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The new {\em ab initio} quantum path integral Monte Carlo approach has been developed and applied for the entropy difference calculations for the strongly coupled degenerated uniform electron gas (UEG), a well--known model of simple metals.…

Plasma Physics · Physics 2021-07-28 Vladimir Filinov , Pavel Levashov , Alexander Larkin

We have developed a Python package ZMCintegral for multi-dimensional Monte Carlo integration on multiple Graphics Processing Units(GPUs). The package employs a stratified sampling and heuristic tree search algorithm. We have built three…

Computational Physics · Physics 2022-09-19 Hong-Zhong Wu , Jun-Jie Zhang , Long-Gang Pang , Qun Wang

We present a multilevel Monte Carlo simulation method for analysing multi-scale physical systems via a hierarchy of coarse-grained representations, to obtain numerically-exact results, at the most detailed level. We apply the method to a…

Statistical Mechanics · Physics 2022-10-04 Paul B. Rohrbach , Hideki Kobayashi , Robert Scheichl , Nigel B. Wilding , Robert L. Jack

We created an efficient algorithm suitable for graphics processing units (GPUs) to perform Monte Carlo simulations of a subset of reaction-diffusion models. The algorithm uses techniques that are specific to GPU programming, and combines…

Computational Physics · Physics 2013-03-06 R. D. Schram

We demonstrate that substantial progress can be achieved in the study of the phase structure of 4-dimensional compact QED by a joint use of hybrid Monte Carlo and multicanonical algorithms, through an efficient parallel implementation. This…

High Energy Physics - Lattice · Physics 2015-06-25 G. Arnold , Th. Lippert , K. Schilling

A simple and efficient method for quantum Monte Carlo simulation is presented, based on discretization of the action in the path integral, and a Gaussian averaging of the potential, which works well e.g. with the Coulomb potential.

Computational Physics · Physics 2007-05-23 Jan Myrheim

Finite detector resolution and limited acceptance require to apply unfolding methods in high energy physics experiments. Information on the detector resolution is usually given by a set of Monte Carlo events. Based on the experience with a…

High Energy Physics - Experiment · Physics 2007-05-23 Volker Blobel

The Multilevel Monte Carlo (MLMC) method has proven to be an effective variance-reduction statistical method for Uncertainty Quantification (UQ) in Partial Differential Equation (PDE) models, combining model computations at different levels…

Mathematical Software · Computer Science 2023-05-24 Santiago Badia , Jerrad Hampton , Javier Principe

We investigate a hybrid numerical algorithm aimed at the large-scale cosmological N-body simulation for the on-going and the future high precious sky surveys. It makes use of a truncated Fast Multiple Method (FMM) for short-range gravity,…

Computational Physics · Physics 2021-01-13 Qiao Wang

We discuss the efficiency of Monte Carlo methods in solving continuum radiative transfer problems. The sampling of the radiation field and convergence of dust temperature calculations in the case of optically thick clouds are both studied.…

Astrophysics · Physics 2009-11-10 M. Juvela

We present a new Monte Carlo method which couples Path Integral for finite temperature protons with Quantum Monte Carlo for ground state electrons, and we apply it to metallic hydrogen for pressures beyond molecular dissociation. This…

Statistical Mechanics · Physics 2009-11-10 Markus Holzmann , Carlo Pierleoni , David M. Ceperley

We present an approach to calculation of point defect optical and thermal ionization energies based on the highly accurate quantum Monte Carlo methods. The use of an inherently many-body theory that directly treats electron correlation…

Materials Science · Physics 2015-06-11 Elif Ertekin , Lucas K. Wagner , Jeffrey C. Grossman

We analyze a new Monte Carlo method which uses transition matrix in the space of energy. This method gives an efficient reweighting technique. The associated artificial dynamics is a constrained random walk in energy, producing the result…

Statistical Mechanics · Physics 2009-10-31 Jian-Sheng Wang

We describe an efficient algorithm to compute forces in quantum Monte Carlo using adjoint algorithmic differentiation. This allows us to apply the space warp coordinate transformation in differential form, and compute all the 3M force…

Other Condensed Matter · Physics 2015-05-20 Sandro Sorella , Luca Capriotti

Methods for computing the integral of the Planck blackbody function over a finite spectral range, the so-called incomplete Planck integral, are necessary to perform multigroup radiative transfer calculations. We present a comparison, in…

Computational Physics · Physics 2025-03-13 Whit Lewis , Ryan G. McClarren

We introduce a new strategy for coupling the parallel in time (parareal) iterative methodology with multiscale integrators. Following the parareal framework, the algorithm computes a low-cost approximation of all slow variables in the…

Numerical Analysis · Mathematics 2015-11-19 Gil Ariel , Seong Jun Kim , Richard Tsai

A general synthetic iterative scheme is proposed to solve the Enskog equation within a Monte Carlo framework. The method demonstrates rapid convergence by reducing intermediate Monte Carlo evolution and preserves the asymptotic-preserving…

Fluid Dynamics · Physics 2025-09-26 Bin Hu , Liyan Luo , Lei Wu

We present a new Monte Carlo method which couples Path Integral for finite temperature protons with Quantum Monte Carlo for ground state electrons, and we apply it to metallic hydrogen for pressures beyond molecular dissociation. We report…

Computational Physics · Physics 2007-05-23 Carlo Pierleoni , David M. Ceperley , Markus Holzmann

We propose quantum algorithms that provide provable speedups for Markov Chain Monte Carlo (MCMC) methods commonly used for sampling from probability distributions of the form $\pi \propto e^{-f}$, where $f$ is a potential function. Our…

Quantum Physics · Physics 2025-04-07 Guneykan Ozgul , Xiantao Li , Mehrdad Mahdavi , Chunhao Wang

The multi-level Monte Carlo method proposed by M. Giles (2008) approximates the expectation of some functionals applied to a stochastic process with optimal order of convergence for the mean-square error. In this paper, a modified…

Probability · Mathematics 2023-01-20 Kristian Debrabant , Andreas Rößler
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