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The aim of this work is to establish numerous interrelated gradient estimates in the nonlinear nonlocal setting. First of all, we prove that weak solutions to a class of homogeneous nonlinear nonlocal equations of possibly arbitrarily low…

Analysis of PDEs · Mathematics 2024-08-09 Lars Diening , Kyeongbae Kim , Ho-Sik Lee , Simon Nowak

We consider the problem of sampling distributions stemming from non-convex potentials with Unadjusted Langevin Algorithm (ULA). We prove the stability of the discrete-time ULA to drift approximations under the assumption that the potential…

Machine Learning · Statistics 2025-09-01 Marien Renaud , Valentin De Bortoli , Arthur Leclaire , Nicolas Papadakis

The Riccati inequality and equality are studied for infinite dimensional linear discrete time stationary systems with respect to the scattering supply rate. The results obtained are an addition to and based on our earlier work on the…

Functional Analysis · Mathematics 2016-09-02 D. Z. Arov , M. A. Kaashoek , D. R. Pik

Score-based diffusion models have demonstrated outstanding empirical performance in machine learning and artificial intelligence, particularly in generating high-quality new samples from complex probability distributions. Improving the…

Machine Learning · Statistics 2025-05-30 Yuchen Jiao , Gen Li

Perturbations of super Poincar\'e and weak Poincar\'e inequalities for L\'evy type Dirichlet forms are studied. When the range of jumps is finite our results are natural extensions to the corresponding ones derived earlier for diffusion…

Probability · Mathematics 2015-01-27 Xin Chen , Feng-Yu Wang , Jian Wang

Combining classical arguments for the analysis of the simulated annealing algorithm with the more recent hypocoercive method of distorted entropy, we prove the convergence for large time of the kinetic Langevin annealing with logarithmic…

Probability · Mathematics 2017-08-01 Pierre Monmarché

We present some classical and weighted Poincar\'e inequalities for some one-dimensional probability measures. This work is the one-dimensional counterpart of a recent study achieved by the authors for a class of spherically symmetric…

Probability · Mathematics 2014-11-24 Michel Bonnefont , Aldéric Joulin , Yutao Ma

We prove a sequence of limiting results about weakly dependent stationary and regularly varying stochastic processes in discrete time. After deducing the limiting distribution for individual clusters of extremes, we present a new type of…

Probability · Mathematics 2017-12-05 Bojan Basrak , Hrvoje Planinic , Philippe Soulier

The boundary cancellation theorem for open systems extends the standard quantum adiabatic theorem: assuming the gap of the Liouvillian does not vanish, the distance between a state prepared by a boundary cancelling adiabatic protocol and…

Quantum Physics · Physics 2024-01-17 Humberto Munoz-Bauza , Lorenzo Campos Venuti , Daniel Lidar

A convergence theorem for martingales with c\`adl\`ag trajectories (right continuous with left limits everywhere) is obtained in the sense of the weak dual topology on Hilbert space, under conditions that are much weaker than those required…

Probability · Mathematics 2024-10-08 Bruno N. Remillard , Jean Vaillancourt

We consider in this work small random perturbations (of multiplicative noise type) of the gradient flow. We prove that under mild conditions, when the potential function is a Morse function with additional strong saddle condition, the…

Probability · Mathematics 2020-04-29 Jiaojiao Yang , Wenqing Hu , Chris Junchi Li

The purpose of this short note is to demonstrate uniform logarithmic Sobolev inequalities for the mean field gradient particle systems associated to an energy functional that is convex in the flat sense. A defective log-Sobolev inequality…

Probability · Mathematics 2024-08-13 Songbo Wang

In a recent study (Ref. [1]), quantum annealing was reported to exhibit a scaling advantage for approximately solving Quadratic Unconstrained Binary Optimization (QUBO). However, this claim critically depends on the choice of classical…

Quantum Physics · Physics 2025-05-29 J. Pawlowski , P. Tarasiuk , J. Tuziemski , L. Pawela , B. Gardas

We study the convergence rate of continuous-time simulated annealing $(X_t; \, t \ge 0)$ and its discretization $(x_k; \, k =0,1, \ldots)$ for approximating the global optimum of a given function $f$. We prove that the tail probability…

Probability · Mathematics 2021-02-10 Wenpin Tang , Xun Yu Zhou

Many practical samplers rely on time-dependent drifts -- often induced by annealing or tempering schedules -- to improve exploration and stability. This motivates a unified non-asymptotic analysis of the corresponding Langevin diffusions…

Numerical Analysis · Mathematics 2026-05-12 Andreas Habring , Martin Zach

We show that there exists an ergodic conductance environment such that the weak (annealed) invariance principle holds for the corresponding continuous time random walk but the quenched invariance principle does not hold. In the present…

Probability · Mathematics 2013-12-17 Martin Barlow , Krzysztof Burdzy , Adám Timár

We study a system of semilinear wave equations satisfying the weak null condition, which can be regarded as a simplified model for the Einstein vacuum equations. The main objective is to establish precise pointwise decay estimates, as both…

Analysis of PDEs · Mathematics 2026-02-27 Shijie Dong , Siyuan Ma , Yue Ma , Xu Yuan

In this paper we introduce and study a weakened form of logarithmic Sobolev inequalities in connection with various others functional inequalities (weak Poincar\'{e} inequalities, general Beckner inequalities...). We also discuss the…

Probability · Mathematics 2007-05-23 Patrick Cattiaux , Ivan Gentil , Arnaud Guillin

Discretization of continuous-time diffusion processes is a widely recognized method for sampling. However, the canonical Euler Maruyama discretization of the Langevin diffusion process, referred as Unadjusted Langevin Algorithm (ULA),…

Computation · Statistics 2021-07-28 Dao Nguyen , Xin Dang , Yixin Chen

The aim of this paper is to prove the exponential convergence, local and global, of Adam algorithm under precise conditions on the parameters, when the objective function lacks differentiability. More precisely, we require Lipschitz…

Optimization and Control · Mathematics 2024-03-14 Juan Ferrera , Javier Gómez Gil