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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 study a sequential Monte Carlo algorithm to sample from the Gibbs measure with a non-convex energy function at a low temperature. We use the practical and popular geometric annealing schedule, and use a Langevin diffusion at each…

Statistics Theory · Mathematics 2026-01-13 Ruiyu Han , Gautam Iyer , Dejan Slepčev

We study lithium systems over a range of number of atoms, e.g., atomic anion, dimer, metallic cluster, and body-centered cubic crystal by the diffusion Monte Carlo method. The calculations include both core and valence electrons in order to…

Computational Physics · Physics 2015-07-29 Kevin Rasch , Lubos Mitas

In this work, we investigate the fidelity of orbital optimization in variational Monte Carlo to improve diffusion Monte Carlo results on correlated magnetic systems, using CrSBr as a model system. We compare the performance of different…

Strongly Correlated Electrons · Physics 2026-04-27 Cody A. Melton , Jaron T. Krogel

We describe a number of strategies for minimizing and calculating accurately the statistical uncertainty in quantum Monte Carlo calculations. We investigate the impact of the sampling algorithm on the efficiency of the variational Monte…

Computational Physics · Physics 2012-02-14 R. M. Lee , G. J. Conduit , N. Nemec , P. Lopez Rios , N. D. Drummond

We propose a modification, based on the RESTART (repetitive simulation trials after reaching thresholds) and DPR (dynamics probability redistribution) rare event simulation algorithms, of the standard diffusion Monte Carlo (DMC) algorithm.…

Probability · Mathematics 2014-04-10 Martin Hairer , Jonathan Weare

We discuss the improvement in the accuracy of a Monte Carlo integration that can be obtained by optimization of the `a-priori weights' of the various channels. These channels may be either the strata in a stratified-sampling approach, or…

High Energy Physics - Phenomenology · Physics 2009-10-28 R. Kleiss , R. Pittau

Quantum Monte Carlo is one of the most promising approaches for dealing with large-scale quantum many-body systems. It has played an extremely important role in understanding strongly correlated physics. However, two fundamental problems,…

Strongly Correlated Electrons · Physics 2026-03-03 Zhiyan Wang , Zenan Liu , Bin-Bin Mao , Zhe Wang , Zheng Yan

A kinetic Monte Carlo method was used to simulate the diffusion of reptating polymer chains across the interface. A time-resolved fluorescence technique conjunction with direct energy transfer method was used to measure the extend of…

Soft Condensed Matter · Physics 2007-05-23 Erkan Tuzel , K. Batuhan Kisacikoglu , Onder Pekcan

A quantum Monte Carlo study of the atomization energies for the G2 set of molecules is presented. Basis size dependence of diffusion Monte Carlo atomization energies is studied with a single determinant Slater-Jastrow trial wavefunction…

Chemical Physics · Physics 2015-06-04 F. R. Petruzielo , Julien Toulouse , C. J. Umrigar

Direct sampling of multi-dimensional systems with quantum Monte Carlo methods allows exact account of many-body effects or particle correlations. The most straightforward approach to solve the Schr\"odinger equation, Diffusion Monte Carlo,…

Quantum Physics · Physics 2017-09-07 Ilkka Ruokosenmäki , Tapio T. Rantala

A Monte Carlo model was used to study the scattering error of an absorption meter with a divergent light beam and a limited acceptance angle of the receiver. Reflections at both ends of the tube were taken into account. Calculations of the…

Atmospheric and Oceanic Physics · Physics 2009-11-06 Jacek Piskozub , Piotr J. Flatau , J. V. R. Zaneveld

In order to find the equilibrium geometries of molecules and solids and to perform ab initio molecular dynamics, it is necessary to calculate the forces on the nuclei. We present a correlated sampling method to efficiently calculate…

Condensed Matter · Physics 2009-10-31 Claudia Filippi , C. J. Umrigar

The recently introduced backward Monte-Carlo method [Johan Carlsson, arXiv:math.NA/0010118] is validated, benchmarked, and compared to the conventional, forward Monte-Carlo method by analyzing the error in the Monte-Carlo solutions to a…

Numerical Analysis · Mathematics 2025-10-20 Johan Carlsson

We combine histogram reweighting techniques with the two-lattice matching Monte Carlo renormalization group method to conduct computationally efficient calculations of critical exponents on systems with moderately small lattice sizes. The…

High Energy Physics - Lattice · Physics 2024-01-23 Dimitrios Bachtis

Population control is an essential component of any projector Monte Carlo algorithm. This control mechanism usually introduces a bias in the sampled quantities that is inversely proportional to the population size. In this paper, we…

Computational Physics · Physics 2021-04-28 Khaldoon Ghanem , Niklas Liebermann , Ali Alavi

Quantum mechanics for many-body systems may be reduced to the evaluation of integrals in 3N dimensions using Monte-Carlo, providing the Quantum Monte Carlo ab initio methods. Here we limit ourselves to expectation values for trial…

Computational Physics · Physics 2010-11-22 John Robert Trail , Ryo Maezono

Path integrals describing quantum many-body systems can be calculated with Monte Carlo sampling techniques, but average quantities are often subject to signal-to-noise ratios that degrade exponentially with time. A phase-reweighting…

High Energy Physics - Lattice · Physics 2017-07-12 Michael L. Wagman , Martin J. Savage

This paper develops and analyzes an efficient numerical method for solving elliptic partial differential equations, where the diffusion coefficients are random perturbations of deterministic diffusion coefficients. The method is based upon…

Numerical Analysis · Mathematics 2016-03-30 X. Feng , J. Lin. , C. Lorton

We review the use of continuum quantum Monte Carlo (QMC) methods for the calculation of energy gaps from first principles, and present a broad set of excited-state calculations carried out with the variational and fixed-node diffusion QMC…

Materials Science · Physics 2018-08-22 Ryan J. Hunt , Marcin Szyniszewski , Genki I. Prayogo , Ryo Maezono , Neil D. Drummond