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In this work we study the diffusion annealed Langevin dynamics, a score-based diffusion process recently introduced in the theory of generative models and which is an alternative to the classical overdamped Langevin diffusion. Our goal is…

Probability · Mathematics 2025-11-14 Patrick Cattiaux , Paula Cordero-Encinar , Arnaud Guillin

We introduce a constructive framework to learn effective Langevin equations from stationary time series. Unlike conventional approaches that require iterative calibration to match target statistics, our construction guarantees the observed…

Chaotic Dynamics · Physics 2026-02-16 Ludovico Theo Giorgini

The problem of estimating small transition probabilities for overdamped Langevin dynamics is considered. A simplification of Girsanov's formula is obtained in which the relationship between the infinitesimal generator of the underlying…

Mathematical Physics · Physics 2012-05-17 David Aristoff

A large class of quantum and statistical field theoretical models, encompassing relevant condensed matter and non-abelian gauge systems, are defined in terms of complex actions. As the ordinary Monte-Carlo methods are useless in dealing…

Statistical Mechanics · Physics 2009-11-11 L. Moriconi , M. Moriconi

Contraction in Wasserstein 1-distance with explicit rates is established for generalized Hamiltonian Monte Carlo with stochastic gradients under possibly nonconvex conditions. The algorithms considered include splitting schemes of kinetic…

Probability · Mathematics 2024-09-16 Martin Chak , Pierre Monmarché

This work deals with the large time behaviour of the spatially homogeneous Landau equation with Coulomb potential. Firstly, we obtain a bound from below of the entropy dissipation $D(f)$ by a weighted relative Fisher information of $f$ with…

Analysis of PDEs · Mathematics 2015-10-30 Kleber Carrapatoso , Laurent Desvillettes , Lingbing He

Quantitative long-time entropic convergence and short-time regularization are established for an idealized Hamiltonian Monte Carlo chain which alternatively follows an Hamiltonian dynamics for a fixed time and then partially or totally…

Probability · Mathematics 2023-06-06 Pierre Monmarché

We develop a unified approach for establishing rates of decay for the Fourier transform of a wide class of dynamically defined measures. Among the key features of the method is the systematic use of the $L^2$-flattening theorem obtained in…

Dynamical Systems · Mathematics 2024-12-23 Simon Baker , Osama Khalil , Tuomas Sahlsten

We analyze upwind difference methods for strongly degenerate convection-diffusion equations in several spatial dimensions. We prove that the local $L^1$-error between the exact and numerical solutions is $\mathcal{O}(\Delta x^{2/(19+d)})$,…

Analysis of PDEs · Mathematics 2015-09-07 Kenneth Hvistendahl Karlsen , Nils Henrik Risebro , Erlend Briseid Storrøsten

We consider the extreme value statistics of correlated random variables that arise from a Langevin equation. Recently, it was shown that the extreme values of the Ornstein-Uhlenbeck process follow a different distribution than those…

Statistical Mechanics · Physics 2021-08-17 Lior Zarfaty , Eli Barkai , David A. Kessler

This paper presents a new accelerated proximal Markov chain Monte Carlo methodology to perform Bayesian inference in imaging inverse problems with an underlying convex geometry. The proposed strategy takes the form of a stochastic relaxed…

We study the convergence rates of the classical Lagrangian-based methods and their variants for solving convex optimization problems with equality constraints. We present a generalized prediction-correction framework to establish $O(1/K^2)$…

Optimization and Control · Mathematics 2023-04-04 T. Zhang , Y. Xia , S. R. Li

In this paper, we propose a new numerical method for the underdamped Langevin diffusion (ULD) and present a non-asymptotic analysis of its sampling error in the 2-Wasserstein distance when the $d$-dimensional target distribution…

Machine Learning · Statistics 2025-08-25 Maximilian Scott , Dáire O'Kane , Andraž Jelinčič , James Foster

We present new results of full QCD at nonzero chemical potential. In PRD 92, 094516 (2015) the complex Langevin method was shown to break down when the inverse coupling decreases and enters the transition region from the deconfined to the…

High Energy Physics - Lattice · Physics 2018-04-18 Jacques Bloch , Olaf Schenk

We study the mathematical properties of a nonequilibrium Langevin dynamics which can be used to estimate the shear viscosity of a system. More precisely, we prove a linear response result which allows to relate averages over the…

Statistical Mechanics · Physics 2012-11-26 Remi Joubaud , Gabriel Stoltz

We present an improved analysis of the Euler-Maruyama discretization of the Langevin diffusion. Our analysis does not require global contractivity, and yields polynomial dependence on the time horizon. Compared to existing approaches, we…

Probability · Mathematics 2019-11-05 Wenlong Mou , Nicolas Flammarion , Martin J. Wainwright , Peter L. Bartlett

We establish pointwise polynomial decay estimates in velocity space for the spatially inhomogeneous Boltzmann equation without cutoff, in the case of hard potentials ($\gamma +2s > 2$), under the assumption that the mass, energy, and…

Analysis of PDEs · Mathematics 2020-06-24 Stephen Cameron , Stanley Snelson

The complex Langevin method is a promising approach to the complex-action problem based on a fictitious time evolution of complexified dynamical variables under the influence of a Gaussian noise. Although it is known to have a restricted…

High Energy Physics - Lattice · Physics 2017-01-04 Keitaro Nagata , Jun Nishimura , Shinji Shimasaki

We study the Langevin dynamics of a dipole diffusing in a random electrical field E derived from a quenched Gaussian potential. We show that in a suitable adiabatic limit (where the dynamics of the dipole moment is much faster than the…

Disordered Systems and Neural Networks · Physics 2015-05-13 Clement Touya , David S. Dean , Clement Sire

In this paper, we quantitative convergence in $W_2$ for a family of Langevin-like stochastic processes that includes stochastic gradient descent and related gradient-based algorithms. Under certain regularity assumptions, we show that the…

Statistics Theory · Mathematics 2019-07-03 Xiang Cheng , Peter L. Bartlett , Michael I. Jordan
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