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We formulate a class of velocity-free finite-particle methods for mass transport problems based on a time-discrete incremental variational principle that combines entropy and the cost of particle transport, as measured by the Wasserstein…

Computational Physics · Physics 2023-05-10 Anna Pandolfi , Laurent Stainier , Michael Ortiz

The behavior of a Lattice Monte Carlo algorithm (if it is designed correctly) must approach that of the continuum system that it is designed to simulate as the time step and the mesh step tend to zero. However, we show for an algorithm for…

Statistical Mechanics · Physics 2010-08-23 Mykyta V. Chubynsky , Gary W. Slater

This paper proposes a numerical upscaling procedure for elliptic boundary value problems with diffusion tensors that vary randomly on small scales. The resulting effective deterministic model is given through a quasilocal discrete integral…

Numerical Analysis · Mathematics 2019-01-24 Dietmar Gallistl , Daniel Peterseim

In this paper, we are interested in deriving non-asymptotic error bounds for the multilevel Monte Carlo method. As a first step, we deal with the explicit Euler discretization of stochastic differential equations with a constant diffusion…

Probability · Mathematics 2018-10-19 Benjamin Jourdain , Ahmed Kebaier

Behavior of the mixture of particles and dimers moving with different jump rates at reconstructed surfaces is described. Collective diffusion coefficient is calculated by the variational approach. Anisotropy of the collective particle…

Statistical Mechanics · Physics 2014-05-12 Marcin Mińkowski , Magdalena A. Załuska Kotur

The prediction of diffusion in solids is necessary to understand the microstructure evolution in materials out of equilibrium. Although one can reasonably predict diffusive transport coefficients using atomistic methods, these approaches…

Materials Science · Physics 2025-08-07 Jacob Jeffries , Emilio Mendoza Reyes , Fadi Abdeljawad , Murray Daw , Enrique Martinez

We consider the application of multilevel Monte Carlo methods to steady state Darcy flow in a random porous medium, described mathematically by elliptic partial differential equations with random coefficients. The levels in the multilevel…

Numerical Analysis · Mathematics 2015-06-16 Minho Park , Aretha Teckentrup

We study passive scalar mixing by parallel shear flows in the presence of weak molecular diffusion. We recover the sharp uniform-in-diffusivity mixing rate for shear flows with finitely many critical points, recently proven in [1]. Our…

Analysis of PDEs · Mathematics 2026-03-11 Kyle L. Liss , Kunhui Luan

We present a more accurate numerical scheme for the calculation of diffusive shock acceleration of cosmic rays using Stochastic Differential Equations. The accuracy of this scheme is demonstrated using a simple analytical flow profile that…

High Energy Astrophysical Phenomena · Physics 2011-03-17 A. Achterberg , K. M. Schure

Direct comparisons of diffusive particle acceleration numerical simulations have been made against Monte Carlo and hybrid plasma simulations by Ellison {\it et. al.} (1993) and against observations at the earth's bow shock presented by…

Astrophysics · Physics 2016-08-30 Hyesung Kang , T. W. Jones

Quantum mechanics for many-body systems may be reduced to the evaluation of integrals in 3N dimensions using Monte-Carlo, providing the Quantum Monte Carlo ab initio methods. Here we limit ourselves to expectation values for trial…

Computational Physics · Physics 2010-11-22 John Robert Trail , Ryo Maezono

We propose a new approach to quantize the marginals of the discrete Euler diffusion process. The method is built recursively and involves the conditional distribution of the marginals of the discrete Euler process. Analytically, the method…

Probability · Mathematics 2015-05-25 Gilles Pagès , Abass Sagna

We propose a nonlinear Discrete Duality Finite Volume scheme to approximate the solutions of drift diffusion equations. The scheme is built to preserve at the discrete level even on severely distorted meshes the energy / energy dissipation…

Analysis of PDEs · Mathematics 2017-05-31 Clément Cancès , Claire Chainais-Hillairet , Stella Krell

We discuss the efficiency of Monte Carlo methods in solving continuum radiative transfer problems. The sampling of the radiation field and convergence of dust temperature calculations in the case of optically thick clouds are both studied.…

Astrophysics · Physics 2009-11-10 M. Juvela

We consider the Cauchy problem for a stochastic scalar parabolic-hyperbolic equation in any space dimension with nonlocal, nonlinear, and possibly degenerate diffusion terms. The equations are nonlocal because they involve fractional…

Analysis of PDEs · Mathematics 2020-08-10 Neeraj Bhauryal , Ujjwal Koley , Guy Vallet

If a stochastic system during some periods of its evolution can be divided into non-interacting parts, the kinetics of each part can be simulated independently. We show that this can be used in the development of efficient Monte Carlo…

Materials Science · Physics 2009-11-13 V. I. Tokar , H. Dreyssé

A geometric numerical method for simulating suspensions of spherical and non-spherical particles with Stokes drag is proposed. The method combines divergence-free matrix-valued radial basis function interpolation of the fluid velocity field…

Computational Physics · Physics 2021-02-26 Benjamin K. Tapley , Helge I. Andersson , Elena Celledoni , Brynjulf Owren

Direct numerical simulation of diffusion through heterogeneous media can be difficult due to the computational cost of resolving fine-scale heterogeneities. One method to overcome this difficulty is to homogenize the model by replacing the…

Numerical Analysis · Mathematics 2020-11-24 Nathan G. March , Elliot J. Carr , Ian W. Turner

Given the importance of continuous-time stochastic volatility models to describe the dynamics of interest rates, we propose a goodness-of-fit test for the parametric form of the drift and diffusion functions, based on a marked empirical…

Discrete diffusion models have gained increasing attention for their ability to model complex distributions with tractable sampling and inference. However, the error analysis for discrete diffusion models remains less well-understood. In…

Machine Learning · Computer Science 2025-03-04 Yinuo Ren , Haoxuan Chen , Grant M. Rotskoff , Lexing Ying