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Monte Carlo sampling is a powerful toolbox of algorithmic techniques widely used for a number of applications wherein some noisy quantity, or summary statistic thereof, is sought to be estimated. In this paper, we survey the literature for…

We describe a generalized scheme for the probability-changing cluster (PCC) algorithm, based on the study of the finite-size scaling property of the correlation ratio, the ratio of the correlation functions with different distances. We…

Statistical Mechanics · Physics 2009-11-07 Yutaka Okabe , Yusuke Tomita , Chiaki Yamaguchi

We conduct experimental simulations of many body quantum systems using a \emph{hybrid} classical-quantum algorithm. In our setup, the wave function of the transverse field quantum Ising model is represented by a restricted Boltzmann…

Quantum Physics · Physics 2018-12-05 Bartłomiej Gardas , Marek M. Rams , Jacek Dziarmaga

We investigate the accuracy of a number of wavefunction based methods at the heart of quantum chemistry for metallic systems. Using Hartree-Fock as a reference, perturbative (M{\o}ller-Plesset, MP) and coupled cluster (CC) theories are used…

Chemical Physics · Physics 2013-10-24 James J. Shepherd , Andreas Grüneis

We review the basics of the coupled-cluster expansion formalism for numerical solutions of the many-body problem, and we outline the principles of an approach directed towards an adequate inclusion of continuum effects in the associated…

Nuclear Theory · Physics 2009-11-10 Bogdan Mihaila

We review the background of the cluster algorithms in Monte Carlo simulation of statistical physics problems. One of the first such successful algorithm was developed by Swendsen and Wang eight years ago. In contrast to the local…

Condensed Matter · Physics 2007-05-23 Jian-Sheng Wang

The coupled-cluster method is applied to the spin-1/2 antiferromagnetic XXZ model on a square lattice by employing an approximation which contains two-body long-range correlations and high-order four-body local correlations. Improvement is…

Strongly Correlated Electrons · Physics 2015-05-28 Mohammad Merdan , Y. Xian

We apply diffusion quantum Monte Carlo (DMC) to a broad set of solids, benchmarking the method by comparing bulk structural properties (equilibrium volume and bulk modulus) to experiment and DFT based theories. The test set includes…

Materials Science · Physics 2015-06-17 Luke Shulenburger , Thomas R. Mattsson

Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying…

This paper introduces quantum computing methods for Monte Carlo simulations in power systems which are expected to be exponentially faster than their classical computing counterparts. Monte Carlo simulations is a fundamental method, widely…

Quantum Physics · Physics 2023-10-02 Emilie Jong , Brynjar Sævarsson , Hjörtur Jóhannsson , Spyros Chatzivasileiadis

In this work, we test a recently developed method to enhance classical auxiliary-field quantum Monte Carlo (AFQMC) calculations with quantum computers against examples from chemistry and material science, representatives of classes of…

We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a novel…

Statistical Mechanics · Physics 2017-12-27 Tameem Albash , Gene Wagenbreth , Itay Hen

The optimization of neural wave functions in variational Monte Carlo crucially relies on a robust convergence criterion. While the energy variance is theoretically a definitive measure, its practical application as a primary convergence…

Quantum Physics · Physics 2025-11-03 Huan-Chen Shi , Er-Liang Cui , Dan Zhou

Simulating long-range interacting systems is a challenging task due to its computational complexity that the computational effort for each local update is of order $\cal{O}$$(N)$, where $N$ is the size of system. Recently, a technique,…

Computational Physics · Physics 2025-11-14 Zhijie Fan , Chao Zhang , Youjin Deng

A variational Monte Carlo method is used to generate sets of orthogonal trial functions, Psi_T(J^pi,T), for given quantum numbers in various light p-shell nuclei. These Psi_T are then used as input to Green's function Monte Carlo…

Nuclear Theory · Physics 2008-11-26 Steven C. Pieper , R. B. Wiringa , J. Carlson

A ``forward walking'' Quantum Monte Carlo (QMC) algorithm has been developed to calculate correlation functions for the Hamiltonian lattice formulation of U(1) Yang-Mills theory in (2+1) dimensions. It is shown that Wilson loops can be…

High Energy Physics - Lattice · Physics 2009-10-31 Chris J. Hamer , Robert J. Bursill , Maria Samaras

A strongly coupled quark-gluon plasma (QGP) of heavy constituent quasiparticles is studied by a path-integral Monte-Carlo method, which improves the corresponding classical simulations by extending them to the quantum regime. It is shown…

Nuclear Theory · Physics 2011-09-20 V. S. Filinov , Yu. B. Ivanov , M. Bonitz , P. R. Levashov , V. E. Fortov

Quantum Monte Carlo (QMC) is a family of powerful tools for addressing quantum many-body problems. However, its applications are often plagued by the fermionic sign problem. A promising strategy is to simulate an interaction without sign…

Nuclear Theory · Physics 2025-05-01 Jun Liu , Teng Wang , Bing-Nan Lu

It is shown how to adapt the non-perturbative coupled cluster method of many-body theory so that it may be successfully applied to Hamiltonian lattice $SU(N)$ gauge theories. The procedure involves first writing the wavefunctions for the…

High Energy Physics - Lattice · Physics 2009-10-22 C. H. Llewellyn Smith , N. J. Watson

We introduce a multiscale Monte Carlo algorithm to simulate dense simple fluids. The probability of an update follows a power law distribution in its length scale. The collective motion of clusters of particles requires generalization of…

Statistical Mechanics · Physics 2009-11-11 A. C. Maggs