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Variational and diffusion quantum Monte Carlo (VMC and DMC) methods with Slater-Jastrow-backflow trial wave functions are used to study the spin-polarized three-dimensional uniform electron fluid. We report ground state VMC and DMC energies…

Strongly Correlated Electrons · Physics 2025-11-11 Sam Azadi , N. D. Drummond , Sam. M. Vinko

Ab initio quantum Monte Carlo (QMC) is a stochastic approach for solving the many-body Schr\"odinger equation without resorting to one-body approximations. QMC algorithms are readily parallelizable via ensembles of $N_w$ walkers, making…

Chemical Physics · Physics 2025-08-19 Kousuke Nakano , Sandro Sorella , Michele Casula

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

Wavefunction correction scheme, which was developed as a variance reduction tool for the pure and fixed-node diffusion Monte Carlo (DMC) computations by Anderson and Freihaut, is applied to the DMC computations of fermions without using the…

Computational Physics · Physics 2010-03-29 Nazim Dugan , Inanc Kanik , Sakir Erkoc

The search for two-dimensional (2D) magnetic materials has attracted a great deal of attention because of the experimental synthesis of 2D CrI$_3$, which has a measured Curie temperature of 45 K. Often times, these monolayers have a higher…

Strongly Correlated Electrons · Physics 2023-01-16 Daniel Wines , Kamal Choudhary , Francesca Tavazza

Wave-function Monte Carlo methods are an important tool for simulating quantum systems, but the standard method cannot be used to simulate decoherence in continuously measured systems. Here we present a new Monte Carlo method for such…

Quantum Physics · Physics 2013-05-29 Kurt Jacobs

We report exact expressions for atomic forces in the diffusion Monte Carlo (DMC) method when using nonlocal pseudopotentials. We present approximate schemes for estimating these expressions in both mixed and pure DMC calculations, including…

Materials Science · Physics 2008-08-15 A. Badinski , R. J. Needs

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

We study, through the diffusion Monte Carlo method, a spin one-half fermion fluid, in the three dimensional Euclidean space, at zero temperature. The point particles, immersed in a uniform "neutralizing" background, interact with a…

Strongly Correlated Electrons · Physics 2013-07-11 Riccardo Fantoni

Due to its accuracy and generality, Monte Carlo radiative transfer (MCRT) has emerged as the prevalent method for Ly$\alpha$ radiative transfer in arbitrary geometries. The standard MCRT encounters a significant efficiency barrier in the…

Cosmology and Nongalactic Astrophysics · Physics 2018-06-13 Aaron Smith , Benny T. -H. Tsang , Volker Bromm , Milos Milosavljevic

The Kinetic Monte Carlo (KMC) method has become an important tool for examination of phenomena like surface diffusion and thin film growth because of its ability to carry out simulations for time scales that are relevant to experiments. But…

Materials Science · Physics 2007-05-23 Talat S. Rahman , Abdelkader Kara , Altaf Karim , Oleg Trushin

We study several aspects of the recently introduced fixed-phase spin-orbit diffusion Monte Carlo (FPSODMC) method, in particular, its relation to the fixed-node method and its potential use as a general approach for electronic structure…

Computational Physics · Physics 2017-10-18 Cody A. Melton , Lubos Mitas

Atomic force calculations within the variational and diffusion quantum Monte Carlo (VMC and DMC) methods are described. The advantages of calculating DMC forces with the "pure" rather than the "mixed" probability distribution are discussed.…

Materials Science · Physics 2010-02-15 A. Badinski , P. D. Haynes , J. R. Trail , R. J. Needs

This work describes a new 1D hybrid approach for modeling atmospheric pressure discharges featuring complex chemistry. In this approach electrons are described fully kinetically using Particle-In-Cell/Monte-Carlo (PIC/MCC) scheme, whereas…

Plasma Physics · Physics 2016-01-20 Denis Eremin , Torben Hemke , Thomas Mussenbrock

We use the diffusion quantum Monte Carlo (DMC) method to calculate the ground state phase diagram of solid molecular hydrogen and examine the stability of the most important insulating phases relative to metallic crystalline molecular…

Materials Science · Physics 2015-06-16 S. Azadi , W. M. C. Foulkes , T. D. Kuehne

We review an approach where the energy functional of Density-Functional Theory (DFT) can be determined without empiricism via a Quantum Monte Carlo (QMC) procedure. The idea consists of a nested iterative loop where the configurational…

Strongly Correlated Electrons · Physics 2017-11-22 Luigi Delle Site

We report diffusion Monte Carlo (DMC) calculations on MgO in the rock-salt and CsCl structures. The calculations are based on Hartree-Fock pseudopotentials, with the single-particle orbitals entering the correlated wave function being…

Strongly Correlated Electrons · Physics 2016-08-16 D. Alfè , M. Alfredsson , J. Brodholt , M. J. Gillan M. D. Towler , R. J. Needs

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

We propose a Monte Carlo sampler from the reverse diffusion process. Unlike the practice of diffusion models, where the intermediary updates -- the score functions -- are learned with a neural network, we transform the score matching…

Machine Learning · Statistics 2024-03-14 Xunpeng Huang , Hanze Dong , Yifan Hao , Yi-An Ma , Tong Zhang

We develop a variational Monte Carlo (VMC) method for electron-phonon coupled systems. The VMC method has been extensively used for investigating strongly correlated electrons over the last decades. However, its applications to…

Strongly Correlated Electrons · Physics 2014-06-02 Takahiro Ohgoe , Masatoshi Imada