE) and it is applied to a large class of potentials.…

Mathematical Physics · Physics 2009-11-10 Paolo Amore , Ricardo A. Saenz

The linear stability threshold of the Rayleigh-Benard configuration is analyzed with compressible effects taken into account. It is assumed that the fluid obeys a Newtonian rheology and Fourier's law of thermal transport with constant,…

Fluid Dynamics · Physics 2017-04-05 Thierry Alboussiere , Yanick Ricard

The approximate string matching is a fundamental and recurrent problem that arises in most computer science fields. This problem can be defined as follows: Let $D=\{x_1,x_2,\ldots x_d\}$ be a set of $d$ words defined on an alphabet…

Data Structures and Algorithms · Computer Science 2017-01-31 Ibrahim Chegrane

This article revisits an analysis on inaccuracies of time series averaging under dynamic time warping conducted by \cite{Niennattrakul2007}. The authors presented a correctness-criterion and introduced drift-outs of averages from clusters.…

Machine Learning · Statistics 2018-09-11 Brijnesh Jain

We study a parabolic system with $p(t,x)$-structure under Dirichlet boundary conditions. In particular, we deduce the optimal convergence rate for the error of the gradient of a finite element based space-time approximation. The error is…

Numerical Analysis · Mathematics 2019-04-02 Dominic Breit , Prince Romeo Mensah

We study a finite form of the classical interval discrepancy problem. Starting from the unit interval, one repeatedly splits an existing interval into two until $n$ intervals have been produced. The discrepancy of such a process is the…

Combinatorics · Mathematics 2026-05-29 Jared DeLeo , Owen Henderschedt , Chris Wells

We calculate the triple correlations for the truncated divisor sum $\lambda_{R}(n)$. The $\lambda_{R}(n)$'s behave over certain averages just as the prime counting von Mangoldt function $\Lambda(n)$ does or is conjectured to do. We also…

Number Theory · Mathematics 2007-05-23 D. A. Goldston , C. Y. Yildirim