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In probability theory and statistics, the IID model represents a single population, and a large, potentially infinite sample from this population. Main theorems, in particular the central limit theorem and laws of large number (LLN) assure…

Statistics Theory · Mathematics 2017-10-02 Uwe Saint-Mont

Using Wang-landau algorithm combined with analytic method, the density of states of two dimensional XY model on square lattices of sizes $16\times16$, $24\times24$ and $32\times32$ is accurately calculated. Thermodynamic quantities, such as…

Statistical Mechanics · Physics 2010-03-16 Jun Xu , H. R. Ma

Triangulations are important objects of study in combinatorics, finite element simulations and quantum gravity, where its entropy is crucial for many physical properties. Due to their inherent complex topological structure even the number…

Computational Physics · Physics 2015-03-05 Johannes F. Knauf , Benedikt Krüger , Klaus Mecke

We present a perfect marginal sampler of the unique Gibbs measure of a spin system on $\mathbb Z^2$. The algorithm is an adaptation of a previous `lazy depth-first' approach by the authors, but relaxes the requirement of strong spatial…

Data Structures and Algorithms · Computer Science 2023-02-16 Konrad Anand , Mark Jerrum

We propose a method for Monte Carlo simulation of statistical physical models with discretized energy. The method is based on several ideas including the cluster algorithm, the multicanonical Monte Carlo method and its acceleration proposed…

Statistical Mechanics · Physics 2009-11-07 Chiaki Yamaguchi , Naoki Kawashima

The thermodynamic properties of systems with long-range interactions is still an ongoing challenge, both from the point of view of theory as well as computer simulation. In this work we study a model system, a Coulomb gas confined inside a…

Statistical Mechanics · Physics 2020-11-04 Sergio Davis , Jalaj Jain , Biswajit Bora

This paper is concerned with probabilistic techniques for forecasting dynamical systems described by partial differential equations (such as, for example, the Navier-Stokes equations). In particular, it is investigating and comparing…

Machine Learning · Computer Science 2025-11-07 Hans Harder , Abhijeet Vishwasrao , Luca Guastoni , Ricardo Vinuesa , Sebastian Peitz

We present a technique designed for parallelizing large rigid body simulations, capable of exploiting multiple CPU cores within a computer and across a network. Our approach can be applied to simulate both unilateral and bilateral…

Graphics · Computer Science 2024-03-27 Manas Kale , Paul G. Kry

By combining two generalized-ensemble algorithms, Replica-Exchange Wang-Landau (REWL) method and Multicanonical Replica-Exchange Method (MUCAREM), we propose an effective simulation protocol to determine the density of states with high…

Statistical Mechanics · Physics 2019-10-23 Takuya Hayashi , Yuko Okamoto

We explain the fundamental challenges of sampling from multimodal distributions, particularly for high-dimensional problems. We present the major types of MCMC algorithms that are designed for this purpose, including parallel tempering,…

Computation · Statistics 2025-01-13 Krzysztof Łatuszyński , Matthew T. Moores , Timothée Stumpf-Fétizon

Coarse-grained (lattice-) models have a long tradition in aiding efforts to decipher the physical or biological complexity of proteins. Despite the simplicity of these models, however, numerical simulations are often computationally very…

Soft Condensed Matter · Physics 2012-09-14 Thomas Wüst , David P. Landau

Wang and Landau proposed recently, a simple and flexible non-Boltzmann Monte Carlo method for estimating the density of states, from which the macroscopic properties of a closed system can be calculated. They demonstrated their algorithm by…

Statistical Mechanics · Physics 2009-11-11 D. Jayasri , V. S. S. Sastry , K. P. N. Murthy

As far as we know, there is no flat-histogram algorithm to sample the stationary distribution of non-equilibrium stochastic processes. The present work addresses this gap by introducing a generalization of the Wang-Landau algorithm, applied…

Statistical Mechanics · Physics 2026-02-27 L. M. C. Alencar , T. F. A. Alves , G. A. Alves , F. W. S. Lima , A. Macedo-Filho , R. S. Ferreira

The multiple range random walk algorithm recently proposed by Wang and Landau [Phys. Rev. Lett. 86, 2050 (2001)] is adapted to the computation of free energy profiles for molecular systems along reaction coordinates. More generally, we show…

Statistical Mechanics · Physics 2009-11-07 F. Calvo

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

In this work we develop an implementation of the Wang--Landau algorithm [Phys. Rev. Lett. \textbf{86}, 2050-2053 (2001)]. This algorithm allows us to find the density of states (DOS), a function that, for a given system, describes the…

Statistical Mechanics · Physics 2022-02-09 Felipe Moreno , Joaquín Peralta , Sergio Davis

We implemented a parallel version of the multicanonical algorithm and applied it to a variety of systems with phase transitions of first and second order. The parallelization relies on independent equilibrium simulations that only…

Computational Physics · Physics 2015-01-27 Johannes Zierenberg , Martin Marenz , Wolfhard Janke

Efficient simulations of quantum evolutions of spin-1/2 systems are relevant for ensemble quantum computation as well as in typical NMR experiments. We propose an efficient method to calculate the dynamics of an observable provided that the…

We propose a novel way of investigating the universal properties of spin systems by coupling them to an ensemble of causal dynamically triangulated lattices, instead of studying them on a fixed regular or random lattice. Somewhat…

High Energy Physics - Lattice · Physics 2008-11-26 D. Benedetti , R. Loll

We introduce a novel framework for simulating spin models using differentiable programming, an approach that leverages the advancements in machine learning and computational efficiency. We focus on three distinct spin systems: the Ising…

Statistical Mechanics · Physics 2024-05-28 Tiago de Souza Farias , Vitor Vaz Schultz , José Carlos Merino Mombach , Jonas Maziero