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A review of the Loop Algorithm, its generalizations, and its relation to some other Monte Carlo techniques is given. The loop algorithm is a Quantum Monte Carlo procedure which employs nonlocal changes of worldline configurations,…

Strongly Correlated Electrons · Physics 2014-10-13 H. G. Evertz

We develop a generic strategy and simple numerical models for multi-component metallic glasses for which the swap Monte Carlo algorithm can produce highly stable equilibrium configurations equivalent to experimental systems cooled more than…

Statistical Mechanics · Physics 2020-10-09 Anshul D. S. Parmar , Misaki Ozawa , Ludovic Berthier

The Hybrid Monte Carlo algorithm is adapted to the simulation of a system of classical degrees of freedom coupled to non self-interacting lattices fermions. The diagonalization of the Hamiltonian matrix is avoided by introducing a…

Strongly Correlated Electrons · Physics 2009-10-31 J. L. Alonso , L. A. Fernandez , F. Guinea , V. Laliena , V. Martin-Mayor

Cluster Monte Carlo algorithms are widely regarded as the most effective route to overcoming critical slowing down in lattice spin systems. Whether this acceleration persists in the presence of vacancies and multicritical fluctuations,…

Statistical Mechanics · Physics 2026-05-11 Minjun Jeon , Alexandros Vasilopoulos , Dong-Hee Kim , Víctor Martín-Mayor , Nikolaos G. Fytas

The aim of this work is to prove that it is possible to realise an optical system which produces as output a light intensity that can be expressed in the same mathematical form of the spin glass Hamiltonian. The optical system under study…

Disordered Systems and Neural Networks · Physics 2020-10-27 Erik Hörmann

We present a multithreaded event-chain Monte Carlo algorithm (ECMC) for hard spheres. Threads synchronize at infrequent breakpoints and otherwise scan for local horizon violations. Using a mapping onto absorbing Markov chains, we rigorously…

Computational Physics · Physics 2022-08-31 Botao Li , Synge Todo , A. C. Maggs , Werner Krauth

We present a rigorous efficient event-chain Monte Carlo algorithm for long-range interacting particle systems. Using a cell-veto scheme within the factorized Metropolis algorithm, we compute each single-particle move with a fixed number of…

Statistical Mechanics · Physics 2016-09-28 Sebastian C. Kapfer , Werner Krauth

Monte Carlo simulation using the standard single-spin flip algorithm often fails to sample over the entire configuration space at low temperatures for frustrated spin systems. A typical example is a class of spin-ice type Ising models. In…

Statistical Mechanics · Physics 2011-09-30 Hiroshi Shinaoka , Yusuke Tomita , Yukitoshi Motome

We present a Monte Carlo study of the two-component $\phi^4$ model on the simple cubic lattice in three dimensions. By suitable tuning of the coupling constant $\lambda$ we eliminate leading order corrections to scaling. High statistics…

Statistical Mechanics · Physics 2009-10-31 M. Hasenbusch , T. Toeroek

It is shown that superefficient Monte Carlo computations can be carried out by using chaotic dynamical systems as non-uniform random-number generators. Here superefficiency means that the expectation value of the square of the error…

chao-dyn · Physics 2007-05-23 Ken Umeno

We present, in a unifying way, the main components of three asynchronous event-driven algorithms for simulating physical systems of interacting particles. The first example, hard-particle molecular dynamics, is well-known. We also present a…

Other Computer Science · Computer Science 2008-09-09 Aleksandar Donev

We investigate the applicability of Quasi-Monte Carlo methods to Euclidean lattice systems for quantum mechanics in order to improve the asymptotic error behavior of observables for such theories. In most cases the error of an observable…

High Energy Physics - Lattice · Physics 2013-11-19 K. Jansen , H. Leovey , A. Ammon , A. Griewank , M. Müller-Preussker

We introduce a Metropolis-Hastings Markov chain for Boltzmann distributions of classical spin systems. It relies on approximate tensor network contractions to propose correlated collective updates at each step of the evolution. We present…

A new Monte Carlo algorithm is introduced for the simulation of supercooled liquids and glass formers, and tested in two model glasses. The algorithm is shown to thermalize well below the Mode Coupling temperature and to outperform other…

Statistical Mechanics · Physics 2009-05-21 L. A. Fernandez , V. Martin-Mayor , P. Verrocchio

We present an efficient computational approach to sample the histories of nonlinear stochastic processes. This framework builds upon recent work on casting a $d$-dimensional stochastic dynamical system into a $d+1$-dimensional equilibrium…

Statistical Mechanics · Physics 2009-11-11 Natali Gulbahce , Francis J. Alexander , Gregory Johnson

In this paper I report results for simulations of the three-dimensional gauge glass and the four-dimensional XY spin glass using the parallel tempering Monte Carlo method at low temperatures for moderate sizes. The results are qualitatively…

Disordered Systems and Neural Networks · Physics 2009-11-07 Helmut G. Katzgraber

Within a general cluster framework, we discuss the loop-algorithm, a new type of cluster algorithm that reduces critical slowing down in vertex models and in quantum spin systems. We cover the example of the 6-vertex model in detail. For…

Condensed Matter · Physics 2007-05-23 H. G. Evertz , M. Marcu

In finite-size scaling analyses of Monte Carlo simulations of second-order phase transitions one often needs an extended temperature/energy range around the critical point. By combining the replica-exchange algorithm with cluster updates…

Statistical Mechanics · Physics 2011-08-20 Wolfhard Janke , Elmar Bittner

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

We consider generalizations of the classical inverse problem to Bayesien type estimators, where the result is not one optimal parameter but an optimal probability distribution in parameter space. The practical computational tool to compute…

Optimization and Control · Mathematics 2024-05-03 Michael Herty , Christian Ringhofer
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