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We suggest a numerical integration procedure for solving the equations of motion of certain classical spin systems which preserves the underlying symplectic structure of the phase space. Such symplectic integrators have been successfully…

Statistical Mechanics · Physics 2007-05-23 Robin Steinigeweg , Heinz-Jürgen Schmidt

Recent advances in Bayesian learning with large-scale data have witnessed emergence of stochastic gradient MCMC algorithms (SG-MCMC), such as stochastic gradient Langevin dynamics (SGLD), stochastic gradient Hamiltonian MCMC (SGHMC), and…

Machine Learning · Statistics 2016-10-24 Changyou Chen , Nan Ding , Lawrence Carin

We provide an analytical framework for analyzing the quality of stochastic Verlet-type integrators for simulating the Langevin equation. Focusing only on basic objective measures, we consider the ability of an integrator to correctly…

Computational Physics · Physics 2026-02-12 Niels Grønbech-Jensen

A class of generative models that unifies flow-based and diffusion-based methods is introduced. These models extend the framework proposed in Albergo and Vanden-Eijnden (2023), enabling the use of a broad class of continuous-time stochastic…

Machine Learning · Computer Science 2025-10-10 Michael S. Albergo , Nicholas M. Boffi , Eric Vanden-Eijnden

This paper applies several well-known tricks from the numerical treatment of deterministic differential equations to improve the efficiency of the Multilevel Monte Carlo (MLMC) method for stochastic differential equations (SDEs) and…

Numerical Analysis · Mathematics 2014-12-23 Eike H. Mueller , Rob Scheichl , Tony Shardlow

We introduce and test an algorithm that adaptively estimates large deviation functions characterizing the fluctuations of additive functionals of Markov processes in the long-time limit. These functions play an important role for predicting…

Statistical Mechanics · Physics 2023-03-30 Grégoire Ferré , Hugo Touchette

The usual explicit finite-difference method of solving partial differential equations is limited in stability because it approximates the exact amplification factor by power-series. By adapting the same exponential-splitting method of…

Numerical Analysis · Mathematics 2012-06-11 Siu A. Chin

Symplectic integrators offer vastly superior performance over traditional numerical techniques for conservative dynamical systems, but their application to \emph{dissipative} systems is inherently difficult due to dissipative systems' lack…

Stochastic methods offer an effective way to suppress coherent errors in quantum simulation. In particular, the randomized compilation protocol may reduce circuit depth by randomly sampling Hamiltonian terms rather than following the…

Quantum Physics · Physics 2026-05-15 Yu-Xia Wu , Yun-Zhuo Fan , Dan-Bo Zhang

We study higher-order small-noise fluctuation expansions for the overdamped Langevin dynamics in a quartic double-well potential. Assuming that the initial data admits a suitable expansion structure, we obtain a strong dynamical expansion…

Probability · Mathematics 2026-04-07 Lin Wang , Zhengyan Wu

The development of surrogate models to study uncertainties in hydrologic systems requires significant effort in the development of sampling strategies and forward model simulations. Furthermore, in applications where prediction time is…

Computational Physics · Physics 2023-01-19 Chen Chen , Clint Dawson , Eirik Valseth

We study fluctuations of mean-field interacting particle systems around their McKean--Vlasov limit. Our main result provides a uniform-in-time quantitative central limit theorem for the fluctuation process, with convergence rate of order…

Probability · Mathematics 2026-05-06 Solesne Bourguin , Konstantinos Spiliopoulos

In this work, we study and extend a class of semi-Lagrangian exponential methods, which combine exponential time integration techniques, suitable for integrating stiff linear terms, with a semi-Lagrangian treatment of nonlinear advection…

Numerical Analysis · Mathematics 2025-04-25 João Guilherme Caldas Steinstraesser , Martin Schreiber , Pedro da Silva Peixoto

We provide bounds on temporal fluctuations around the infinite-time average of out-of-time-ordered and time-ordered correlators of many-body quantum systems without energy gap degeneracies. For physical initial states, our bounds predict…

Strongly Correlated Electrons · Physics 2023-12-20 Talía L. M. Lezama , Yevgeny Bar Lev , Lea F. Santos

Probabilistic integration of a continuous dynamical system is a way of systematically introducing model error, at scales no larger than errors introduced by standard numerical discretisation, in order to enable thorough exploration of…

Numerical Analysis · Mathematics 2019-10-29 H. C. Lie , A. M. Stuart , T. J. Sullivan

We introduce a family of stochastic models motivated by the study of nonequilibrium steady states of fluid equations. These models decompose the deterministic dynamics of interest into fundamental building blocks, i.e., minimal vector…

Probability · Mathematics 2025-05-07 Andrea Agazzi , Jonathan C. Mattingly , Omar Melikechi

This work aims to introduce a heuristic timestep-adaptive algorithm for Computational Fluid Dynamics (CFD) and Fluid-Structure Interaction (FSI) problems where the flow is dominated by the pressure. In such scenarios, many time-adaptive…

Numerical Analysis · Mathematics 2024-07-02 Ivan Prusak , Davide Torlo , Monica Nonino , Gianluigi Rozza

Recently, a thermodynamic bound on correlation times was formulated in [A. Dechant, J. Garnier-Brun, S.-i. Sasa, Phys. Rev. Lett. 131, 167101 (2023)], showing how the decay of correlations in Langevin dynamics is bounded by short-time…

Statistical Mechanics · Physics 2025-05-15 Cai Dieball , Aljaž Godec

Using experiments on a colloidal particle trapped in an optical tweezer, we confirm a recent proposal to increase the effective mobility or clock rate of systems described by Langevin dynamics, by simultaneously scaling deterministic forces…

Statistical Mechanics · Physics 2026-03-05 Prithviraj Basak , Stephen Whitelam , John Bechhoefer

We analyse three time integration schemes for unfitted methods in fluid structure interaction. In Alghorithm 1 we propose a fully discrete monolithic algorithm with P1 P1 stabilized finite elements for the fluid problem; for this alghorithm…

Numerical Analysis · Mathematics 2021-05-27 Michele Annese
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