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We present a novel flow-based kinetic approach, inspired by continuous normalizing flows, for plasma simulation that unifies the complementary strengths of direct Vlasov solvers and particle-based methods. By tracking the distribution…

Plasma Physics · Physics 2025-01-29 Bowen Zhu , Jian Wu , Yuanbo Lu

We summarize a series of numerical experiments of collisional dynamics in dense stellar systems such as globular clusters (GCs) and in weakly collisional plasmas using a novel simulation technique, the so-called Multi-particle collision…

This chapter is devoted to the computation of equilibrium (thermodynamic) properties of quantum systems. In particular, we will be interested in the situation where the interaction between particles is so strong that it cannot be treated as…

Mesoscale and Nanoscale Physics · Physics 2016-02-03 Alexei Filinov , Jens Böning , Michael Bonitz

The Kinetic-Diffusion Monte Carlo (KDMC) method is a powerful tool for simulating neutral particles in fusion reactors. It is a hybrid fluid-kinetic method that is significantly faster than pure kinetic methods at the cost of a small bias…

Numerical Analysis · Mathematics 2025-09-05 Thijs Steel , Vince Maes , Giovanni Samaey

We design and develop a new Particle-in-Cell (PIC) method for plasma simulations using Deep-Learning (DL) to calculate the electric field from the electron phase space. We train a Multilayer Perceptron (MLP) and a Convolutional Neural…

Plasma Physics · Physics 2021-07-07 Xavier Aguilar , Stefano Markidis

The plasma edge flow, situated at the intricate boundary between plasma and neutral particles, plays a pivotal role in the design of nuclear fusion devices such as divertors and pumps. Traditional numerical simulation methods, such as the…

Computational Physics · Physics 2024-11-14 Yifan Wen , Yanbing Zhang , Lei Wu

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

Quantum Monte Carlo (QMC) methods such as Variational Monte Carlo, Diffusion Monte Carlo or Path Integral Monte Carlo are the most accurate and general methods for computing total electronic energies. We will review methods we have…

Computational Physics · Physics 2007-05-23 David Ceperley , Mark Dewing , Carlo Pierleoni

Quantitative theory of interbilayer interactions is essential to interpret x-ray scattering data and to elucidate these interactions for biologically relevant systems. For this purpose Monte Carlo simulations have been performed to obtain…

Biological Physics · Physics 2009-10-31 Nikolai Gouliaev , John F. Nagle

The particle-in-cell (PIC) method has been widely used for plasma simulation, because of its noise-reduction capability and moderate computational cost. The immersed finite element (IFE) method is efficient for solving interface problems on…

Numerical Analysis · Mathematics 2019-10-18 Jinwei Bai , Yong Cao , Yuchuan Chu , Xu Zhang

We develop an all-electron path integral Monte Carlo (PIMC) method with free-particle nodes for warm dense matter and apply it to water and carbon plasmas. We thereby extend PIMC studies beyond hydrogen and helium to elements with core…

Materials Science · Physics 2012-03-22 Kevin Driver , Burkhard Militzer

The results of analytical approximations and extensive calculations based on a path integral Monte Carlo (PIMC) scheme are presented. A new (direct) PIMC method allows for a correct determination of thermodynamic properties such as energy…

Astrophysics · Physics 2007-05-23 V. Filinov , M. Bonitz , D. Kremp , W. -D. Kraeft , V. Fortov

Recent increases in supercomputing power, driven by the multi-core revolution and accelerators such as the IBM Cell processor, graphics processing units (GPUs) and Intel's Many Integrated Core (MIC) technology have enabled kinetic…

Sequential Monte Carlo methods, also known as particle methods, are a popular set of techniques for approximating high-dimensional probability distributions and their normalizing constants. These methods have found numerous applications in…

Computation · Statistics 2021-06-23 Jeremy Heng , Adrian N. Bishop , George Deligiannidis , Arnaud Doucet

Reliable simulations of correlated quantum systems, including high-temperature superconductors and frustrated magnets, are increasingly desired nowadays to further understanding of essential features in such systems. Quantum Monte Carlo…

Strongly Correlated Electrons · Physics 2019-03-28 Zi-Xiang Li , Hong Yao

picFoam is a fully kinetic electrostatic Particle-in-Cell(PIC) solver, including Monte Carlo Collisions(MCC), for non-equilibrium plasma research in the open-source framework of OpenFOAM. The solver's modular design, based on the same…

Plasma Physics · Physics 2021-02-09 Christoph Kühn , Rodion Groll

Solids facing a plasma are a common situation in many astrophysical systems and laboratory setups. Moreover, many plasma technology applications rely on the control of the plasma-surface interaction. However, presently often a fundamental…

Plasma Physics · Physics 2019-12-20 M Bonitz , A Filinov , J W Abraham , K Balzer , H Kählert , E Pehlke , FX Bronold , M Pamperin , M M Becker , D Loffhagen , H Fehske

In this work, we introduce a simple modification of the Monte Carlo algorithm, which we call step Monte Carlo (sMC). The sMC approach allows to simulate processes far from equilibrium and obtain information about the dynamic properties of…

Other Condensed Matter · Physics 2023-12-15 Dariusz Sztenkiel

The Vlasov-Poisson system describes the time evolution of a plasma in the so-called collisionless regime. The investigation of a high-temperature plasma that is influenced by an exterior magnetic field is one of the most significant aspects…

Optimization and Control · Mathematics 2024-07-11 Jan Bartsch , Patrik Knopf , Stefania Scheurer , Jörg Weber

Nonlinear non-Gaussian state-space models are ubiquitous in statistics, econometrics, information engineering and signal processing. Particle methods, also known as Sequential Monte Carlo (SMC) methods, provide reliable numerical…

Computation · Statistics 2015-09-11 Nikolas Kantas , Arnaud Doucet , Sumeetpal S. Singh , Jan Maciejowski , Nicolas Chopin