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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

In plasma edge simulations, kinetic Monte Carlo (MC) is often used to simulate neutral particles and estimate source terms. For large-sized reactors, like ITER and DEMO, high particle collision rates lead to a substantial computational cost…

Computational Engineering, Finance, and Science · Computer Science 2025-09-16 Zhirui Tang , Emil Løvbak , Julian Koellermeier , Giovanni Samaey

In plasma edge simulations, the behavior of neutral particles is often described by a Boltzmann--BGK equation. Solving this kinetic equation and estimating the moments of its solution are essential tasks, typically carried out using Monte…

Numerical Analysis · Mathematics 2025-12-30 Zhirui Tang , Julian Koellermeier , Emil Løvbak , Giovanni Samaey

We propose and investigate a new multi-level Monte Carlo scheme for numerical solutions of the kinetic Boltzmann equation for neutral species in edge plasmas. In particular, this method explicitly exploits a key structural property of…

Plasma Physics · Physics 2025-12-11 Gregory J. Parker , Maxim V. Umansky , Benjamin D. Dudson

Computer modeling of multicellular systems has been a valuable tool for interpreting and guiding in vitro experiments relevant to embryonic morphogenesis, tumor growth, angiogenesis and, lately, structure formation following the printing of…

Biological Physics · Physics 2015-05-28 Elijah Flenner , Lorant Janosi , Bogdan Barz , Adrian Neagu , Gabor Forgacs , Ioan Kosztin

We describe CPMC-Lab, a Matlab program for the constrained-path and phaseless auxiliary-field Monte Carlo methods. These methods have allowed applications ranging from the study of strongly correlated models, such as the Hubbard model, to…

Strongly Correlated Electrons · Physics 2014-10-14 Huy Nguyen , Hao Shi , Jie Xu , Shiwei Zhang

In the present work, we present a novel numerical algorithm to couple the Direct Simulation Monte Carlo method (DSMC) for the solution of the Boltzmann equation with a finite volume like method for the solution of the Euler equations.…

Numerical Analysis · Mathematics 2014-04-08 Pierre Degond , Giacomo Dimarco

In traffic flow modeling, incorporating uncertainty is crucial for accurately capturing the complexities of real-world scenarios. In this work we focus on kinetic models of traffic flow, where a key step is to design effective numerical…

Numerical Analysis · Mathematics 2025-01-28 Elisa Iacomini , Lorenzo Pareschi

The Dynamic Monte Carlo (DMC) method is an established molecular simulation technique for the analysis of the dynamics in colloidal suspensions. An excellent alternative to Brownian Dynamics or Molecular Dynamics simulation, DMC is…

Soft Condensed Matter · Physics 2020-07-15 Fabián A. García Daza , Alejandro Cuetos , Alessandro Patti

We present a new method to couple the Direct Simulation Monte Carlo (DSMC) algorithm with molecular dynamics (MD). The coupling approach generalizes prior coupling methods using a cell-based decision. The approach is supported by a lifting…

Computational Physics · Physics 2025-06-03 Tim Linke , Dane Sterbentz , Niels Grønbech-Jensen , Jean-Pierre Delplanque , Jonathan Belof

Computer simulation is an important tool for scientific progress, especially when lab experiments are either extremely costly and difficult or lack the required resolution. However, all of the simulation methods come with limitations. In…

Fluid Dynamics · Physics 2023-08-04 Edward R. Smith , Panagiotis E. Theodorakis

Linear kinetic Monte Carlo particle transport models are frequently employed in fusion plasma simulations to quantify atomic and surface effects on the main plasma flow dynamics. Separate codes are used for transport of neutral particles…

Plasma Physics · Physics 2015-06-03 J. Seebacher , A. Kendl

Many problems require to approximate an expected value by some kind of Monte Carlo (MC) sampling, e.g. molecular dynamics (MD) or simulation of stochastic reaction models (also termed kinetic Monte Carlo (kMC)). Often, we are furthermore…

Numerical Analysis · Mathematics 2019-02-18 Sandra Döpking , Sebastian Matera

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

This paper presents a class of one-dimensional cellular automata (CA) models on traffic flows, featuring nonlocal look-ahead interactions. We develop kinetic Monte Carlo (KMC) algorithms to simulate the dynamics. The standard KMC method can…

Numerical Analysis · Mathematics 2023-02-15 Yi Sun , Changhui Tan

Plasmas with varying collisionalities occur in many applications, such as tokamak edge regions, where the flows are characterized by significant variations in density and temperature. While a kinetic model is necessary for…

Computational Engineering, Finance, and Science · Computer Science 2017-07-27 Debojyoti Ghosh , Mikhail A. Dorf , Milo R. Dorr , Jeffrey A. F. Hittinger

In this paper we introduce and discuss numerical schemes for the approximation of kinetic equations for flocking behavior with phase transitions that incorporate uncertain quantities. This class of schemes here considered make use of a…

Numerical Analysis · Mathematics 2019-10-31 Jose Antonio Carrillo , Mattia Zanella

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

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

The basic idea of fast Monte Carlo (MC) simulations is to perform particle-based MC simulations with the excluded-volume interactions modeled by "soft" repulsive potentials that allow particle overlapping. This gives much faster system…

Soft Condensed Matter · Physics 2012-01-24 Qiang Wang
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