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Particle-In-Cell codes are widely used for plasma physics simulations. It is often the case that particles within a computational cell need to be split to improve the statistics or, in the case of non-uniform meshes, to avoid the…

Computational Physics · Physics 2021-04-22 Roch Smets , Nicolas Aunais , ANdrea Ciardi , Matthieu Drouin , Martin Campos-Pino , Philip Deegan

In this contribution we present the first formulation of a heterogeneous multiscale method for an incompressible immiscible two-phase flow system with degenerate permeabilities. The method is in a general formulation which includes…

Numerical Analysis · Mathematics 2014-11-24 Patrick Henning , Mario Ohlberger , Ben Schweizer

We propose a hybridizable discontinuous Galerkin (HDG) finite element method to approximate the solution of the time dependent drift-diffusion problem. This system involves a nonlinear convection diffusion equation for the electron…

Numerical Analysis · Mathematics 2018-11-27 Gang Chen , Peter Monk , Yangwen Zhang

We study parallel particle-in-cell (PIC) methods for low-temperature plasmas (LTPs), which discretize kinetic formulations that capture the time evolution of the probability density function of particles as a function of position and…

Computational Engineering, Finance, and Science · Computer Science 2025-08-12 James Almgren-Bell , Nader Al Awar , Dilip S Geethakrishnan , Milos Gligoric , George Biros

We describe a new model for the study of weakly-collisional, magnetized plasmas derived from exploiting the separation of the dynamics parallel and perpendicular to the magnetic field. This unique system of equations retains the particle…

Plasma Physics · Physics 2025-10-06 James Juno , Ammar Hakim , Jason M. TenBarge

Particle methods are less computationally efficient than grid based numerical solution of the Navier Stokes equation. However, they have important advantages including rigorous mass conservation, momentum conservation and isotropy. In…

Fluid Dynamics · Physics 2024-06-26 Paul Meakin , Zhijie Xu

Many modern production and measurement facilities incorporate multiphase systems at low pressures. In this region of flows at small, non-zero Knudsen- and low Mach numbers the classical mesoscopic Monte Carlo methods become increasingly…

Fluid Dynamics · Physics 2015-09-10 S. Schmieschek , D. K. N. Sinz , F. Keller , U. Nieken , J. Harting

We present a multiscale hybrid particle-field scheme for the simulation of relaxation and diffusion behavior of soft condensed matter systems. It combines particle-based Brownian dynamics and field-based local dynamics in an adaptive sense…

Soft Condensed Matter · Physics 2017-09-06 Shuanhu Qi , Friederike Schmid

We introduce a modified SPH approach that is based on discretising the particle density instead of the mass density. This approach makes it possible to use SPH particles with very different masses to simulate multi-phase flows with large…

Computational Physics · Physics 2016-09-08 Frank Ott , Erik Schnetter

In this paper, we present an efficient algorithm for the long time behavior of plasma simulations. We will focus on 4D drift-kinetic model, where the plasma's motion occurs in the plane perpendicular to the magnetic field and can be…

Numerical Analysis · Mathematics 2014-10-01 Francis Filbet , Chang Yang

Outstanding advances in solid-state laser technology, employing the optical parametric chirped-pulse-amplification (OPCPA) technique, have led physicists to focus laser pulses to highly-relativistic intensities which led to novel schemes…

Plasma Physics · Physics 2026-01-28 Szilárd Majorosi , Nasr Hafz , Zsolt Lécz

This paper reviews Vlasov-based numerical methods used to model plasma in space physics and astrophysics. Plasma consists of collectively behaving charged particles that form the major part of baryonic matter in the Universe. Many concepts…

Hybrid Monte Carlo is a powerful Markov Chain Monte Carlo method for sampling from complex continuous distributions. However, a major limitation of HMC is its inability to be applied to discrete domains due to the lack of gradient signal.…

Machine Learning · Computer Science 2021-03-02 Priyank Jaini , Didrik Nielsen , Max Welling

We develop a hybrid Monte Carlo method to efficiently compute the physical observables from the samplings of the Laughlin and the Moore-Read wave functions of fractional quantum Hall (FQH) systems. With the advancements in methodology,…

Strongly Correlated Electrons · Physics 2026-02-20 Ting-Tung Wang , Ha Quang Trung , Qianhui Xu , Min Long , Bo Yang , Zi Yang Meng

We present a hybrid particle/grid approach for simulating incompressible fluids on collocated velocity grids. We interchangeably use particle and grid representations of transported quantities to balance efficiency and accuracy. A novel…

Particle-in-cell methods with stochastic collision models are commonly used to simulate collisional plasma dynamics, with applications ranging from hypersonic flight to semiconductor manufacturing. Code verification of such methods is…

Computational Physics · Physics 2026-05-26 Brian A. Freno , William J. McDoniel , Christopher H. Moore , Neil R. Matula

Simulating the evolution of the local universe is important for studying galaxies and the intergalactic medium in a way free of cosmic variance. Here we present a method to reconstruct the initial linear density field from an input…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-22 Huiyuan Wang , H. J. Mo , Xiaohu Yang , Y. P. Jing , W. P. Lin

In this paper, we combine concepts of the generalized multiscale finite element method and mode decomposition methods to construct a robust local-global approach for model reduction of flows in high-contrast porous media. This is achieved…

Computational Physics · Physics 2013-01-25 Mehdi Ghommem , Michael Presho , Victor M. Calo , Yalchin Efendiev

In this manuscript, we present a novel approach for sampling from a continuous multivariate probability distribution, which may either be explicitly known (up to a normalization factor) or represented via empirical samples. Our method…

Machine Learning · Statistics 2025-03-14 Hamidreza Behjoo , Michael Chertkov

We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov-Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem,…

Numerical Analysis · Mathematics 2016-05-25 Xingyu Wang , Roman Samulyak , Xiangmin Jiao , Kwangmin Yu