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Random spatial networks-that is, graphs whose connectivity is governed by geometric proximity-have emerged as fundamental models for systems constrained by an underlying spatial structure. A prototypical example is the random geometric…

Probability · Mathematics 2026-02-20 Christian Hirsch , Kyeongsik Nam , Moritz Otto

We derive a systematic, multiple time-scale perturbation expansion for the work distribution in isothermal quasi-static Langevin processes. To first order we find a Gaussian distribution reproducing the result of Speck and Seifert [Phys.…

Statistical Mechanics · Physics 2015-06-15 Johannes Hoppenau , Andreas Engel

We survey the properties of the log-correlated Gaussian field (LGF), which is a centered Gaussian random distribution (generalized function) $h$ on $\mathbb R^d$, defined up to a global additive constant. Its law is determined by the…

Probability · Mathematics 2014-07-22 Bertrand Duplantier , Rémi Rhodes , Scott Sheffield , Vincent Vargas

A collection of rigorous results for a class of mean-field monomer-dimer models is presented. It includes a Gaussian representation for the partition function that is shown to considerably simplify the proofs. The solutions of the quenched…

Mathematical Physics · Physics 2016-12-30 Diego Alberici , Pierluigi Contucci , Emanuele Mingione

Multivariate distributions are explored using the joint distributions of marginal sample quantiles. Limit theory for the mean of a function of order statistics is presented. The results include a multivariate central limit theorem and a…

Statistics Theory · Mathematics 2011-04-25 G. Jogesh Babu , Zhidong Bai , Kwok Pui Choi , Vasudevan Mangalam

In this paper we examine isotropic Gaussian random fields defined on $\mathbb R^N$ satisfying certain conditions. Specifically, we investigate the type of a critical point situated within a small vicinity of another critical point, with…

Probability · Mathematics 2023-10-20 Paul Marriott , Weinan Qi , Yi Shen

This manuscript studies the Gaussian approximation of the coordinate-wise maximum of self-normalized statistics in high-dimensional settings. We derive an explicit Berry-Esseen bound under weak assumptions on the absolute moments. When the…

Probability · Mathematics 2025-01-16 Woonyoung Chang , Kenta Takatsu , Konrad Urban , Arun Kumar Kuchibhotla

In this paper, we explore the convergence of the semi-discrete Scharfetter-Gummel scheme for the aggregation-diffusion equation using a variational approach. Our investigation involves obtaining a novel gradient structure for the finite…

Numerical Analysis · Mathematics 2024-12-23 Anastasiia Hraivoronska , André Schlichting , Oliver Tse

Using a microfluidics device filled with a colloidal suspension of microspheres, we test the laws of diffusion in the limit of small particle numbers. Our focus is not just on average properties such as the mean flux, but rather on the…

Statistical Mechanics · Physics 2007-05-23 Effrosyni Seitaridou , Mandar M. Inamdar , Rob Phillips , Kingshuk Ghosh , Ken Dill

We characterize the behavior of a random discrete interface $\phi$ on $[-L,L]^d \cap \mathbb{Z}^d$ with energy $\sum V(\Delta \phi(x))$ as $L \to \infty$, where $\Delta$ is the discrete Laplacian and $V$ is a uniformly convex, symmetric,…

Probability · Mathematics 2023-02-14 Eric Thoma

We consider the discrete Gaussian Free Field (DGFF) in scaled-up (square-lattice) versions of suitably regular continuum domains $D\subset\mathbb C$ and describe the scaling limit, including local structure, of the level sets at heights…

Probability · Mathematics 2020-01-06 Marek Biskup , Oren Louidor

We resolve a conjecture of Sheffield that $\SLE(4)$, a conformally invariant random curve, is the universal limit of the chordal zero-height contours of random surfaces with isotropic, uniformly convex potentials. Specifically, we study the…

Probability · Mathematics 2010-10-08 Jason Miller

We propose a new approach to deriving quantitative mean field approximations for any probability measure $P$ on $\mathbb{R}^n$ with density proportional to $e^{f(x)}$, for $f$ strongly concave. We bound the mean field approximation for the…

Probability · Mathematics 2022-06-06 Daniel Lacker , Sumit Mukherjee , Lane Chun Yeung

Let $Z:=\{Z_t,t\geq0\}$ be a stationary Gaussian process. We study two estimators of $\mathbb{E}[Z_0^2]$, namely $\widehat{f}_T(Z):= \frac{1}{T} \int_{0}^{T} Z_{t}^{2}dt$, and $\widetilde{f}_n(Z) :=\frac{1}{n} \sum_{i =1}^{n}…

Statistics Theory · Mathematics 2021-02-10 Soukaina Douissi , Khalifa Es-Sebaiy , George Kerchev , Ivan Nourdin

Primordial, non-Gaussian perturbations can generate scale-dependent bias in the galaxy distribution. This in turn will modify correlations between galaxy positions and peculiar velocities at late times, since peculiar velocities reflect the…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-16 Yin-Zhe Ma , James E. Taylor , Douglas Scott

This paper derives central limit and bootstrap theorems for probabilities that sums of centered high-dimensional random vectors hit hyperrectangles and sparsely convex sets. Specifically, we derive Gaussian and bootstrap approximations for…

Statistics Theory · Mathematics 2016-03-09 Victor Chernozhukov , Denis Chetverikov , Kengo Kato

We generalize the well-known zero bias distribution and the $\lambda$-Stein pair to an approximate zero bias distribution and an approximate $\lambda,R$-Stein pair, respectively. Berry Esseen type bounds to the normal, based on approximate…

Probability · Mathematics 2017-11-27 Nathakhun Wiroonsri

The Sachs-Wolfe temperature fluctuations produced by primordial density perturbations are proportional to the potential field \phi, which is a weighted integral over the density field \delta. Because of the central limit theorem, \phi can…

Astrophysics · Physics 2011-05-12 Robert J. Scherrer , Robert K. Schaefer

We prove a central limit theorem for smooth linear statistics associated with zero divisors of standard Gaussian holomorphic sections in a sequence of holomorphic line bundles with Hermitian metrics of class $\mathscr{C}^{3}$ over a compact…

Complex Variables · Mathematics 2025-02-10 Afrim Bojnik , Ozan Günyüz

This paper develops asymptotic theory for quantile estimation via stochastic gradient descent (SGD) with a constant learning rate. The quantile loss function is neither smooth nor strongly convex. Beyond conventional perspectives and…

Machine Learning · Statistics 2026-04-06 Ziyang Wei , Jiaqi Li , Likai Chen , Wei Biao Wu