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In this paper, we develop and analyze a stochastic algorithm for solving space-time fractional diffusion models, which are widely used to describe anomalous diffusion dynamics. These models pose substantial numerical challenges due to the…

Numerical Analysis · Mathematics 2025-08-29 Tengteng Cui , Chengtao Sheng , Bihao Su , Zhi Zhou

A recently introduced stochastic model for fluid flow can be made Galilean invariant by introducing a random shift of the computational grid before collisions. This grid shifting procedure accelerates momentum transfer between cells and…

Soft Condensed Matter · Physics 2009-11-10 Thomas Ihle , Erkan Tuzel , Daniel M. Kroll

Car following (CF) models are fundamental to describing traffic dynamics. However, the CF behavior of human drivers is highly stochastic and nonlinear. As a result, identifying the best CF model has been challenging and controversial…

Machine Learning · Computer Science 2023-12-19 Jiwan Jiang , Yang Zhou , Xin Wang , Soyoung Ahn

Score-based diffusion models currently constitute the state of the art in continuous generative modeling. These methods are typically formulated via overdamped or underdamped Ornstein--Uhlenbeck-type stochastic differential equations, in…

Machine Learning · Computer Science 2025-12-22 Herlock Rahimi

We present a method to compute transport coefficients in molecular dynamics. Transport coefficients quantify the linear dependencies of fluxes in non-equilibrium systems subject to small external forcings. Whereas standard non-equilibrium…

Statistical Mechanics · Physics 2023-05-17 Noé Blassel , Gabriel Stoltz

In order to predict future performance of subsurface fluid reservoirs under possible operating scenarios, a dynamic, porous-medium flow simulation model must be tuned to include representative properties of the reservoir. Estimating…

Geophysics · Physics 2026-02-04 Zhen Zhang , Xuebin Zhao , Andrew Curtis

In this work, we explore a time-fractional diffusion equation of order $\alpha \in (0,1)$ with a stochastic diffusivity parameter. We focus on efficient estimation of the expected values (considered as an infinite dimensional integral on…

Numerical Analysis · Mathematics 2024-09-04 Josef Dick , Hecong Gao , William McLean , Kassem Mustapha

The Green function (GF) equation of motion technique for solving the effective two-band Hubbard model of high-T_c superconductivity in cuprates [N.M. Plakida et al., Phys. Rev. B, v. 51, 16599 (1995); JETP, v. 97, 331 (2003)] rests on the…

Superconductivity · Physics 2009-11-13 Gh. Adam , S. Adam

Physics-guided sampling with diffusion model priors has shown promise for solving partial differential equation (PDE) governed problems, but applications to chemically meaningful reaction-transport systems remain limited. We apply…

Chemical Physics · Physics 2026-03-06 Andrew Millard , Henrik Pedersen

We consider the numerical solution of scalar, nonlinear degenerate convection-diffusion problems with random diffusion coefficient and with random flux functions. Building on recent results on the existence, uniqueness and continuous…

Analysis of PDEs · Mathematics 2013-11-08 U. Koley , N. H. Risebro , Ch. Schwab , F. Weber

An analytical Green's function is developed to study the acoustic scattering by a flat plate with a serrated edge. The scattered pressure is solved using the Wiener-Hopf technique in conjunction with the adjoint technique. It is shown that…

Fluid Dynamics · Physics 2023-05-10 Benshuai Lyu

The stochastic differential and integral equations describing the system of particles weakly interacting among themselves which are absorbed and scattered by particles of a medium are considered. The time-dependent transport equation with…

Mathematical Physics · Physics 2010-03-15 Igor Kharin

We present a numerical formulation for the solution of non-isothermal, compressible, Navier-Stokes equations with thermal fluctuations to describe mesoscale transport phenomena in multispecies fluid mixtures. The novelty of our numerical…

We used methods of Bayesian statistical inference and the principle of maximum entropy to analytically continue imaginary-time Green's function generated in quantum Monte Carlo simulations to obtain the real-time Green's functions. For test…

Condensed Matter · Physics 2009-10-28 J. Bonca , J. E. Gubernatis

We present a new method for extracting numerically exact imaginary-time Green functions from standard Hirsch-Fye quantum Monte Carlo (HF-QMC) simulations within dynamical mean-field theory. By analytic continuation, angular resolved spectra…

Strongly Correlated Electrons · Physics 2007-12-11 N. Blümer

We have developed a Green's function formalism to compute the local field distribution near an interface separating two media of different dielectric constants. The Maxwell's equations are converted into a surface integral equation; thus it…

Soft Condensed Matter · Physics 2007-05-23 K. W. Yu , Jones T. K. Wan

We propose an optimization framework for stochastic optimal power flow with uncertain loads and renewable generator capacity. Our model follows previous work in assuming that generator outputs respond to load imbalances according to an…

Optimization and Control · Mathematics 2019-10-11 Rohit Kannan , James R. Luedtke , Line A. Roald

Phonon Monte Carlo (PMC) is a versatile stochasic technique for solving the Boltzmann transport equation for phonons. It is particularly well suited for analyzing thermal transport in structures that have real-space roughness or are too…

Mesoscale and Nanoscale Physics · Physics 2016-02-26 L. N. Maurer , S. Mei , I. Knezevic

A novel scheme to solve the quantum eigenvalue problem through the imaginary-time Green function Monte Carlo method is presented. This method is applicable to the excited states as well as to the ground state of a generic system. We…

Nuclear Theory · Physics 2008-11-26 Taksu Cheon

We prove quantitative estimates on the the parabolic Green function and the stationary invariant measure in the context of stochasic homogenization of elliptic equations in nondivergence form. We consequently obtain a quenched, local CLT…

Analysis of PDEs · Mathematics 2025-12-02 Scott Armstrong , Benjamin Fehrman , Jessica Lin