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We propose a new recursive procedure to estimate the microcanonical density of states in multicanonical Monte Carlo simulations which relies only on measurements of moments of the energy distribution, avoiding entirely the need for energy…

Statistical Mechanics · Physics 2007-05-23 J. Viana Lopes , Miguel D. Costa , J. M. B. Lopes dos Santos , R. Toral

A statistical method is derived for the calculation of thermodynamic properties of many-body systems at low temperatures. This method is based on the self-healing diffusion Monte Carlo method for complex functions [F. A. Reboredo J. Chem.…

Other Condensed Matter · Physics 2014-03-05 Fernando A. Reboredo , Jeongnim Kim

Thermodynamics of dissipative quantum systems with double-well potentials is studied by the path-integral Monte Carlo (PIMC) method without truncation to the two-state model. For efficient simulation at low temperatures, we develop a new…

Statistical Mechanics · Physics 2007-05-23 Takeshi Matsuo , Yuhei Natsume , Takeo Kato

We study the transport and the relaxation properties of a molecular supercooled liquid by molecular-dynamics numerical simulations. The focus is on the translational motion. Jump motion is detected. At lower temperature the Stokes-Einstein…

Statistical Mechanics · Physics 2007-05-23 Cristiano De Michele , Dino Leporini

In molecular simulations, efficient methods for investigating equilibration and slow relaxation in dense systems are crucial yet challenging. This study focuses on the diffusional characteristics of monodisperse hard disk systems at…

Soft Condensed Matter · Physics 2024-10-21 Daigo Mugita , Masaharu Isobe

We present the explicit bonding Reaction ensemble Monte Carlo (eb-RxMC) method, designed to sample reversible bonding reactions in macromolecular systems in thermodynamic equilibrium. Our eb-RxMC method is based on the Reaction ensemble…

Soft Condensed Matter · Physics 2024-09-13 Pablo M. Blanco , Peter Košovan

We present a nonlocal Monte Carlo algorithm with particle swaps that greatly accelerates thermalization of soft sphere binary mixtures in the glassy region. Our first results show that thermalization of systems of hundreds of particles is…

Disordered Systems and Neural Networks · Physics 2009-10-31 Tomas S. Grigera , Giorgio Parisi

We introduce a Monte-Carlo method that allows for the simulation of a polymeric phase containing a weak polyelectrolyte, which is coupled to a reservoir at a fixed pH, salt concentration and total concentration of a weak polyprotic acid.…

Soft Condensed Matter · Physics 2023-07-12 David Beyer , Christian Holm

Ab initio Monte Carlo simulations have been performed to determine the equilibrium properties of liquid lithium and lithium clusters at different temperatures. First-principles density-functional methods were employed to calculate the…

Materials Science · Physics 2007-05-23 Sanwu Wang , Steven J. Mitchell , Per Arne Rikvold

Replica exchange (RE) is one of the most popular enhanced-sampling simulations technique in use today. Despite widespread successes, RE simulations can sometimes fail to converge in practical amounts of time, e.g., when sampling around…

Statistical Mechanics · Physics 2021-05-13 Thomas Vogel , Danny Perez

We present an effcient Monte-Carlo method for lattice glass models which are characterized by hard constraint conditions. The basic idea of the method is similar to that of the $N$-fold way method. By using a list of sites into which we can…

Statistical Mechanics · Physics 2015-06-05 Munetaka Sasaki , Koji Hukushima

We develop a classical Monte Carlo algorithm based on a quasi-classical approximation for a pseudospin S=1 Hamiltonian in real space to construct a phase diagram of a model cuprate with a high Tc. A model description takes into account both…

Strongly Correlated Electrons · Physics 2021-10-25 Yu. D. Panov , A. S. Moskvin , A. A. Chikov , V. A. Ulitko

We present an algorithm for the simulation of the exact real-time dynamics of classical many-body systems with discrete energy levels. In the same spirit of kinetic Monte Carlo methods, a stochastic solution of the master equation is found,…

Statistical Mechanics · Physics 2016-07-20 Alejandro Mendoza-Coto , Rogelio Díaz-Méndez , Guido Pupillo

We introduce the Quantization Monte Carlo method to solve thermal radiative transport equations with possibly several collision regimes, ranging from few collisions to massive number of collisions per time unit. For each particle in a given…

Computational Physics · Physics 2024-09-13 Laetitia Laguzet , Gabriel Turinici

Computational codes based on the Diffusion Monte Carlo method can be used to determine the quantum state of two-electron systems confined by external potentials of various nature and geometry. In this work, we show how the application of…

Chemical Physics · Physics 2021-02-24 Gaia Micca Longo , Carla Maria Coppola , Domenico Giordano , Savino Longo

Bayesian data analysis is widely used across many disciplines, and representative examples in materials science include spectral analysis and sparse modeling. In such applications, the underlying models often become complex and yield…

Information Theory · Computer Science 2026-03-04 Tomohiro Nabika , Kenji Nagata , Shun Katakami , Masaichiro Mizumaki , Masato Okada

We report the results of Monte Carlo simulations investigating the effect of a spherical confinement within a simple model for a flexible homopolymer. We use the parallel tempering method combined with multi-histogram reweighting analysis…

Soft Condensed Matter · Physics 2012-12-27 M. Marenz , J. Zierenberg , H. Arkin , W. Janke

This paper introduces a class of Monte Carlo algorithms which are based upon the simulation of a Markov process whose quasi-stationary distribution coincides with a distribution of interest. This differs fundamentally from, say, current…

Methodology · Statistics 2020-04-14 Murray Pollock , Paul Fearnhead , Adam M. Johansen , Gareth O. Roberts

Combinatorial optimization problems play crucial roles in real-world applications, and many studies from a physics perspective have contributed to specialized hardware for high-speed computation. However, some combinatorial optimization…

Applied Physics · Physics 2025-01-07 Tatsuya Naoi , Tatsuya Kishimoto , Jun Ohkubo

This paper is concerned with differentiable resampling in the context of sequential Monte Carlo (e.g., particle filtering). Drawing on reparametrisation, we propose a new resampling method that is informative and instantly differentiable,…

Machine Learning · Statistics 2026-05-29 Jennifer Rosina Andersson , Zheng Zhao