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In simulations of crystals, unlike liquids or gases, it may happen that the properties of the studied system depend not only on the volume of the simulation cell but also on its shape. For such cases it is desirable to change the shape of…

Computational Physics · Physics 2022-10-04 A. Baumketner

We determine how MRI-turbulent stresses depend on gas pressure via a suite of unstratified shearing box simulations. Earlier numerical work reported only a very weak dependence at best, results that call into question the canonical…

High Energy Astrophysical Phenomena · Physics 2015-11-11 Johnathan Ross , Henrik N. Latter , Jerome Guilet

We describe and analyze some Monte Carlo methods for manifolds in Euclidean space defined by equality and inequality constraints. First, we give an MCMC sampler for probability distributions defined by un-normalized densities on such…

Numerical Analysis · Mathematics 2017-09-21 Emilio Zappa , Miranda Holmes-Cerfon , Jonathan Goodman

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

We have carried out molecular dynamics simulations of the crystallization of hard spheres modelling colloidal systems that are studied in conventional and space-based experiments. We use microscopic probes to investigate the effects of…

Condensed Matter · Physics 2009-11-07 Igor Volkov , Marek Cieplak , Joel Koplik , Jayanth R. Banavar

We introduce an ambidextrous view of stochastic dynamical systems, comparing their forward-time and reverse-time representations and then integrating them into a single time-symmetric representation. The perspective is useful theoretically,…

Statistical Mechanics · Physics 2015-05-13 Christopher J. Ellison , John R. Mahoney , James P. Crutchfield

On the base of a Feynman-Kac--type formula involving Poisson stochastic processes, recently a Monte Carlo algorithm has been introduced, which describes exactly the real- or imaginary-time evolution of many-body lattice quantum systems. We…

Other Condensed Matter · Physics 2011-07-19 Massimo Ostilli , Carlo Presilla

The reliability of a complex industrial system can rarely be assessed analytically. As system failure is often a rare event, crude Monte-Carlo methods are prohibitively expensive from a computational point of view. In order to reduce…

Computation · Statistics 2019-06-03 H. Chraibi , A. Dutfoy , T. Galtier , J. Garnier

To minimise systematic errors in Monte Carlo simulations of charged particles, long range electrostatic interactions have to be calculated accurately and efficiently. Standard approaches, such as Ewald summation or the naive application of…

Computational Physics · Physics 2021-02-24 William Robert Saunders , James Grant , Eike Hermann Müller

Simulation plays a central role in scientific discovery. In many applications, the bottleneck is no longer running a simulator; it is choosing among large families of plausible simulators, each corresponding to different forward…

Packing problems have been a source of fascination for millenia and their study has produced a rich literature that spans numerous disciplines. Investigations of hard-particle packing models have provided basic insights into the structure…

Statistical Mechanics · Physics 2018-08-01 Salvatore Torquato

We perform Monte Carlo simulation of the thermodynamic and structural properties of Hard-, Square-Well, and Square-Shoulder Disks in narrow channels. For the thermodynamics we study the internal energy per particle and the longitudinal and…

Statistical Mechanics · Physics 2024-04-15 Riccardo Fantoni

Detailed models of galactic disk formation and evolution require knowledge about the initial conditions under which disk galaxies form, the boundary conditions that affect their secular evolution and the micro-physical processes that drive…

Astrophysics · Physics 2015-05-13 Andreas Burkert

Markov chain Monte Carlo is a class of algorithms for drawing Markovian samples from high-dimensional target densities to approximate the numerical integration associated with computing statistical expectation, especially in Bayesian…

Computation · Statistics 2018-03-28 Khoa T. Tran

Hyperbolic cross approximation is a special type of multivariate approximation. Recently, driven by applications in engineering, biology, medicine and other areas of science new challenging problems have appeared. The common feature of…

Numerical Analysis · Mathematics 2017-04-24 Dinh Dũng , Vladimir N. Temlyakov , Tino Ullrich

A key challenge in complex design problems that permeate science and engineering is the need to balance design objectives for specific design elements or subsystems with global system objectives. Global objectives give rise to competing…

Physics and Society · Physics 2018-12-11 Andrei A. Klishin , Colin P. F. Shields , David J. Singer , Greg van Anders

The fluid-structure interaction between a thin circular disk and its turbulent wake is investigated experimentally and described with a low-order stochastic model. The disk faces a uniform flow at Reynolds number Re=133 000 and can rotate…

Fluid Dynamics · Physics 2019-02-20 E. Boujo , O. Cadot

Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform…

Statistical Mechanics · Physics 2015-06-19 Jean-Charles Walter , Gerard Barkema

Continuous-time random disturbances from the renewable generation pose a significant impact on power system dynamic behavior. In evaluating this impact, the disturbances must be considered as continuous-time random processes instead of…

Optimization and Control · Mathematics 2020-07-09 Yiwei Qiu , Jin Lin , Xiaoshuang Chen , Feng Liu , Yonghua Song

We present a novel technique to incorporate precision calculations from quantum chromodynamics into fully differential particle-level Monte-Carlo simulations. By minimizing an information-theoretic quantity subject to constraints, our…

High Energy Physics - Phenomenology · Physics 2025-09-19 Benoît Assi , Stefan Höche , Kyle Lee , Jesse Thaler