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Related papers: Simulated Tempering and Swapping on Mean-Field Mod…

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Swendsen-Wang dynamics for the Potts model was proposed in the late 1980's as an alternative to single-site heat-bath dynamics, in which global updates allow this MCMC sampler to switch between metastable states and ideally mix faster. Gore…

Probability · Mathematics 2017-05-03 Reza Gheissari , Eyal Lubetzky , Yuval Peres

The Cellular Potts Model (CPM) is a lattice based modeling technique which is widely used for simulating cellular patterns such as foams or biological tissues. Despite its realism and generality, the standard Monte Carlo algorithm used in…

Soft Condensed Matter · Physics 2016-09-14 Marc Durand , Etienne Guesnet

Markov chain Monte Carlo methods are primarily used for sampling from a given probability distribution and estimating multi-dimensional integrals based on the information contained in the generated samples. Whenever it is possible, more…

Statistical Mechanics · Physics 2017-05-22 Manuel Athènes , Pierre Terrier

In recent years the Swap Monte Carlo algorithm has led to remarkable progress in equilibrating supercooled model liquids at low temperatures. Applications have so far been limited to systems composed of spherical particles, however, whereas…

Soft Condensed Matter · Physics 2025-09-05 Till Böhmer , Jeppe C. Dyre , Lorenzo Costigliola

We propose an iterative proposal to estimate critical points for statistical models based on configurations by combing machine-learning tools. Firstly, phase scenarios and preliminary boundaries of phases are obtained by…

Disordered Systems and Neural Networks · Physics 2019-10-23 X. L. Zhao , L. B. Fu

A numerical model able to simulate solid-state constrained sintering is presented. The model couples an existing kinetic Monte Carlo (kMC) model for free sintering with a finite element model (FEM) for calculating stresses on a…

Materials Science · Physics 2016-05-10 R. Bjørk , H. L. Frandsen , N. Pryds

We propose a modification of the embedded-atom method-type potential aiming at reconciling simulated melting and ground-state properties of metals by means of classical molecular dynamics. Considering titanium, magnesium, gold, and platinum…

Mesoscale and Nanoscale Physics · Physics 2016-04-15 Gennady Sushko , Alexey Verkhovtsev , Christian Kexel , Andrei V. Korol , Stefan Schramm , Andrey V. Solov'yov

We investigate the lattice spacing dependence of the equilibration time for a recently proposed multiscale thermalization algorithm for Markov chain Monte Carlo simulations. The algorithm uses a renormalization-group matched coarse lattice…

High Energy Physics - Lattice · Physics 2018-04-18 William Detmold , Michael G. Endres

This work proposes an extension of phase change and latent heat models for the simulation of metal powder bed fusion additive manufacturing processes on the macroscale and compares different models with respect to accuracy and numerical…

Computational Engineering, Finance, and Science · Computer Science 2021-09-07 Sebastian D. Proell , Wolfgang A. Wall , Christoph Meier

We present an algorithm for the simulation of three-dimensional spin glasses deep in the low-temperature phase: Parallel Tempering enhanced with Houdayer moves and with an entropic reservoir (PTHR). Although differences with the standard…

Disordered Systems and Neural Networks · Physics 2026-05-26 Claudio Chilin , Enzo Marinari , Víctor Martín-Mayor , Giorgio Parisi , Juan J. Ruiz-Lorenzo , David Yllanes

We discuss methods that allow to increase the step-size in a parallel tempering simulation of statistical models and test them at the example of the three-dimensional Heisenberg spin glass. We find an overall speed-up of about two for…

Statistical Mechanics · Physics 2010-11-19 Martin Hasenbusch , Stefan Schaefer

The Bayesian paradigm is becoming an increasingly popular framework for estimation and uncertainty quantification of unknown parameters in geo-physical inversion problems. Badlands is a basin and landscape evolution forward model for…

We establish finite sample bounds for the error of standard and waste-free SMC samplers. Our results cover estimates of both expectations and normalising constants of the target distributions. We consider first an arbitrary sequence of…

Computation · Statistics 2026-04-15 Yvann Le Fay , Nicolas Chopin , Matti Vihola

We present a novel Exchange Monte Carlo (EMC) method designed for application in continuous-space Path Integral Monte Carlo (PIMC) simulations at finite temperature. Traditional PIMC methods for bosonic systems suffer from long…

Statistical Mechanics · Physics 2026-05-26 Xun Zhao , Synge Todo

The dynamics of quantum entanglement plays a central role in explaining the emergence of thermal equilibrium in isolated many-body systems. However, entanglement is notoriously hard to measure. Recent works have introduced a notion of…

Quantum Physics · Physics 2025-03-20 Xiaozhou Feng , Matteo Ippoliti

An approximate treatment of exchange in finite-temperature path integral Monte Carlo simulations for fermions has been proposed. In this method, some of the fine details of density matrix due to permutations have been smoothed over or…

Statistical Mechanics · Physics 2015-05-13 D. Y. Sun

Recently, diffusion probabilistic models (DPMs) have achieved promising results in diverse generative tasks. A typical DPM framework includes a forward process that gradually diffuses the data distribution and a reverse process that…

Machine Learning · Computer Science 2023-10-31 Tianyu Pang , Cheng Lu , Chao Du , Min Lin , Shuicheng Yan , Zhijie Deng

We study how the thermodynamic properties of the Triangular Plaquette Model (TPM) are influenced by the addition of extra interactions. The thermodynamics of the original TPM is trivial, while its dynamics is glassy, as usual in Kinetically…

Disordered Systems and Neural Networks · Physics 2016-03-23 Silvio Franz , Giacomo Gradenigo , Stefano Spigler

Simulated annealing - moving from a tractable distribution to a distribution of interest via a sequence of intermediate distributions - has traditionally been used as an inexact method of handling isolated modes in Markov chain samplers.…

Computational Physics · Physics 2007-05-23 Radford M. Neal

Restricted Boltzmann Machines are simple and powerful generative models that can encode any complex dataset. Despite all their advantages, in practice the trainings are often unstable and it is difficult to assess their quality because the…

Machine Learning · Computer Science 2023-03-16 Nicolas Béreux , Aurélien Decelle , Cyril Furtlehner , Beatriz Seoane
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