English
Related papers

Related papers: A uniformly accurate scheme for the numerical inte…

200 papers

This paper considers the strong error analysis of the Euler and fast Euler methods for nonlinear overdamped generalized Langevin equations driven by the fractional noise. The main difficulty lies in handling the interaction between the…

Numerical Analysis · Mathematics 2023-02-21 Xinjie Dai , Jialin Hong , Derui Sheng , Tau Zhou

We study the convergence in total variation and $V$-norm of discretization schemes of the underdamped Langevin dynamics. Such algorithms are very popular and commonly used in molecular dynamics and computational statistics to…

Probability · Mathematics 2023-04-24 Alain Durmus , Aurélien Enfroy , Éric Moulines , Gabriel Stoltz

We derive and analyze numerical methods for underdamped (kinetic) Langevin dynamics in a domain with elastic reflection at the boundary. First-order approximations are based on an Euler-type scheme incorporating collision-handling at the…

Numerical Analysis · Mathematics 2025-12-10 B. Leimkuhler , A. Sharma , M. V. Tretyakov

Path reweighting is a principally exact method to estimate dynamic properties from biased simulations - provided that the path probability ratio matches the stochastic integrator used in the simulation. Previously reported path probability…

Chemical Physics · Physics 2021-03-02 Stefanie Kieninger , Bettina G. Keller

We propose a novel kinetic Langevin sampler based on a specific splitting scheme using the exact harmonic Langevin integrator. For strongly log-concave target measures, the sampler exploits a decomposition of the strongly convex potential…

Computation · Statistics 2026-05-26 Katharina Schuh

We study three kinetic Langevin samplers including the Euler discretization, the BU and the UBU splitting scheme. We provide contraction results in $L^1$-Wasserstein distance for non-convex potentials. These results are based on a carefully…

Probability · Mathematics 2025-08-20 Katharina Schuh , Peter A. Whalley

Low-dimensional structure in real-world data plays an important role in the success of generative models, which motivates diffusion models defined on intrinsic data manifolds. Such models are driven by stochastic differential equations…

Machine Learning · Statistics 2026-03-05 Zhiyuan Zhan , Masashi Sugiyama

We discuss the design of state-of-the-art numerical methods for molecular dynamics, focusing on the demands of soft matter simulation, where the purposes include sampling and dynamics calculations both in and out of equilibrium. We discuss…

Computational Physics · Physics 2020-02-14 Xiaocheng Shang , Martin Kröger , Benedict Leimkuhler

We address in this paper a model for the simulation of turbulent deflagrations in industrial applications. The flow is governed by the Euler equations for a variable composition mixture and the combustion modelling is based on a…

Numerical Analysis · Mathematics 2020-10-16 D Grapsas , Raphaèle Herbin , J. -C Latché , Y Nasseri

We study and develop multilevel methods for the numerical approximation of a log-concave probability $\pi$ on $\mathbb{R}^d$, based on (over-damped) Langevin diffusion. In the continuity of \cite{art:egeapanloup2021multilevel} concentrated…

Numerical Analysis · Mathematics 2023-01-24 Maxime Egéa

Many complex systems, ranging from migrating cells to animal groups, exhibit stochastic dynamics described by the underdamped Langevin equation. Inferring such an equation of motion from experimental data can provide profound insight into…

Biological Physics · Physics 2026-04-17 David B. Brückner , Pierre Ronceray , Chase P. Broedersz

Simulating the kinetic Langevin dynamics is a popular approach for sampling from distributions, where only their unnormalized densities are available. Various discretizations of the kinetic Langevin dynamics have been considered, where the…

Computation · Statistics 2026-05-08 Kyurae Kim , Samuel Gruffaz , Ji Won Park , Alain Oliviero Durmus

We present the first method to directly use a learned continuous Lagrangian to forecast the dynamics of systems governed by partial differential equations, exploiting the inherent conservative structure to achieve stable long-range…

Machine Learning · Computer Science 2026-05-11 Lyra Zhornyak , Eric Forgoston , M. Ani Hsieh

Dynamics simulations of constrained particles can greatly aid in understanding the temporal and spatial evolution of biological processes such as lateral transport along membranes and self-assembly of viruses. Most theoretical efforts in…

Computational Physics · Physics 2017-03-03 Stefan Paquay , Remy Kusters

We address here the discretization of the momentum convection operator for fluid flow simulations on 2D triangular and quadrangular meshes and 3D polyhedral meshes containing hexahedra, tetrahedra, prisms and pyramids. The finite volume…

Numerical Analysis · Mathematics 2022-09-15 Aubin Brunel , Raphaèle Herbin , Jean-Claude Latché

We study the design and implementation of numerical methods to solve the generalized Langevin equation (GLE) focusing on canonical sampling properties of numerical integrators. For this purpose, we cast the GLE in an extended phase space…

Numerical Analysis · Mathematics 2020-12-09 Benedict Leimkuhler , Matthias Sachs

The Vlasov-Poisson-BGK (VPBGK) model is a kinetic model for describing the dynamics of collisional plasmas. Although various numerical schemes have been developed for it, a corresponding convergence theory has been absent. This paper fills…

Numerical Analysis · Mathematics 2026-05-11 Seung Yeon Cho , Sungsu Park , Seok-Bae Yun

We develop a formulation for molecular dynamics, Langevin, and hybrid Monte Carlo algorithms in the recently proposed generalized ensemble that is based on a physically motivated realisation of Tsallis weights. The effectiveness of the…

Biological Physics · Physics 2016-09-08 Ulrich H. E. Hansmann , Frank Eisenmenger , Yuko Okamoto

We propose a novel discrete Poisson equation approach to estimate the statistical error of a broad class of numerical integrators for the underdamped Langevin dynamics. The statistical error refers to the mean square error of the estimator…

Numerical Analysis · Mathematics 2024-05-14 Xuda Ye , Zhennan Zhou

In this work we consider the unbiased estimation of expectations w.r.t.~probability measures that have non-negative Lebesgue density, and which are known point-wise up-to a normalizing constant. We focus upon developing an unbiased method…

Computation · Statistics 2023-08-17 Hamza Ruzayqat , Neil K. Chada , Ajay Jasra
‹ Prev 1 2 3 10 Next ›