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In high dimensions, reflective Hamiltonian Monte Carlo with inexact reflections exhibits slow mixing when the particle ensemble is initialised from a Dirac delta distribution and the uniform distribution is targeted. By quantifying the…

Machine Learning · Statistics 2026-03-20 Namu Kroupa , Gábor Csányi , Will Handley

To understand the performance of popular density-functional theory (DFT) exchange-correlation (xc) functionals in simulations of liquid water, water monomers and dimers were extracted from a PBE simulation of liquid water and examined with…

Materials Science · Physics 2009-10-21 Biswajit Santra , Angelos Michaelides , Matthias Scheffler

Quantum Monte Carlo (QMC) methods have received considerable attention over the last decades due to their great promise for providing a direct solution to the many-body Schrodinger equation in electronic systems. Thanks to their low scaling…

Chemical Physics · Physics 2013-03-28 M. A. Morales , J. McMinis , B. K. Clark , J. Kim , G. Scuseria

The Diffusion Monte Carlo method with constant number of walkers, also called Stochastic Reconfiguration as well as Sequential Monte Carlo, is a widely used Monte Carlo methodology for computing the ground-state energy and wave function of…

Statistics Theory · Mathematics 2024-12-09 Michel Caffarel , Pierre del Moral , Luc de Montella

A diffusion Monte Carlo algorithm is introduced that can determine the correct nodal structure of the wave function of a few-fermion system and its ground-state energy without an uncontrolled bias. This is achieved by confining signed…

Computational Physics · Physics 2020-02-05 Alexander A. Kunitsa , So Hirata

Characterizing the properties and orientations of sub-voxel fiber populations, although essential to study white-matter architecture, microstructure and connectivity, remains one of the main challenges faced by the MRI microstructure…

Monte Carlo simulation is one of the most important tools in the study of diffusion processes. For constant diffusion coefficients, an appropriate Gaussian distribution of particle's steplengths can generate exact results, when compared…

Computational Physics · Physics 2015-06-12 V. Ruiz Barlett , M. Hoyuelos , H. O. Mártin

The quantum Monte Carlo (QMC) is one of the most promising many-body electronic structure approaches. It employs stochastic techniques for solving the stationary Schr\" odinger equation and for evaluation of expectation values. The key…

Other Condensed Matter · Physics 2007-12-20 Michal Bajdich

The accuracy and efficiency of ab-initio quantum Monte Carlo (QMC) algorithms benefits greatly from compact variational trial wave functions that accurately reproduce ground state properties of a system. We investigate the possibility of…

Materials Science · Physics 2019-01-30 Shivesh Pathak , Lucas K. Wagner

We propose a streamlined combination scheme of the transcorrelation (TC) and coupled cluster (CC) theory, which not only increases the convergence rate with respect to the basis set, but also extends the applicability of the lowest order CC…

Strongly Correlated Electrons · Physics 2021-07-28 Ke Liao , Thomas Schraivogel , Hongjun Luo , Daniel Kats , Ali Alavi

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

Several aspects of the recently proposed DMC-CIPSI approach consisting in using selected Configuration Interaction (SCI) approaches such as CIPSI (Configuration Interaction using a Perturbative Selection done Iteratively) to build accurate…

Chemical Physics · Physics 2017-04-20 Michel Caffarel , Thomas Applencourt , Emmanuel Giner , Anthony Scemama

Diffusion Monte Carlo (DMC) is one of the most accurate techniques available for calculating the electronic properties of molecules and materials, yet it often remains a challenge to economically compute forces using this technique. As a…

Chemical Physics · Physics 2022-11-15 Cancan Huang , Brenda M. Rubenstein

Using dynamic cluster quantum Monte Carlo simulations, we study the superconducting behavior of a 1/8 doped two-dimensional Hubbard model with imposed uni-directional stripe-like charge density wave modulation. We find a significant…

Superconductivity · Physics 2015-05-14 T. A. Maier , G. Alvarez , M. Summers , T. C. Schulthess

Quantum Monte Carlo (QMC) is a stochastic method which has been particularly successful for ground-state electronic structure calculations but mostly unexplored for the computation of excited-state energies. Here, we show that, within a…

Chemical Physics · Physics 2018-08-09 Anthony Scemama , Anouar Benali , Denis Jacquemin , Michel Caffarel , Pierre-François Loos

Unitary coupled cluster (UCC), originally developed as a variational alternative to the popular traditional coupled cluster method, has seen a resurgence as a functional form for use on quantum computers. However, the number of excitors…

Chemical Physics · Physics 2021-01-07 Maria-Andreea Filip , Alex J. W. Thom

Identifying the atomic structure and properties of solid hydrogen under high pressures is a long-standing problem of high-pressure physics with far-reaching significance in planetary and materials science. Determining the…

Materials Science · Physics 2020-04-16 Ke Liao , Xin-Zheng Li , Ali Alavi , Andreas Grüneis

The cluster mean-field approximations are performed, up to 13 cluster sizes, to study the critical behavior of the driven pair contact process with diffusion (DPCPD) and its precedent, the PCPD in one dimension. Critical points are…

Statistical Mechanics · Physics 2007-05-23 Su-Chan Park , Hyunggyu Park

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

Quantum Monte Carlo (QMC) methods are powerful approaches for solving electronic structure problems. Although they often provide high-accuracy solutions, the precision of most QMC methods is ultimately limited by a trial wave function that…

Quantum Physics · Physics 2025-03-13 Nick S. Blunt , Laura Caune , Javiera Quiroz-Fernandez
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