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The critical behavior of the disordered ferromagnetic Ising model is studied numerically by the Monte Carlo method in a wide range of variation of concentration of nonmagnetic impurity atoms. The temperature dependences of correlation…

Disordered Systems and Neural Networks · Physics 2007-09-11 V. Prudnikov , P. Prudnikov , A. Vakilov , A. Krinitsyn

We develop clustering procedures for longitudinal trajectories based on a continuous-time hidden Markov model (CTHMM) and a generalized linear observation model. Specifically in this paper, we carry out finite and infinite mixture…

Methodology · Statistics 2021-12-08 Yu Luo , David A. Stephens , David L. Buckeridge

We develop a recently proposed importance-sampling Monte Carlo algorithm for sampling rare events and quenched variables in random disordered systems. We apply it to a two dimensional bond-diluted Ising model and study the Griffiths…

Disordered Systems and Neural Networks · Physics 2009-11-13 Koji Hukushima , Yukito Iba

Dilute dipolar Ising magnets remain a notoriously hard problem to tackle both analytically and numerically because of long-ranged interactions between spins as well as rare region effects. We study a new type of anisotropic dilute dipolar…

Disordered Systems and Neural Networks · Physics 2019-08-28 Tushar Kanti Bose , Roderich Moessner , Arnab Sen

Snapshots of colloidal particles moving on disordered two-dimensional substrates can be used to extract equal-time many-body correlations in their positions. To understand the systematics of these correlations, we perform Monte Carlo…

Soft Condensed Matter · Physics 2019-10-23 N. Shankaraiah , Surajit Sengupta , Gautam I. Menon

We study the fluctuation-induced Casimir interactions in colloidal suspensions, especially between colloids immersed in a binary liquid close to its critical demixing point. To simulate these systems, we present a highly efficient cluster…

Soft Condensed Matter · Physics 2017-06-09 Hendrik Hobrecht , Alfred Hucht

We present a new approach to study measures on ensembles of contours, polymers or other objects interacting by some sort of exclusion condition. For concreteness we develop it here for the case of Peierls contours. Unlike existing methods,…

Probability · Mathematics 2016-08-15 Roberto Fernández , Pablo A. Ferrari , Nancy L. Garcia

Potts spin systems play a fundamental role in statistical mechanics and quantum field theory, and can be studied within the spin, the Fortuin-Kasteleyn (FK) bond or the $q$-flow (loop) representation. We introduce a Loop-Cluster (LC) joint…

Statistical Mechanics · Physics 2020-11-16 Lei Zhang , Manon Michel , Eren M. Elçi , Youjin Deng

We present a Monte Carlo method to compute efficiently susceptibilites or covariances of two physical variables. The method relies on a generalization of the exchange cluster algorithm to any model of interacting particles with any $2$-body…

Computational Physics · Physics 2025-02-11 Assaraf Roland , Chevreau Hilaire

The fractal dimensions and the percolation exponents of the geometrical spin clusters of like sign at criticality, are obtained numerically for an Ising model with temperature-dependent annealed bond dilution, also known as the thermalized…

Statistical Mechanics · Physics 2012-04-03 S. Davatolhagh , M. Moshfeghian , A. A. Saberi

We have proposed a cluster heat bath method in Monte Carlo simulations of Ising models in which one of the possible spin configurations of a cluster is selected in accordance with its Boltzmann weight. We have argued that the method…

Condensed Matter · Physics 2009-10-30 F. Matsubara , A. Sato , O. Koseki , T. Shirakura

A continuous time cluster algorithm for two-level systems coupled to a dissipative bosonic bath is presented and applied to the sub-ohmic spin-Boson model. When the power s of the spectral function J(w) \propto w^s is smaller than 1/2, the…

Statistical Mechanics · Physics 2010-04-22 Andre Winter , Heiko Rieger , Matthias Vojta , Ralf Bulla

Many spin systems affected by critical slowing down can be efficiently simulated using cluster algorithms. Where such systems have long-range interactions, suitable formulations can additionally bring down the computational effort for each…

Statistical Mechanics · Physics 2017-04-07 Emilio Flores-Sola , Martin Weigel , Ralph Kenna , Bertrand Berche

The dynamical system for inertial particles in fluid flow has both attracting and repelling regions, the interplay of which can localize particles. In laminar flow experiments we find that particles, initially moving throughout the fluid…

Fluid Dynamics · Physics 2014-07-10 Steven Wang , Robert L. Stewart , Guy Metcalfe , Jie Wu

Monodisperse ensembles of particles that have cluster crystalline phases at low temperatures can model a number of physical systems, such as vortices in type-1.5 superconductors, colloidal suspensions and cold atoms. In this work we study a…

Soft Condensed Matter · Physics 2019-04-29 Wenlong Wang , Rogelio Díaz-Méndez , Mats Wallin , Jack Lidmar , Egor Babaev

The non-equilibrium dynamics of the three-dimensional Edwards-Anderson spin-glass model with different bond distributions is investigated by means of Monte Carlo simulation. A numerical method is used to determine the critical temperature…

Disordered Systems and Neural Networks · Physics 2010-12-15 F. Roma

We use Monte Carlo techniques and analytical methods to study the phase diagram of the M--component Widom-Rowlinson model on the bcc-lattice: there are M species all with the same fugacity z and a nearest neighbor hard core exclusion…

Statistical Mechanics · Physics 2015-06-25 P. Nielaba , J. L. Lebowitz

We present a methodology for simulating three-dimensional flow of incompressible viscoplastic fluids modelled by generalised Newtonian rheological equations. It is implemented in a highly efficient framework for massively parallelisable…

Fluid Dynamics · Physics 2019-09-17 Knut Sverdrup , Ann Almgren , Nikolaos Nikiforakis

Global optimization is an active area of research in atomistic simulations, and many algorithms have been proposed to date. A prominent example is basin hopping Monte Carlo, which performs a modified Metropolis Monte Carlo search to explore…

Chemical Physics · Physics 2020-02-04 Martín Leandro Paleico , Jörg Behler

Mixture models extend the toolbox of clustering methods available to the data analyst. They allow for an explicit definition of the cluster shapes and structure within a probabilistic framework and exploit estimation and inference…

Methodology · Statistics 2025-09-15 Bettina Grün