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We present a novel Monte Carlo algorithm which enhances equilibrization of low-temperature simulations and allows sampling of configurations over a large range of energies. The method is based on a non-Boltzmann probability weight factor…

Condensed Matter · Physics 2009-10-30 Ulrich H. E. Hansmann , Yuko Okamoto

We present density response estimators for Monte Carlo simulations that are based on a reweighting procedure, where the samples of an unperturbed system are used to estimate the properties of a system perturbed by an external harmonic…

A boundary-based net-exchange Monte Carlo method was introduced in [1] that allows to bypass the difficulties encountered by standard Monte Carlo algorithms in the limit of optically thick absorption (and/or for quasi-isothermal…

Computational Physics · Physics 2019-03-06 V. Eymet , R. Fournier , S. Blanco , J. L. Dufresne

We study the rate of convergence to equilibrium of the self-repellent random walk and its local time process on the discrete circle $\mathbb{Z}_n$. While the self-repellent random walk alone is non-Markovian since the jump rates depend on…

Probability · Mathematics 2025-12-01 Andreas Eberle , Francis Lörler

We present a novel quasi-Monte Carlo mechanism to improve graph-based sampling, coined repelling random walks. By inducing correlations between the trajectories of an interacting ensemble such that their marginal transition probabilities…

Machine Learning · Statistics 2024-05-27 Isaac Reid , Eli Berger , Krzysztof Choromanski , Adrian Weller

The method of tempered transitions was proposed by Neal (1996) for tackling the difficulties arising when using Markov chain Monte Carlo to sample from multimodal distributions. In common with methods such as simulated tempering and…

Computation · Statistics 2012-09-11 Gundula Behrens , Nial Friel , Merrilee Hurn

We propose new polymer models for Monte Carlo simulation and apply them to a polymer chain confined in a relatively thin box which has both curved and flat sides, and show that either an ideal or an excluded-volume chain spends more time in…

Soft Condensed Matter · Physics 2007-05-23 Y. Y. Suzuki , T. Dotera , M. Hirabayashi

When approaching the continuum limit in lattice QCD or other theories in a setup with topological sectors, conventional update algorithms experience a particularly severe form of critical slowing down that is caused by high action barriers…

High Energy Physics - Lattice · Physics 2025-03-28 Timo Eichhorn , Gianluca Fuwa , Christian Hoelbling , Lukas Varnhorst

We study the diffusion of a linear polymer in the presence of permeable membranes without excluded volume interactions, using scaling theory and Monte Carlo simulations. We find that the average time it takes for a chain with polymerization…

Condensed Matter · Physics 2016-08-31 Hyoungsoo Yoon , J. M. Deutsch

Most Markov chain Monte Carlo methods operate in discrete time and are reversible with respect to the target probability. Nevertheless, it is now understood that the use of non-reversible Markov chains can be beneficial in many contexts. In…

Methodology · Statistics 2021-02-23 Chris Sherlock , Alexandre H. Thiery

The basic problem in equilibrium statistical mechanics is to compute phase space average, in which Monte Carlo method plays a very important role. We begin with a review of nonlocal algorithms for Markov chain Monte Carlo simulation in…

Statistical Mechanics · Physics 2007-05-23 Jian-Sheng Wang

Sampling from the full posterior distribution of high-dimensional non-linear, non-Gaussian latent dynamical models presents significant computational challenges. While Particle Gibbs (also known as conditional sequential Monte Carlo) is…

Computation · Statistics 2025-03-05 Adrien Corenflos , Simo Särkkä

Correlated fermions are of high interest in condensed matter (Fermi liquids, Wigner molecules), cold atomic gases and dense plasmas. Here we propose a novel approach to path integral Monte Carlo (PIMC) simulations of strongly degenerate…

Quantum Gases · Physics 2016-01-15 Tobias Dornheim , Simon Groth , Alexey Filinov , Michael Bonitz

An efficient approach of measuring the absolute free energy in parallel tempering Monte Carlo using the exponential averaging method is discussed and the results are compared with those of population annealing Monte Carlo using the…

Disordered Systems and Neural Networks · Physics 2015-05-20 Wenlong Wang

In the absence of impurities and boundary effects, first order phase transitions are initiated by the nucleation of critical bubbles. In thermally driven transitions many systems can remain metastable for an extended time, possibly tens of…

High Energy Physics - Lattice · Physics 2025-02-21 Jaakko Hällfors , Kari Rummukainen

A Monte Carlo method for dynamics simulation of all-atom protein models is introduced, to reach long times not accessible to conventional molecular dynamics. The considered degrees of freedom are the dihedrals at C$_\alpha$-atoms. Two Monte…

chem-ph · Physics 2009-10-28 Daniel Hoffmann , Ernst-Walter Knapp

The extreme slowing down associated with glass formation in experiments and in simulations results in serious difficulties to prepare deeply quenched, well annealed, glassy material. Recently, methods to achieve such deep quenching were…

Soft Condensed Matter · Physics 2020-07-08 Bhanu Prasad Bhowmik , Valery Iylin , Itamar Procaccia

While boundary plasmas in present-day tokamaks generally fall in a fluid regime, neutral species near the boundary often require kinetic models due to long mean-free-paths compared to characteristic spatial scales in the region. Monte-Carlo…

Plasma Physics · Physics 2025-01-31 Gregory J. Parker , Maxim V. Umansky , Benjamin D. Dudson

We show several results on convergence of the Monte Carlo method applied to consistent approximations of the isentropic Euler system of gas dynamics with uncertain initial data. Our method is based on combination of several new concepts. We…

Numerical Analysis · Mathematics 2024-04-19 Eduard Feireisl , Mária Lukáčová-Medvid'ová , Hana Mizerová , Changsheng Yu

In this work we show that randomized (block) coordinate descent methods can be accelerated by parallelization when applied to the problem of minimizing the sum of a partially separable smooth convex function and a simple separable convex…

Optimization and Control · Mathematics 2013-11-27 Peter Richtárik , Martin Takáč
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