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Monte Carlo simulations are widely employed to measure the physical properties of glass-forming liquids in thermal equilibrium. Combined with local Monte Carlo moves, the Metropolis algorithm can also be used to simulate the relaxation…

Statistical Mechanics · Physics 2024-09-23 Ludovic Berthier , Federico Ghimenti Frédéric van Wijland

We report an essential improvement of the plain Fourier Monte Carlo algorithm that promises to be a powerful tool for investigating critical behavior in a large class of lattice models, in particular those containing microscopic or…

Statistical Mechanics · Physics 2015-02-17 Andreas Tröster

In dynamic Monte Carlo simulations, using for example the Metropolis dynamic, it is often required to simulate for long times and to simulate large systems. We present an overview of advanced algorithms to simulate for larger times and to…

Statistical Mechanics · Physics 2007-05-23 M. A. Novotny , Alice K. Kolakowska , G. Korniss

To minimise systematic errors in Monte Carlo simulations of charged particles, long range electrostatic interactions have to be calculated accurately and efficiently. Standard approaches, such as Ewald summation or the naive application of…

Computational Physics · Physics 2021-02-24 William Robert Saunders , James Grant , Eike Hermann Müller

The Metropolis implementation of the Monte Carlo algorithm has been developed to study the equilibrium thermodynamics of many-body systems. Choosing small trial moves, the trajectories obtained applying this algorithm agree with those…

Other Quantitative Biology · Quantitative Biology 2009-11-13 G. Tiana , L. Sutto , R. A. Broglia

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

We present several implementations of the Metropolis method, an adaptive Monte Carlo algorithm, which allow for the calculation of multi-dimensional integrals over arbitrary on-shell four-momentum phase space. The Metropolis technique…

High Energy Physics - Phenomenology · Physics 2009-10-31 Hamid Kharraziha , Stefano Moretti

Solvent-free coarse grained models represent one of the most promising approaches for molecular simulations of mesoscopically large membranes. In these models, the size of the simulated membrane is limited by the slow relaxation time of…

Soft Condensed Matter · Physics 2009-11-13 Oded Farago

We investigate local update algorithms for the fully frustrated XY model on a square lattice. In addition to the standard updating procedures like the Metropolis or heat bath algorithm we include overrelaxation sweeps, implemented through…

Disordered Systems and Neural Networks · Physics 2007-05-23 S. Grosse Pawig , K. Pinn

Advanced algorithms are necessary to obtain faster-than-real-time dynamic simulations in a number of different physical problems that are characterized by widely disparate time scales. Recent advanced dynamic Monte Carlo algorithms that…

Materials Science · Physics 2016-11-23 M. A. Novotny

We describe collective-move Monte Carlo algorithms designed to approximate the overdamped dynamics of self-assembling nanoscale components equipped with strong, short-ranged and anisotropic interactions. Conventional Monte Carlo simulations…

Statistical Mechanics · Physics 2012-04-16 Stephen Whitelam

We present an improved Metropolis algorithm for arbitrary hard core systems in any dimensions. In the new updating scheme the conventional Metropolis step of a single particle is replaced by a collective step of a chain of particles. For…

Statistical Mechanics · Physics 2007-05-23 Andreas Jaster

Adiabatic quantum computers, such as the quantum annealers commercialized by D-Wave Systems Inc., are routinely used to tackle combinatorial optimization problems. In this article, we show how to exploit them to accelerate equilibrium…

Disordered Systems and Neural Networks · Physics 2023-07-12 Giuseppe Scriva , Emanuele Costa , Benjamin McNaughton , Sebastiano Pilati

We investigate the applicability of the synchronous relaxation (SR) algorithm to parallel kinetic Monte Carlo simulations of simple models of thin-film growth. A variety of techniques for optimizing the parallel efficiency are also…

Materials Science · Physics 2007-05-23 Yunsic Shim , Jacques G. Amar

We show how to apply the absorbing Markov chain Monte Carlo algorithm of Novotny to simulate kinetically constrained models of glasses. We consider in detail one-spin facilitated models, such as the East model and its generalizations to…

Statistical Mechanics · Physics 2009-11-11 Douglas J. Ashton , Lester O. Hedges , Juan P. Garrahan

Computational determination of the equilibrium state of heterogeneous phospholipid mem-branes is a significant challenge. We wish to explore the rich phase diagram of these multi-component systems. However, the diffusion and mixing times in…

Biological Physics · Physics 2020-10-28 Yevhen K. Cherniavskyi , Arman Fathizadeh , Ron Elber , D. Peter Tieleman

The self-organized Monte Carlo simulations of 2D Ising ferromagnet on the square lattice are performed. The essence of devised simulation method is the artificial dynamics consisting of the single-spin-flip algorithm of Metropolis…

Computational Physics · Physics 2009-11-10 Denis Horvath , Martin Gmitra

Competing phases or interactions in complex many-particle systems can result in free energy barriers that strongly suppress thermal equilibration. Here we discuss how extended ensemble Monte Carlo simulations can be used to study the…

Statistical Mechanics · Physics 2007-05-23 S. Trebst , D. A. Huse , E. Gull , H. G. Katzgraber , U. H. E. Hansmann , M. Troyer

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

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
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