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The Reduced Relativistic Gas (RRG) is a simplified version of the ideal relativistic gas, which assumes that all particles have the same momentum magnitude. Although this is a very idealized situation, the resulting model preserves the…

Cosmology and Nongalactic Astrophysics · Physics 2019-06-25 G. Pordeus-da-Silva , R. C. Batista , L. G. Medeiros

The macroscopic behavior of dissipative stochastic partial differential equations usually can be described by a finite dimensional system. This article proves that a macroscopic reduced model may be constructed for stochastic…

Mathematical Physics · Physics 2008-12-11 Wei Wang , A. J. Roberts

A model hierarchy that is based on the one-dimensional isothermal Euler equations of fluid dynamics is used for the simulation and optimisation of gas flow through a pipeline network. Adaptive refinement strategies have the aim of bringing…

Numerical Analysis · Mathematics 2017-02-01 Pia Domschke , Aseem Dua , Jeroen J. Stolwijk , Jens Lang , Volker Mehrmann

A procedure for generating random variates from a relativistic Maxwellian distribution with arbitrary temperature and drift velocity is presented. The algorithm is based on the rejection method and can be used to initialize particle…

Plasma Physics · Physics 2015-06-16 M. Swisdak

In numerical simulations of many charged systems at the micro/nano scale, a common theme is the repeated solution of the Poisson-Boltzmann equation. This task proves challenging, if not entirely infeasible, largely due to the nonlinearity…

Numerical Analysis · Mathematics 2018-08-29 Lijie Ji , Yanlai Chen , Zhenli Xu

In this paper, three efficient ensemble algorithms are proposed for fast-solving the random fluid-fluid interaction model. Such a model can be simplified as coupling two heat equations with random diffusion coefficients and a friction…

Numerical Analysis · Mathematics 2023-01-24 Yizhong Sun , Jiangshan Wang , Haibiao Zheng

Linear Mixed-Effects (LME) models are a fundamental tool for modeling clustered data, including cohort studies, longitudinal data analysis, and meta-analysis. The design and analysis of variable selection methods for LMEs is considerably…

Methodology · Statistics 2022-09-28 Aleksandr Aravkin , James Burke , Aleksei Sholokhov , Peng Zheng

A method for adaptive model order reduction for nonsmooth discrete element simulation is developed and analysed in numerical experiments. Regions of the granular media that collectively move as rigid bodies are substituted with rigid bodies…

Computational Physics · Physics 2015-12-02 Martin Servin , Da Wang

Based on multiple parallel short molecular dynamics simulation trajectories, we designed the reweighted ensemble dynamics (RED) method to more efficiently sample complex (biopolymer) systems, and to explore their hierarchical metastable…

Statistical Mechanics · Physics 2015-02-24 Linchen Gong , Xin Zhou , Zhong-Can Ou-Yang

In this paper we present computational techniques to investigate the solutions of two-component, nonlinear reaction-diffusion (RD) systems on arbitrary surfaces. We build on standard techniques for linear and nonlinear analysis of RD…

Computational Engineering, Finance, and Science · Computer Science 2016-05-06 Daljit Singh J. Dhillon , Michel C. Milinkovitch , Matthias Zwicker

We propose a novel method to fit and segment multi-structural data via convex relaxation. Unlike greedy methods --which maximise the number of inliers-- this approach efficiently searches for a soft assignment of points to models by…

Computer Vision and Pattern Recognition · Computer Science 2017-06-07 Paul Amayo , Pedro Pinies , Lina M. Paz , Paul Newman

This study addresses the challenge of simulating realistic particle systems by proposing a novel particle decomposition scheme that improves the parallel performance of surface resolved particle simulations. Realistic particle systems often…

Fluid Dynamics · Physics 2024-03-21 J. E. Marquardt , N. Hafen , M. J. Krause

High-speed chemically active flows present significant computational challenges due to their disparate space and time scales, where stiff chemistry often dominates simulation time. While modern supercomputing scientific codes achieve…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-04 Anthony Carreon , Jagmohan Singh , Shivank Sharma , Shuzhi Zhang , Venkat Raman

In fire spread simulations, heat transfer and pyrolysis are processes to describe the thermal degradation of solid material. In general, the necessary material parameters cannot be directly measured. They are implicitly deduced from micro-…

Fluid Dynamics · Physics 2023-06-28 Tristan Hehnen , Lukas Arnold

We consider stochastic descriptions of chemical reaction networks in which there are both fast and slow reactions, and for which the time scales are widely separated. We develop a computational algorithm that produces the generator of the…

Dynamical Systems · Mathematics 2015-12-11 Xingye Kan , Chang Hyeong Lee , Hans G. Othmer

First of all, this paper presents some improvements of DSMC method in the form of new schemes and approaches, that, for a wide class of problems, increase performance and reduce the demands on computer resources. The most important…

Fluid Dynamics · Physics 2012-01-16 Roman V. Maltsev

A method for generating random $U(1)$ variables with Boltzmann distribution is presented. It is based on the rejection method with transformation of variables. High efficiency is achieved for all range of temparatures or coupling…

High Energy Physics - Lattice · Physics 2009-10-22 Tetsuya Hattori , Hideo Nakajima

A quasiparticle description of various condensed media is a very popular tool in study of their transport and thermodynamic properties. I present here a microscopic theory for the description of diffusion processes in two-component gas of…

Statistical Mechanics · Physics 2009-11-07 Alexander V. Zhukov

We present a new algorithm, MULTIGRAIN, for modelling the dynamics of an entire population of small dust grains immersed in gas, typical of conditions that are found in molecular clouds and protoplanetary discs. The MULTIGRAIN method is…

Instrumentation and Methods for Astrophysics · Physics 2018-02-28 Mark A. Hutchison , Daniel J. Price , Guillaume Laibe

We present efficient algorithms to build data structures and the lists needed for fast multipole methods. The algorithms are capable of being efficiently implemented on both serial, data parallel GPU and on distributed architectures. With…

Mathematical Software · Computer Science 2013-01-10 Qi Hu , Nail A. Gumerov , Ramani Duraiswami