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Related papers: Optimized Monte Carlo Method for glasses

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We propose a new global optimization method ({\em Simulated Tempering}) for simulating effectively a system with a rough free energy landscape (i.e. many coexisting states) at finite non-zero temperature. This method is related to simulated…

High Energy Physics - Lattice · Physics 2010-12-17 Enzo Marinari , Giorgio Parisi

It is shown, by means of Monte Carlo simulation and Finite Size Scaling analysis, that the Heisenberg spin glass undergoes a finite-temperature phase transition in three dimensions. There is a single critical temperature, at which both a…

Disordered Systems and Neural Networks · Physics 2009-11-11 I. Campos , M. Cotallo-Aban , V. Martin-Mayor , S. Perez-Gaviro , A. Tarancon

We start from recently published numerical data by Hatano and Gubernatis cond-mat/0008115 to discuss properties of convergence to equilibrium of optimized Monte Carlo methods (bivariate multi canonical and parallel tempering). We show that…

Statistical Mechanics · Physics 2009-10-31 E. Marinari , G. Parisi , F. Ricci-Tersenghi , F. Zuliani

In this paper we present a dynamical Monte Carlo algorithm which is applicable to systems satisfying a clustering condition: during the dynamical evolution the system is mostly trapped in deep local minima (as happens in glasses, pinning…

Condensed Matter · Physics 2009-10-22 Werner Krauth , Olivier Pluchery

We discuss a rejectionless global optimization technique which, while being technically similar to the recently introduced method of Extremal Optimization, still relies on a physical analogy with a thermalizing system. Our waiting time…

Statistical Mechanics · Physics 2009-11-07 Jesper Dall , Paolo Sibani

A Monte Carlo method is used in order to simulate the competition between the molecular relaxation and crystallization times in the formation of a glass. The results show that nucleation is avoided during supercooling and produce…

Disordered Systems and Neural Networks · Physics 2009-11-07 Adrian Huerta , Gerardo G. Naumis

Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform…

Statistical Mechanics · Physics 2015-06-19 Jean-Charles Walter , Gerard Barkema

Parallel tempering Monte Carlo has proven to be an efficient method in optimization and sampling applications. Having an optimized temperature set enhances the efficiency of the algorithm through more-frequent replica visits to the…

Computational Physics · Physics 2019-11-11 Ignacio Rozada , Maliheh Aramon , Jonathan Machta , Helmut G. Katzgraber

A new computational method for finite-temperature properties of strongly correlated electrons is proposed by extending the variational Monte Carlo method originally developed for the ground state. The method is based on the path integral in…

Strongly Correlated Electrons · Physics 2016-06-10 Kensaku Takai , Kota Ido , Takahiro Misawa , Youhei Yamaji , Masatoshi Imada

We present results from Monte Carlo simulations of the one-dimensional Ising spin glass with power-law interactions at low temperature, using the parallel tempering Monte Carlo method. For a set of parameters where the long-range part of…

Disordered Systems and Neural Networks · Physics 2007-05-23 H. G. Katzgraber , A. P. Young

Monte Carlo sampling of any system may be analyzed in terms of an associated glass model -- a variant of the Random Energy Model -- with, whenever there is a sign problem, complex fields. This model has three types of phases (liquid, frozen…

Statistical Mechanics · Physics 2011-01-17 Gustavo During , Jorge Kurchan

We propose a new strategy for Monte Carlo (MC) optimization on rugged multidimensional landscapes. The strategy is based on querying the statistical properties of the landscape in order to find the temperature at which the mean first…

Computational Physics · Physics 2015-06-04 Denis Tolkunov , Alexandre V. Morozov

The investigation of freezing transitions of single polymers is computationally demanding, since surface effects dominate the nucleation process. In recent studies we have systematically shown that the freezing properties of flexible,…

Soft Condensed Matter · Physics 2012-07-18 Stefan Schnabel , Michael Bachmann , Wolfhard Janke

We address the interesting temperature range of a glass forming system where the mechanical properties are intermediate between those of a liquid and a solid. We employ an efficient Monte-Carlo method to calculate the elastic moduli, and…

Statistical Mechanics · Physics 2009-11-13 Valery Ilyin , Nataliya Makedonska , Itamar Procaccia , Nurith Schupper

We develop a parallel rejection algorithm to tackle the problem of low acceptance in Monte Carlo methods, and apply it to the simulation of the hopping conduction in Coulomb glasses using Graphics Processing Units, for which we also…

Disordered Systems and Neural Networks · Physics 2014-08-19 Ezequiel E. Ferrero , Alejandro B. Kolton , Matteo Palassini

We develop a novel Monte Carlo algorithm for the vector consisting of the supremum, the time at which the supremum is attained and the position at a given (constant) time of an exponentially tempered L\'evy process. The algorithm, based on…

Mathematical Finance · Quantitative Finance 2023-11-20 Jorge Ignacio González Cázares , Aleksandar Mijatović

Monte Carlo (MC) simulations of lattice models are a widely used way to compute thermodynamic properties of substitutional alloys. A limitation to their more widespread use is the difficulty of driving a MC simulation in order to obtain the…

Statistical Mechanics · Physics 2009-11-07 A. van de Walle , M. Asta

The effect of different move sets on the folding kinetics of the Monte Carlo simulations is analysed based on the conformation-network and the temperature-dependent folding kinetics. A new scheme of implementing Metropolis algorithm is…

Soft Condensed Matter · Physics 2007-05-23 Yu-Pin Luo , Ming-Chang Huang , Yen-Liang Chou , Tsong-Ming Liaw

The study of the properties of glass-forming liquids is difficult for many reasons. Analytic solutions of mean field models are usually available only for systems embedded in a space with an unphysically high number of spatial dimensions;…

Disordered Systems and Neural Networks · Physics 2015-02-26 Manuel Sebastian Mariani , Giorgio Parisi , Corrado Rainone

We investigate to what extend the replica-exchange Monte Carlo method is able to equilibrate a simple liquid in its supercooled state. We find that this method does indeed allow to generate accurately the canonical distribution function…

Soft Condensed Matter · Physics 2009-10-31 Ryoichi Yamamoto , Walter Kob