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In this paper, based on the previous work [B. Shi, Z. Guo, Lattice Boltzmann model for nonlinear convection-diffusion equations, Phys. Rev. E 79 (2009) 016701], we develop a general multiple-relaxation-time (MRT) lattice Boltzmann model for…

Computational Physics · Physics 2016-04-01 Zhenhua Chai , Baochang Shi , Zhaoli Guo

This paper presents a new paradigm to stabilize uncertain stochastic linear systems. Herein, second moment polytopic (SMP) systems are proposed that generalize systems with both uncertainty and randomness. The SMP systems are characterized…

Optimization and Control · Mathematics 2024-10-28 Yuji Ito , Kenji Fujimoto

We present the new Guided Moments ($\texttt{GM}$) formalism for neutrino modeling in astrophysical scenarios like core-collapse supernovae and neutron star mergers. The truncated moments approximation ($\texttt{M1}$) and Monte-Carlo…

High Energy Astrophysical Phenomena · Physics 2024-03-18 Manuel R. Izquierdo , J. Fernando Abalos , Carlos Palenzuela

A new lattice Boltzmann (LB) model is introduced, based on a regularization of the pre-collision distribution functions in terms of the local density, velocity, and momentum flux tensor. The model dramatically improves the precision and…

Fluid Dynamics · Physics 2007-05-23 Jonas Latt , Bastien Chopard

We study a class of Galilean-invariant one-dimensional Bethe ansatz solvable models in the thermodynamic limit. Their rapidity distribution obeys an integral equation with a difference kernel over a finite interval, which does not admit a…

Statistical Mechanics · Physics 2023-01-27 Zoran Ristivojevic

We present a new fully first order strongly hyperbolic representation of the BSSN formulation of Einstein's equations with optional constraint damping terms. We describe the characteristic fields of the system, discuss its hyperbolicity…

Boltzmann machines (BMs) are powerful energy-based generative models, but their heavy training cost has largely confined practical use to Restricted BMs (RBMs) trained with an efficient learning method called contrastive divergence. More…

Machine Learning · Computer Science 2025-12-03 Kentaro Kubo , Hayato Goto

We implement a high-order numerical scheme for the entropy-based moment closure, the so-called M$_N$ model, for linear kinetic equations in slab geometry. A discontinuous Galerkin (DG) scheme in space along with a strong-stability…

Numerical Analysis · Mathematics 2015-06-23 Graham Alldredge , Florian Schneider

Unique existence of analytically strong solutions to stochastic partial differential equations (SPDE) with drift given by the subdifferential of a quasi-convex function and with general multiplicative noise is proven. The proof applies a…

Probability · Mathematics 2011-04-22 Benjamin Gess

When dealing with shallow water simulations, the velocity profile is often assumed to be constant along the vertical axis. However, since in many applications this is not the case, modeling errors can be significant. Hence, in this work, we…

Numerical Analysis · Mathematics 2025-01-15 C. Caballero-Cárdenas , I. Gómez-Bueno , A. del Grosso , J. Koellermeier , T. Morales de Luna

In the hyperbolic community, discontinuous Galerkin approaches are mainly applied when finite element methods are considered. As the name suggested, the DG framework allows a discontinuity at the element interfaces, which seems for many…

Numerical Analysis · Mathematics 2021-04-20 Rémi Abgrall , Jan Nordström , Philipp Öffner , Svetlana Tokareva

Several applications exist in which lattice Boltzmann methods (LBM) are used to compute stationary states of fluid motions, particularly those driven or modulated by external forces. Standard LBM, being explicit time-marching in nature,…

Computational Physics · Physics 2009-11-13 Kannan N. Premnath , Martin J. Pattison , Sanjoy Banerjee

This is the second paper in a series in which we develop machine learning (ML) moment closure models for the radiative transfer equation (RTE). In our previous work \cite{huang2021gradient}, we proposed an approach to directly learn the…

Numerical Analysis · Mathematics 2021-06-01 Juntao Huang , Yingda Cheng , Andrew J. Christlieb , Luke F. Roberts , Wen-An Yong

The Stochastic Weighted Particle Method (SWPM) is a Monte Carlo technique developed by Rjasanow and Wagner that generalizes Bird's Direct Simulation Monte Carlo (DSMC) method for solving the Boltzmann equation. To reduce computational cost…

Numerical Analysis · Mathematics 2021-01-06 Sonam Lama , John Zweck , Matthew Goeckner

In this paper, we first present a multiple-relaxation-time lattice Boltzmann (MRT-LB) model for one-dimensional diffusion equation where the D1Q3 (three discrete velocities in one-dimensional space) lattice structure is considered. Then…

Numerical Analysis · Mathematics 2021-08-04 Yuxin Lin , Ning Hong , Baochang Shi , Zhenhua Chai

In this paper we deal with the extension of the Fast Kinetic Scheme (FKS) [J. Comput. Phys., Vol. 255, 2013, pp 680-698] originally constructed for solving the BGK equation, to the more challenging case of the Boltzmann equation. The scheme…

Numerical Analysis · Mathematics 2016-08-30 Giacomo Dimarco , Raphaël Loubère , Jacek Narski , Thomas Rey

This work reports on the development and numerical implementation of the linear electromagnetic gyrokinetic (GK) model in a tokamak flux-tube geometry using a moment approach based on the expansion of the perturbed distribution function on…

Plasma Physics · Physics 2022-10-13 B. J. Frei , A. C. D. Hoffmann , P. Ricci , S. Brunner , Z. Tecchiolli

A kinetic model for granular mixtures is considered to study three different non-equilibrium situations. The model is based on the equivalence between a gas of elastic hard spheres subjected to a drag force proportional to the particle…

Soft Condensed Matter · Physics 2025-02-27 Pablo Avilés , David González Méndez , Vicente Garzó

The purpose of this paper is to estimate the limiting variance of asymptotically stationary Gaussian processes observed at high frequency, using the second moment estimator (SME). We study rates of convergence of the central limit theorem…

Probability · Mathematics 2026-03-06 Khalifa Es-Sebaiy , Yong Chen

Thermal fluctuations play a central role in fluid dynamics at mesoscopic scales and must be incorporated into numerical schemes in a manner consistent with statistical mechanics. In this work, we develop a fluctuating lattice Boltzmann…

Fluid Dynamics · Physics 2026-02-19 Alessandro De Rosis , Yang Zhou