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Efficient Monte Carlo (MC) sampling of many-body systems with long-range electrostatics is often limited by the cost of per-move energy-difference evaluation under periodic boundary conditions. We present DMK-MC, an accelerated MC method…

Computational Physics · Physics 2026-01-15 Xuanzhao Gao , Shidong Jiang , Jiuyang Liang , Qi Zhou

Indirect imaging problems in biomedical optics generally require repeated evaluation of forward models of radiative transport, for which Monte Carlo is accurate yet computationally costly. We develop a novel approach to reduce this…

Computational Physics · Physics 2020-07-10 Callum M. Macdonald , Simon Arridge , Samuel Powell

A revised and greatly improved version of the 3D continuum radiative transfer code MC3D is presented. It is based on the Monte-Carlo method and solves the radiative transfer problem self-consistently. It is designed for the simulation of…

Astrophysics · Physics 2009-11-07 Sebastian Wolf

In this article, the convergence of a hybrid numerical method introduced in Daripa and Dutta (J. Comput. Phys., 335:249-282, 2017) has been established. This method integrates a discontinuous finite element method with a modified method of…

Numerical Analysis · Mathematics 2019-07-18 Prabir Daripa , Sourav Dutta

Frequency-dependent/hybrid approaches for stellar irradiation are of primary importance in numerical simulations of massive star formation. We seek to compare outflow and accretion mechanisms in star formation simulations. We investigate…

Instrumentation and Methods for Astrophysics · Physics 2020-03-11 R. Mignon-Risse , M. González , B. Commerçon , J. Rosdahl

The Direct Simulation Monte Carlo (DSMC) method was widely used to simulate low density gas flows with large Knudsen numbers. However, DSMC encounters limitations in the regime of lower Knudsen numbers (Kn<0.1). In such cases, approaches…

Transport coefficients associated with the mass flux of impurities immersed in a moderately dense granular gas of hard disks or spheres described by the inelastic Enskog equation are obtained by means of the Chapman-Enskog expansion. The…

Statistical Mechanics · Physics 2013-05-29 Vicente Garzo , Francisco Vega Reyes

This work aims at understanding of bold diagrammatic Monte Carlo (BDMC) methods for stochastic summation of Feynman diagrams from the angle of stochastic iterative methods. The convergence enhancement trick of the BDMC is investigated from…

Computational Physics · Physics 2020-02-25 Yingzhou Li , Jianfeng Lu

Diffusion Monte Carlo (DMC) is being recognized as a higher-accuracy, albeit more computationally expensive, alternative to Density Functional Theory (DFT) for energy predictions of catalytic systems. A major computational bottleneck in the…

Materials Science · Physics 2022-10-12 Gopal R. Iyer , Brenda M. Rubenstein

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

The fixed node diffusion Monte Carlo (DMC) method has attracted interest in recent years as a way to calculate properties of solid materials with high accuracy. However, the framework for the calculation of properties such as total…

Materials Science · Physics 2016-01-20 Jaehyung Yu , Lucas K. Wagner , Elif Ertekin

To sample from a general target distribution $p_*\propto e^{-f_*}$ beyond the isoperimetric condition, Huang et al. (2023) proposed to perform sampling through reverse diffusion, giving rise to Diffusion-based Monte Carlo (DMC).…

Machine Learning · Statistics 2024-01-15 Xunpeng Huang , Difan Zou , Hanze Dong , Yian Ma , Tong Zhang

The iterative Quasi-Monte Carlo (iQMC) method is a recently proposed method for multigroup neutron transport simulations. iQMC can be viewed as a hybrid between deterministic iterative techniques, Monte Carlo simulation, and Quasi-Monte…

Computational Physics · Physics 2024-01-09 Samuel Pasmann , Ilham Variansyah , C. T. Kelley , Ryan G. McClarren

In the 20+ years of Doppler observations of stars, scientists have uncovered a diverse population of extrasolar multi-planet systems. A common technique for characterizing the orbital elements of these planets is Markov chain Monte Carlo…

Earth and Planetary Astrophysics · Physics 2015-06-18 Benjamin E. Nelson , Eric B. Ford , Matthew J. Payne

In this paper we develop a direct simulation Monte Carlo (DSMC) method for simulating highly nonequilibrium dynamics of nearly degenerate ultra-cold gases. We show that our method can simulate the high-energy collision of two thermal clouds…

Quantum Gases · Physics 2012-10-16 A. C. J. Wade , D. Baillie , P. B. Blakie

This paper presents two novel ensemble domain decomposition methods for fast-solving the Stokes-Darcy coupled models with random hydraulic conductivity and body force. To address such random systems, we employ the Monte Carlo (MC) method to…

Numerical Analysis · Mathematics 2024-08-13 Chunchi Liu , Yao Rong , Yizhong Sun , Jiaping Yu , Haibiao Zheng

A new Monte-Carlo algorithm for calculating time-dependent radiative-transfer under the assumption of LTE is presented. Unlike flux-limited diffusion the method is polychromatic, includes scattering, and is able to treat the optically thick…

Solar and Stellar Astrophysics · Physics 2015-05-28 Tim J. Harries

Advanced algorithms are necessary to obtain faster-than-real-time dynamic simulations in a number of different physical problems that are characterized by widely disparate time scales. Recent advanced dynamic Monte Carlo algorithms that…

Materials Science · Physics 2016-11-23 M. A. Novotny

The Direct Simulation Monte Carlo (DSMC) method is the gold standard for non-equilibrium rarefied gas dynamics, yet its computational cost can be prohibitive, especially for near-continuum regimes and high-fidelity \emph{ab initio}…

Computational Physics · Physics 2026-02-26 Ehsan Roohi , Ahmad Shoja-Sani , Stefan Stefanov

One of the most significant drawbacks of the all-electron ab initio diffusion Monte Carlo (DMC) is that its computational cost drastically increases with the atomic number ($Z$), which typically scales with $Z^{\sim 6}$. In this study, we…

Computational Physics · Physics 2020-04-15 Kousuke Nakano , Ryo Maezono , Sandro Sorella
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