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We propose a new quantum Monte Carlo algorithm which realizes a relaxation intrinsic to the original quantum system. The Monte Carlo dynamics satisfies the dynamic scaling relation $\tau\sim \xi^z$ and is independent of the Trotter number.…

Statistical Mechanics · Physics 2009-11-10 Tota Nakamura , Yoshiyuki Ito

In this article we review some of recent results on higher order quasi-Monte Carlo (HoQMC) methods. After a seminal work by Dick (2007, 2008) who originally introduced the concept of HoQMC, there have been significant theoretical progresses…

Numerical Analysis · Mathematics 2020-02-04 Takashi Goda , Kosuke Suzuki

The Fermi gas at unitarity is a particularly interesting system of cold atoms, being dilute and strongly interacting at the same time. It can be studied non-perturbatively with Monte Carlo methods, like the recently developed worm…

Quantum Gases · Physics 2010-11-05 Olga Goulko , Matthew Wingate

From basic considerations of the Lie group that preserves a target probability measure, we derive the Barker, Metropolis, and ensemble Markov chain Monte Carlo (MCMC) algorithms, as well as variants of waste-recycling Metropolis-Hastings…

Statistics Theory · Mathematics 2020-01-29 Steve Huntsman

Long-range interactions are relevant for a large variety of quantum systems in quantum optics and condensed matter physics. In particular, the control of quantum-optical platforms promises to gain deep insights in quantum-critical…

Strongly Correlated Electrons · Physics 2024-03-04 P. Adelhardt , J. A. Koziol , A. Langheld , K. P. Schmidt

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

We present two diagrammatic Monte Carlo methods for quantum systems coupled with harmonic baths, whose dynamics are described by integro-differential equations. The first approach can be considered as a reformulation of Dyson series, and…

Quantum Physics · Physics 2023-12-15 Zhenning Cai , Geshuo Wang , Siyao Yang

In this Ph.D. thesis quantum Monte Carlo methods are applied to investigate the properties of a number of ultracold quantum systems. In Chapter 1 we discuss the analytical approaches and approximations used in the subsequent Chapters; also…

Quantum Gases · Physics 2013-01-10 Oleg N. Osychenko

Reverse Monte Carlo (RMC) is an algorithm that incorporates stochastic modification of the action as part of the process that updates the fields in a Monte Carlo simulation. Such update moves have the potential of lowering or eliminating…

High Energy Physics - Lattice · Physics 2015-06-22 Arjun Singh Gambhir , Kostas Orginos

Although the nonequilibrium relaxation (NER) method has been widely used in Monte Carlo studies on phase transitions in classical spin systems, such studies have been quite limited in quantum phase transitions. The reason is that relaxation…

Statistical Mechanics · Physics 2020-03-11 Yoshihiko Nonomura , Yusuke Tomita

This project investigates the applicability of quasi-Monte Carlo methods to Euclidean lattice systems in order to improve the asymptotic error scaling of observables for such theories. The error of an observable calculated by averaging over…

High Energy Physics - Lattice · Physics 2013-11-20 Andreas Ammon , Tobias Hartung , Karl Jansen , Hernan Leovey , Andreas Griewank , Micheal Müller-Preussker

These lecture notes introduce quantum spin systems and several computational methods for studying their ground-state and finite-temperature properties. Symmetry-breaking and critical phenomena are first discussed in the simpler setting of…

Strongly Correlated Electrons · Physics 2015-03-17 Anders W. Sandvik

We propose a variant of the Simulated Annealing method for optimization in the multivariate analysis of differentiable functions. The method uses global actualizations via the Hybrid Monte Carlo algorithm in their generalized version for…

Statistical Mechanics · Physics 2009-10-30 R. Salazar , R. Toral

We present a Markov-chain Monte Carlo algorithm of "worm"type that correctly simulates the O(n) loop model on any (finite and connected) bipartite cubic graph, for any real n>0, and any edge weight, including the fully-packed limit of…

Statistical Mechanics · Physics 2011-07-28 Qingquan Liu , Youjin Deng , Timothy M. Garoni

We present a universal quantum Monte Carlo algorithm for simulating arbitrary high-spin (spin greater than 1/2) Hamiltonians, based on the recently developed permutation matrix representation (PMR) framework. Our approach extends a…

Computational Physics · Physics 2026-01-27 Arman Babakhani , Lev Barash , Itay Hen

In this paper we study randomized optimal stopping problems and consider corresponding forward and backward Monte Carlo based optimisation algorithms. In particular we prove the convergence of the proposed algorithms and derive the…

Optimization and Control · Mathematics 2020-02-05 Christian Bayer , Denis Belomestny , Paul Hager , Paolo Pigato , John Schoenmakers

The Monte Carlo within Metropolis (MCwM) algorithm, interpreted as a perturbed Metropolis-Hastings (MH) algorithm, provides an approach for approximate sampling when the target distribution is intractable. Assuming the unperturbed Markov…

Computation · Statistics 2019-07-31 Felipe Medina-Aguayo , Daniel Rudolf , Nikolaus Schweizer

This is a book chapter soon to appear (2002) in the "Handbook for Numerical Analysis" volume dedicated to "Computational Chemistry" edited by Claude Le Bris. The series editors are P.G. Ciarlet and J. L. Lions. [North Holland/Elservier].…

Strongly Correlated Electrons · Physics 2007-05-23 Alán Aspuru-Guzik , William A. Lester

During the last 15 years, there has been much progress in defining the nuclear Hamiltonian and applying quantum Monte Carlo methods to the calculation of light nuclei. I describe both aspects of this work and some recent results.

Nuclear Theory · Physics 2014-11-18 Steven C. Pieper

Monte Carlo techniques have been widely employed in statistical physics as well as in quantum theory in the Lagrangian formulation. However, in some areas of application to quantum theories computational progress has been slow. Here we…

Statistical Mechanics · Physics 2011-04-15 Xiang-Qian Luo , C. Huang , J. Jiang , H. Jirari , H. Kroger , K. Moriarty