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This work describes a new 1D hybrid approach for modeling atmospheric pressure discharges featuring complex chemistry. In this approach electrons are described fully kinetically using Particle-In-Cell/Monte-Carlo (PIC/MCC) scheme, whereas…

Plasma Physics · Physics 2016-01-20 Denis Eremin , Torben Hemke , Thomas Mussenbrock

In nuclear fusion and fission, fluctuation and dissipation arise due to the coupling of collective degrees of freedom with internal excitations. Close to the barrier, both quantum, statistical and non-Markovian effects are expected to be…

Nuclear Theory · Physics 2010-04-06 G. Hupin , D. Lacroix

We provide a both qualitative and quantitative comparison among different approaches aimed to solve the problem of non-linear diffusive acceleration of particles at shocks. In particular, we show that state-of-the-art models (numerical,…

High Energy Astrophysical Phenomena · Physics 2015-03-17 D. Caprioli , Hyesung Kang , A. Vladimirov , T. W. Jones

A continuous-time formulation of the Diffusion Monte Carlo method for lattice models is presented. In its simplest version, without the explicit use of trial wavefunctions for importance sampling, the method is an excellent tool for…

Strongly Correlated Electrons · Physics 2009-11-10 Olav F. Syljuasen

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

We apply the Direct Simulation Monte Carlo (DSMC) method, developed originally to calculate rarefied gas dynamical problems, to study the gas flow in an accretion disc in a close binary system. The method involves viscosity and thermal…

Astrophysics · Physics 2007-05-23 Takuya Matsuda , Hiromi Mizutani , Henri M. J. Boffin

The shape evolution of two-dimensional islands under electromigration-driven periphery diffusion is studied by kinetic Monte Carlo (KMC) simulations and continuum theory. The energetics of the KMC model is adapted to the Cu(100) surface,…

Materials Science · Physics 2015-06-25 Marko Rusanen , Philipp Kuhn , Joachim Krug

We present in this paper a hybrid, Multi-Level Monte Carlo (MLMC) method for solving the neutral particle transport equation. MLMC methods, originally developed to solve parametric integration problems, work by using a cheap, low fidelity…

Numerical Analysis · Mathematics 2025-08-06 Vincent N. Novellino , Dmitriy Y. Anistratov

We propose a new Monte Carlo scheme to study the late-time dynamics of a 2-dim hard sphere fluid, modeled by a tethered network of hard spheres. Fluidity is simulated by breaking and reattaching the flexible tethers. We study the diffusion…

Condensed Matter · Physics 2007-05-23 P. B. Sunil Kumar , Madan Rao

Atomic force calculations within the variational and diffusion quantum Monte Carlo (VMC and DMC) methods are described. The advantages of calculating DMC forces with the "pure" rather than the "mixed" probability distribution are discussed.…

Materials Science · Physics 2010-02-15 A. Badinski , P. D. Haynes , J. R. Trail , R. J. Needs

The Direct Simulation Monte Carlo (DSMC) method is widely employed for simulating rarefied nonequilibrium gas flows. With advances in aerospace engineering and micro/nano-scale technologies, gas flows exhibit the coexistence of rarefied and…

Computational Physics · Physics 2025-07-01 Hao Jin , Sha Liu , Sirui Yang , Junzhe Cao , Congshan Zhuo , Chengwen Zhong

Monte Carlo methods play important part in modern statistical physics. The application of these methods suffer from two main difficulties.The first is caused by the relatively small number of particles that can participate in any numerical…

Statistical Mechanics · Physics 2007-05-23 A. Brandt , V. Ilyin

We report on the development of a test-particle based kinetic Monte Carlo code for large systems and its application to simulate matter in the continuum regime. Our code combines advantages of the Direct Simulation Monte Carlo and the…

Fluid Dynamics · Physics 2014-07-31 Irina Sagert , Wolfgang Bauer , Dirk Colbry , Rodney Pickett , Terrance Strother

We extend to multi-dimensions the work of [1], where new fully explicit kinetic methods were built for the approximation of linear and non-linear convection-diffusion problems. The fundamental principles from the earlier work are retained:…

Numerical Analysis · Mathematics 2023-12-29 Gauthier Wissocq , Rémi Abgrall

In this work we investigate the ground state and the dissipative quantum dynamics of interacting charged particles in an external potential at finite temperature. The recently devised time-dependent quantum Monte Carlo (TDQMC) method allows…

Quantum Physics · Physics 2025-01-29 Ivan P. Christov

By means of detailed Monte Carlo (MC) simulations, we have presented dynamic phase transition (DPT) properties of ferromagnetic thin-films. Thermal variations of surface, bulk and total dynamical order parameters (DOP) for a film and total…

Statistical Mechanics · Physics 2016-01-06 Bahadır Ozan Aktaş , Erol Vatansever , Hamza Polat

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

A new approach to simulation of stationary flows by Direct Simulation Monte Carlo method is proposed. The idea is to specify an individual time step for each component of a gas mixture. The approach consists of modifications mainly to…

Computational Physics · Physics 2016-08-24 Roman V. Maltsev

A macroscopic mesoscopic, deterministic stochastic coupling strategy is proposed to accelerate the direct simulation Monte Carlo (DSMC) method for chemical reaction. First, a macroscopic synthetic equation is formulated by integrating…

Computational Physics · Physics 2026-05-14 Hong Deng , Liyan Luo , Lei Wu

One of the open challenges in quantum computing is to find meaningful and practical methods to leverage quantum computation to accelerate classical machine learning workflows. A ubiquitous problem in machine learning workflows is sampling…

Quantum Physics · Physics 2024-08-08 Owen Lockwood , Peter Weiss , Filip Aronshtein , Guillaume Verdon
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