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The dynamics of a polydisperse model glassformer are investigated by augmenting molecular dynamics (MD) simulation with swap Monte Carlo (SMC). Three variants of the SMC algorithm are analyzed with regard to convergence and performance. We…

Soft Condensed Matter · Physics 2023-05-09 Niklas Küchler , Jürgen Horbach

Although the Metropolis algorithm is simple to implement, it often has difficulties exploring multimodal distributions. We propose the repelling-attracting Metropolis (RAM) algorithm that maintains the simple-to-implement nature of the…

Methodology · Statistics 2018-08-28 Hyungsuk Tak , Xiao-Li Meng , David A. van Dyk

The exchange algorithm is one of the most popular extensions of the Metropolis--Hastings algorithm to sample from doubly-intractable distributions. However, the theoretical exploration of the exchange algorithm is very limited. For example,…

Computation · Statistics 2021-08-20 Guanyang Wang

We use theory and simulations to investigate the existence of amorphous glassy states in ultrasoft colloids. We combine the hyper-netted chain approximation with mode-coupling theory to study the dynamic phase diagram of soft repulsive…

Soft Condensed Matter · Physics 2010-12-16 Ludovic Berthier , Angel J. Moreno , Grzegorz Szamel

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

Spin Glasses (SG) are paradigmatic models for physical, computer science, biological and social systems. The problem of studying the dynamics for SG models is NP hard, i.e., no algorithm solves it in polynomial time. Here we implement the…

Disordered Systems and Neural Networks · Physics 2021-07-14 M. Leonetti , E. Hörmann , L. Leuzzi , G. Parisi , G. Ruocco

Dilute dipolar Ising magnets remain a notoriously hard problem to tackle both analytically and numerically because of long-ranged interactions between spins as well as rare region effects. We study a new type of anisotropic dilute dipolar…

Disordered Systems and Neural Networks · Physics 2019-08-28 Tushar Kanti Bose , Roderich Moessner , Arnab Sen

In simulations of some infinite range spin glass systems with finite connectivity, it is found that for any resonable computational time, the saturatedenergy per spin that is achieved by a cluster algorithm is lowered in comparison to that…

Condensed Matter · Physics 2016-08-31 N. Persky , I. Kanter , S. Solomon

It was recently discovered that SWAP, a Monte Carlo algorithm that involves the exchange of pairs of particles of differing diameters, can dramatically accelerate the equilibration of simulated supercooled liquids in regimes where the…

Statistical Mechanics · Physics 2019-04-02 Ludovic Berthier , Giulio Biroli , Jean-Philippe Bouchaud , Gilles Tarjus

Spin glass systems as lattices of disordered magnets with random interactions have important implications within the theory of magnetization and applications to a wide-range of hard combinatorial optimization problems. Nevertheless, despite…

Disordered Systems and Neural Networks · Physics 2025-10-28 Fredrik Hasselgren , Max O. Al-Hasso , Amy Searle , Joseph Tindall , Marko von der Leyen

The Reversible Jump algorithm is one of the most widely used Markov chain Monte Carlo algorithms for Bayesian estimation and model selection. A generalized multiple-try version of this algorithm is proposed. The algorithm is based on…

Methodology · Statistics 2013-10-14 S. Pandolfi , F. Bartolucci , N. Friel

In this paper we propose a novel method to study critical systems numerically by a combined collective-mode algorithm and Renormalization Group on the lattice. This method is an improved version of MCRG in the sense that it has all the…

Statistical Mechanics · Physics 2009-12-03 G. Palma , D. Zambrano

The accuracy of molecular simulations is fundamentally limited by the interatomic potentials that govern atomic interactions. Traditional potential development, which relies heavily on ab initio calculations, frequently struggles to…

Disordered Systems and Neural Networks · Physics 2025-10-16 Ruoxia Chen , Kai Yang , Morten M. Smedskjaer , N. M. Anoop Krishnan , Jaime Marian , Fabian Rosner

Particle swaps can drastically accelerate dynamics in glass. The mechanism is expected to be vital for a fundamental understanding of glassy dynamics. To extract defining features, we propose a partial swappability with a fraction {\phi_s}…

Disordered Systems and Neural Networks · Physics 2022-11-01 Gautham Gopinath , Chun-Shing Lee , Xin-Yuan Gao , Xiao-Dong An , Chor-Hoi Chan , Cho-Tung Yip , Hai-Yao Deng , Chi-Hang Lam

Traditional MCMC algorithms are computationally intensive and do not scale well to large data. In particular, the Metropolis-Hastings (MH) algorithm requires passing over the entire dataset to evaluate the likelihood ratio in each…

Machine Learning · Statistics 2019-08-29 Tung-Yu Wu , Y. X. Rachel Wang , Wing H. Wong

We examine the behaviour of the pseudo-marginal random walk Metropolis algorithm, where evaluations of the target density for the accept/reject probability are estimated rather than computed precisely. Under relatively general conditions on…

Computation · Statistics 2014-12-31 Chris Sherlock , Alexandre H. Thiery , Gareth O. Roberts , Jeffrey S. Rosenthal

We present computer simulations of concentrated solutions of unknotted nonconcatenated semiflexible ring polymers. Unlike in their flexible counterparts, shrinking involves a strong energetic penalty, favoring interpenetration and…

One emerging approach for the fabrication of complex architectures on the nanoscale is to utilize particles customized to intrinsically self-assemble into a desired structure. Inverse methods of statistical mechanics have proven…

Materials Science · Physics 2017-09-08 R. B. Jadrich , B. A. Lindquist , T. M. Truskett

We propose here a method to generate random networked amorphous structure using only readily available short-range properties like bond lengths, bond angles and connectivity of the constituents. This method is a variant of Monte-Carlo (MC)…

Materials Science · Physics 2022-05-26 Shakti Singh , Sharat Chandra

Equilibrium systems evolve according to Detailed Balance (DB). This principe guided development of the Monte-Carlo sampling techniques, of which Metropolis-Hastings (MH) algorithm is the famous representative. It is also known that DB is…

Statistical Mechanics · Physics 2015-07-15 Konstantin S. Turitsyn , Michael Chertkov , Marija Vucelja