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This paper describes a new Monte Carlo method based on a novel stochastic potential switching algorithm. This algorithm enables the equilibrium properties of a system with potential $V$ to be computed using a Monte Carlo simulation for a…

Statistical Mechanics · Physics 2007-05-23 C. H. Mak

Quantum Monte Carlo (QMC) methods can very accurately compute ground state properties of quantum systems. We applied these methods to a system of boson hard spheres to get exact, infinite system size results for the ground state at several…

Computational Physics · Physics 2016-09-08 Mark Dewing

We demonstrate the use of a variational method to determine a quantitative lower bound on the rate of convergence of Markov Chain Monte Carlo (MCMC) algorithms as a function of the target density and proposal density. The bound relies on…

Data Analysis, Statistics and Probability · Physics 2013-05-29 Fergal P. Casey , Joshua J. Waterfall , Ryan N. Gutenkunst , Christopher R. Myers , James P. Sethna

We introduce the energy-stepping Monte Carlo (ESMC) method, a Markov chain Monte Carlo (MCMC) algorithm based on the conventional dynamical interpretation of the proposal stage but employing an energy-stepping integrator. The…

Mathematical Physics · Physics 2023-12-13 Ignacio Romero , Michael Ortiz

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

The possibility to simulate the properties of many-body open quantum systems with a large number of degrees of freedom is the premise to the solution of several outstanding problems in quantum science and quantum information. The challenge…

Quantum Physics · Physics 2019-07-03 Alexandra Nagy , Vincenzo Savona

Monte Carlo methods are widely used importance sampling techniques for studying complex physical systems. Integrating these methods with deep learning has significantly improved efficiency and accuracy in high-dimensional problems and…

Disordered Systems and Neural Networks · Physics 2024-12-24 Yixiong Ren , Jianhui Zhou

Modern quantum Monte Carlo (QMC) methods often capture electron correlation through both explicitly correlating Jastrow factors and small to mid-sized configuration interaction (CI) expansions. Here, we study the additional optimization…

Chemical Physics · Physics 2023-02-08 Scott M. Garner , Eric Neuscamman

The microscopic description of collectivity in heavy nuclei in the framework of the configuration-interaction shell model has been a major challenge. The size of the model space required for the description of heavy nuclei prohibits the use…

Nuclear Theory · Physics 2015-06-18 C. Özen , Y. Alhassid , H. Nakada

Quantum Monte Carlo (QMC) methods such as variational Monte Carlo and fixed node diffusion Monte Carlo depend heavily on the quality of the trial wave function. Although Slater-Jastrow wave functions are the most commonly used variational…

Materials Science · Physics 2015-05-28 Bryan K. Clark , Miguel A. Morales , Jeremy McMinis , Jeongnim Kim , Gustavo E. Scuseria

Fixed-node diffusion Monte Carlo (DMC) is a stochastic algorithm for finding the lowest energy many-fermion wave function with the same nodal surface as a chosen trial function. It has proved itself among the most accurate methods available…

Condensed Matter · Physics 2009-10-31 W. M. C. Foulkes , Randolph Q. Hood , R. J. Needs

Many recent advances in large scale probabilistic inference rely on variational methods. The success of variational approaches depends on (i) formulating a flexible parametric family of distributions, and (ii) optimizing the parameters to…

Machine Learning · Statistics 2018-02-22 Christian A. Naesseth , Scott W. Linderman , Rajesh Ranganath , David M. Blei

Quantum Monte Carlo methods are accurate and promising many body techniques for electronic structure calculations which, in the last years, are encountering a growing interest thanks to their favorable scaling with the system size and their…

Chemical Physics · Physics 2014-02-17 Andrea Zen , Ye Luo , Sandro Sorella , Leonardo Guidoni

We describe a technique for constraining macroscopic fluctuations in thermodynamic variables well-suited for Monte Carlo (MC) simulations of multiphase equilibria. In particular for multicomponent systems this amounts to a statistical…

Materials Science · Physics 2013-11-20 Babak Sadigh , Paul Erhart

The shell-model Monte Carlo (SMMC) technique transforms the traditional nuclear shell-model problem into a path-integral over auxiliary fields. We describe below the method and its applications to four physics issues: calculations of sdpf-…

Nuclear Theory · Physics 2009-10-31 D. J. Dean , J. A. White

We discuss electronic properties and their evolution for the linear chain of $H_2$ molecules in the presence of a uniform external force $f$ acting along the chain. The system is described by an extended Hubbard model within a fully…

Materials Science · Physics 2018-08-15 Andrzej Biborski , Andrzej P. Kądzielawa , Józef Spałek

We propose a variational calculation scheme utilizing the superposition of the angular-momentum, parity, number projected quasiparticle vacua, that is especially suitable for applying to medium-heavy nuclei in shell-model calculations. We…

Nuclear Theory · Physics 2021-01-27 Noritaka Shimizu , Yusuke Tsunoda , Yutaka Utsuno , Takaharu Otsuka

An extrapolation method in shell model calculations with deformed basis is presented, which uses a scaling property of energy and energy variance for a series of systematically approximated wave functions to the true one. Such approximated…

Nuclear Theory · Physics 2009-11-10 Takahiro Mizusaki

Quantum Monte Carlo methods have proven to predict atomic and bulk properties of light and non-light elements with high accuracy. Here we report on the first variational quantum Monte Carlo (VMC) calculations for solid surfaces. Taking the…

Materials Science · Physics 2009-10-31 R. Bahnsen , H. Eckstein , W. Schattke , N. Fitzer , R. Redmer

An algorithm is proposed to optimize quantum Monte Carlo (QMC) wave functions based on New ton's method and analytical computation of the first and second derivatives of the variati onal energy. This direct application of the variational…

Chemical Physics · Physics 2016-09-08 Xi Lin , Hongkai Zhang , Andrew M. Rappe