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Monte Carlo simulation has been performed in one-dimensional Lebwohl-Lasher model and two dimensional XY-model using the Wang-Landau and the Wang-Landau-Transition-Matrix Monte Carlo methods. Random walk has been performed in the…

Statistical Mechanics · Physics 2010-05-27 Shyamal Bhar , Soumen Kumar Roy

Relaxational processes in ordered phases of one-dimensional Ising models with long-range interactions are investigated by Monte Carlo simulations. Three types of spin model, the pure ferromagnetic, the diluted ferromagnetic, and the spin…

Statistical Mechanics · Physics 2017-01-04 Yusuke Tomita

We present preliminary results of our numerical study of the critical dynamics of percolation observables for the two-dimensional Ising model. We consider the (Monte-Carlo) short-time evolution of the system obtained with a local heat-bath…

High Energy Physics - Lattice · Physics 2009-11-11 W. G. Wanzeller , G. Krein , T. Mendes

The importance-sampling Monte Carlo algorithm appears to be the universally optimal solution to the problem of sampling the state space of statistical mechanical systems according to the relative importance of configurations for the…

Statistical Mechanics · Physics 2010-06-22 Martin Weigel

In recent years dynamical systems (of deterministic and stochastic nature), describing many models in mathematics, physics, engineering and finances, become more and more complex. Numerical analysis narrowed only to deterministic algorithms…

Numerical Analysis · Mathematics 2024-02-13 Paweł Przybyłowicz

In finite-size scaling analyses of Monte Carlo simulations of second-order phase transitions one often needs an extended temperature range around the critical point. By combining the parallel tempering algorithm with cluster updates and an…

Statistical Mechanics · Physics 2015-05-28 Elmar Bittner , Wolfhard Janke

We introduce a novel Entropy-driven Monte Carlo (EdMC) strategy to efficiently sample solutions of random Constraint Satisfaction Problems (CSPs). First, we extend a recent result that, using a large-deviation analysis, shows that the…

Disordered Systems and Neural Networks · Physics 2016-02-26 Carlo Baldassi , Alessandro Ingrosso , Carlo Lucibello , Luca Saglietti , Riccardo Zecchina

We study the low temperature out of equilibrium Monte Carlo dynamics of the disordered Ising $p$-spin Model with $p=3$ and a small number of spin variables. We focus on sequences of configurations that are stable against single spin flips…

Disordered Systems and Neural Networks · Physics 2020-08-28 Daniel A. Stariolo , Leticia F. Cugliandolo

We use kinetic Monte Carlo simulations to investigate current fluctuations in boundary driven generalized exclusion processes, in different dimensions. Simulation results are in full agreement with predictions based on the additivity…

Statistical Mechanics · Physics 2015-06-01 T. Becker , K. Nelissen , B. Cleuren

Colloids have a striking relevance in a wide spectrum of industrial formulations, spanning from personal care products to protective paints. Their behaviour can be easily influenced by extremely weak forces, which disturb their…

Soft Condensed Matter · Physics 2018-06-14 Daniel Corbett , Alejandro Cuetos , Matthew Dennison , Alessandro Patti

A classical Monte Carlo algorithm based on the quasi-classical approximation is applied to the pseudospin Hamiltonian of the model cuprate. The model takes into account both local and non-local correlations, Heisenberg spin-exchange…

Computational Physics · Physics 2026-01-01 V. A. Ulitko , Yu. D. Panov , A. S. Moskvin

Monte Carlo algorithms often aim to draw from a distribution $\pi$ by simulating a Markov chain with transition kernel $P$ such that $\pi$ is invariant under $P$. However, there are many situations for which it is impractical or impossible…

Methodology · Statistics 2014-04-16 P. Alquier , N. Friel , R. Everitt , A. Boland

We study the off-equilibrium relaxational dynamics at criticality in the three-dimensional Blume-Capel model whose static critical behaviour belongs to the 3d-Ising universality class. Using "improved" Hamiltonian (the leading corrections…

Statistical Mechanics · Physics 2015-03-17 Mario Collura

The efficient representation of quantum many-body states with classical resources is a key challenge in quantum many-body theory. In this work we analytically construct classical networks for the description of the quantum dynamics in…

Strongly Correlated Electrons · Physics 2018-03-01 Markus Schmitt , Markus Heyl

We introduce a method to simulate open quantum many-body dynamics by combining time-dependent variational Monte Carlo (tVMC) with quantum trajectory techniques. Our approach unravels the Lindblad master equation into an ensemble of…

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

This paper develops and analyzes an efficient numerical method for solving elliptic partial differential equations, where the diffusion coefficients are random perturbations of deterministic diffusion coefficients. The method is based upon…

Numerical Analysis · Mathematics 2016-03-30 X. Feng , J. Lin. , C. Lorton

The effect of different move sets on the folding kinetics of the Monte Carlo simulations is analysed based on the conformation-network and the temperature-dependent folding kinetics. A new scheme of implementing Metropolis algorithm is…

Soft Condensed Matter · Physics 2007-05-23 Yu-Pin Luo , Ming-Chang Huang , Yen-Liang Chou , Tsong-Ming Liaw

With Monte Carlo simulations, we investigate the relaxation dynamics with a domain wall for magnetic systems at the critical temperature. The dynamic scaling behavior is carefully analyzed, and a dynamic roughening process is observed. For…

Statistical Mechanics · Physics 2012-02-08 N. J. Zhou , B. Zheng , D. P. Landau

The effectiveness of stochastic algorithms based on Monte Carlo dynamics in solving hard optimization problems is mostly unknown. Beyond the basic statement that at a dynamical phase transition the ergodicity breaks and a Monte Carlo…

Disordered Systems and Neural Networks · Physics 2019-07-10 Maria Chiara Angelini , Federico Ricci-Tersenghi