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Related papers: Simulation of Spin Glass with a Variable-system-si…

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We present an extension of the semi-grandcanonical (SGC) ensemble that we refer to as the variance-constrained semi-grandcanonical (VC-SGC) ensemble. It allows for transmutation Monte Carlo simulations of multicomponent systems in…

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

We studied the performance of the multicanonical algorithm by simulating the van Hemmen spin glass model and reproduced the exact results for this mean field model. Physical quantities such as energy density, specific heat, susceptibility…

Condensed Matter · Physics 2007-05-23 Mohammad Katoot , Ulrich H. E. Hansmann , Tarik Celik

After developing an appropriate iteration procedure for the determination of the parameters, the method of simulated tempering has been successfully applied to the 2D Ising spin glass. The reduction of the slowing down is comparable to that…

Condensed Matter · Physics 2009-10-22 Werner Kerler , Peter Rehberg

We consider a microcanonical local algorithm to be applied on the $\pm J$ spin glass model. We have compared the results coming from a microcanonical Monte Carlo simulation with those from a canonical one: Thermalization times, spin glass…

Disordered Systems and Neural Networks · Physics 2009-10-31 J. J. Ruiz-Lorenzo , C. L. Ullod

A new efficient ensemble prediction strategy is developed for a general turbulent model framework with emphasis on the nonlinear interactions between large and small scale variables. The high computational cost in running large ensemble…

Fluid Dynamics · Physics 2023-02-22 Di Qi , Jian-Guo Liu

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

We propose and use a novel, hybrid Monte Carlo algorithm that combines configurational bias particle swaps with parallel tempering. We use this new method to simulate a standard model of a glass forming binary mixture above and below the…

Soft Condensed Matter · Physics 2009-11-11 Elijah Flenner , Grzegorz Szamel

We present a reduced-dimension, ballistic deposition, Monte Carlo particle packing algorithm and discuss its application to the analysis of the microstructure of hard-sphere systems with broad particle size distributions. We extend our…

Materials Science · Physics 2007-05-23 M. D. Webb , I. L. Davis

In this paper I report results for simulations of the three-dimensional gauge glass and the four-dimensional XY spin glass using the parallel tempering Monte Carlo method at low temperatures for moderate sizes. The results are qualitatively…

Disordered Systems and Neural Networks · Physics 2009-11-07 Helmut G. Katzgraber

We have studied the spin-polarized three-dimensional homogeneous electron gas using the diffusion quantum Monte Carlo method, with trial wave functions including backflow and three-body correlations in the Jastrow factor, and we have used…

Strongly Correlated Electrons · Physics 2013-08-28 G G Spink , R J Needs , N D Drummond

The basic problem in equilibrium statistical mechanics is to compute phase space average, in which Monte Carlo method plays a very important role. We begin with a review of nonlocal algorithms for Markov chain Monte Carlo simulation in…

Statistical Mechanics · Physics 2007-05-23 Jian-Sheng Wang

Adiabatic quantum computers, such as the quantum annealers commercialized by D-Wave Systems Inc., are routinely used to tackle combinatorial optimization problems. In this article, we show how to exploit them to accelerate equilibrium…

Disordered Systems and Neural Networks · Physics 2023-07-12 Giuseppe Scriva , Emanuele Costa , Benjamin McNaughton , Sebastiano Pilati

An efficient simulation-based methodology is proposed for the rolling window estimation of state space models, called particle rolling Markov chain Monte Carlo (MCMC) with double block sampling. In our method, which is based on Sequential…

Computation · Statistics 2021-09-17 Naoki Awaya , Yasuhiro Omori

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

We study the spacial and temporal multiscale properties of complex systems. We present accelerated algorithms for dilute spin glasses and display explicitly their relation to the effective dynamics of specific collective degrees of freedom…

Condensed Matter · Physics 2008-02-03 N. Persky , S. Solomon

A major challenge in simulating glassy systems is the ability to generate configurations that may be found in equilibrium at sufficiently low temperatures, in order to probe static and dynamic behaviour close to the glass transition. A…

Soft Condensed Matter · Physics 2024-06-19 Pallabi Das , Anshul D. S. Parmar , Srikanth Sastry

We discuss Monte Carlo dynamics based on <N(sigma, Delta E)>_E, the (microcanonical) average number of potential moves which increase the energy by Delta E in a single spin flip. The microcanonical average can be sampled using Monte Carlo…

Statistical Mechanics · Physics 2009-10-31 Jian-Sheng Wang , Lik Wee Lee

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

Quantum mechanics for many-body systems may be reduced to the evaluation of integrals in 3N dimensions using Monte-Carlo, providing the Quantum Monte Carlo ab initio methods. Here we limit ourselves to expectation values for trial…

Computational Physics · Physics 2010-11-22 John Robert Trail , Ryo Maezono
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