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Using a cluster-flipping Monte Carlo algorithm combined with a generalization of the histogram reweighting scheme of Ferrenberg and Swendsen, we have studied the equilibrium properties of the thermal random-field Ising model on a cubic…

Condensed Matter · Physics 2009-10-28 M. E. J. Newman , G. T. Barkema

The percolation of Kandel, Ben-Av and Domany clusters for 2d fully frustrated Ising model is extensively studied through numerical simulations. Critical exponents, cluster distribution and fractal dimension of percolative cluster are given.

Condensed Matter · Physics 2009-10-28 Giancarlo Franzese

Stochastic Differential Equations (SDEs) are used as statistical models in many disciplines. However, intractable likelihood functions for SDEs make inference challenging, and we need to resort to simulation-based techniques to estimate and…

Methodology · Statistics 2014-08-12 Grant Schneider , Peter F. Craigmile , Radu Herbei

We elaborate the idea behind Markov chain Monte Carlo (MCMC) methods in a mathematically coherent, yet simple and understandable way. To this end, we proof a pivotal convergence theorem for finite Markov chains and a minimal version of the…

Statistics Theory · Mathematics 2019-07-30 Tobias Siems

Importance sampling has been known as a powerful tool to reduce the variance of Monte Carlo estimator for rare event simulation. Based on the criterion of minimizing the variance of Monte Carlo estimator within a parametric family, we…

Methodology · Statistics 2013-02-11 Cheng-Der Fuh , Huei-Wen Teng , Ren-Her Wang

Monte Carlo evaluation is used to calculate heavy-ion elastic scattering including the center-of-mass correction and the Coulomb interaction.Angular distributions are presented for a number of nuclear pairs over a wide energy range using…

Nuclear Theory · Physics 2015-06-04 W. R. Gibbs , Jean-Pierre Dedonder

The random-cluster model, a correlated bond percolation model, unifies a range of important models of statistical mechanics in one description, including independent bond percolation, the Potts model and uniform spanning trees. By…

Statistical Mechanics · Physics 2016-01-28 Eren Metin Elçi , Martin Weigel , Nikolaos G. Fytas

We review the background of the cluster algorithms in Monte Carlo simulation of statistical physics problems. One of the first such successful algorithm was developed by Swendsen and Wang eight years ago. In contrast to the local…

Condensed Matter · Physics 2007-05-23 Jian-Sheng Wang

We define a percolation problem on the basis of spin configurations of the two dimensional XY model. Neighboring spins belong to the same percolation cluster if their orientations differ less than a certain threshold called the conducting…

Statistical Mechanics · Physics 2010-03-19 Yancheng Wang , Wenan Guo , Bernard Nienhuis , Henk W. J. Blöte

The aim of this Thesis is to present five new tests for random numbers, which are widely used {\em e.g.} in computer simulations in physics applications. The first two tests, the cluster test and the autocorrelation test, are based on…

Condensed Matter · Physics 2008-02-03 I. Vattulainen

Short time Monte Carlo methods are used to study the nonequilibrium ferromagnetic phase transition in a majority vote model in two dimensions. The existance of an initial critical slip regime is verified. The measured values of dyamic…

Condensed Matter · Physics 2009-10-30 J. F. F. Mendes , M. A. Santos

The study of the low temperature phase of spin glass models by means of Monte Carlo simulations is a challenging task, because of the very slow dynamics and the severe finite size effects they show. By exploiting at the best the…

Disordered Systems and Neural Networks · Physics 2014-04-02 Lucas Nicolao , Giorgio Parisi , Federico Ricci-Tersenghi

Using the concept of finite-size scaling, Monte Carlo calculations of various models have become a very useful tool for the study of critical phenomena, with the system linear dimension as a variable. As an example, several recent studies…

Statistical Mechanics · Physics 2009-10-31 Kurt Binder , Erik Luijten , Marcus Müller , Nigel B. Wilding , Henk W. J. Blöte

This work addresses the problem of estimating the parameters of the general half-normal distribution. Namely, the problem of determining the minimum risk equi\-va\-riant (MRE) estimators of the parameters is explored. Simulation studies are…

Methodology · Statistics 2021-10-28 A. G. Nogales , P. Pérez , P. Monfort

In this paper, we derive closed-form estimators for the parameters of certain exponential family distributions through the maximum a posteriori (MAP) equations. A Monte Carlo simulation is conducted to assess the performance of the proposed…

Methodology · Statistics 2025-05-16 Roberto Vila , Helton Saulo , Eduardo Nakano

Using an elaborate set of simulational tools and statistically optimized methods of data analysis we investigate the scaling behavior of the correlation lengths of three-dimensional classical O($n$) spin models. Considering…

Statistical Mechanics · Physics 2011-07-19 Martin Weigel , Wolfhard Janke

We consider a critical Fortuin-Kasteleyn (FK) percolation with cluster weight $q \in [1,4)$ in the plane, and color its clusters in red (respectively blue) with probability $r \in (0,1)$ (respectively $1-r$), independently of each other. We…

Probability · Mathematics 2025-01-17 Laurin Köhler-Schindler , Matthis Lehmkuehler

In statistical mechanics, observables are usually related to local degrees of freedom such as the Q < 4 distinct states of the Q-state Potts models or the heights of the restricted solid-on-solid models. In the continuum scaling limit,…

Statistical Mechanics · Physics 2009-11-13 Yvan Saint-Aubin , Paul A. Pearce , Jorgen Rasmussen

This paper discusses the topic of dimensionality reduction for $k$-means clustering. We prove that any set of $n$ points in $d$ dimensions (rows in a matrix $A \in \RR^{n \times d}$) can be projected into $t = \Omega(k / \eps^2)$…

Artificial Intelligence · Computer Science 2011-05-05 Christos Boutsidis , Anastasios Zouzias , Petros Drineas

We consider systems of stochastic differential equations with multiple scales and small noise and assume that the coefficients of the equations are ergodic and stationary random fields. Our goal is to construct provably-efficient importance…

Probability · Mathematics 2015-09-29 Konstantinos Spiliopoulos