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A Monte Carlo event generator has been developed assuming thermal production of hadrons. The system under consideration is sampled grand canonically in the Boltzmann approximation. A re-weighting scheme is then introduced to account for…

Nuclear Theory · Physics 2009-12-14 M. Hauer , S. Wheaton

Boltzmann sampling based on Metropolis algorithm has been extensively used for simulating a canonical ensemble. An estimate of a mechanical property, like energy, of an equilibrium system, can be made by averaging over a large number…

Statistical Mechanics · Physics 2017-10-04 K P N Murthy

We propose a new ensemble for Monte Carlo simulations, in which each state is assigned a statistical weight $1/k$, where $k$ is the number of states with smaller or equal energy. This ensemble has robust ergodicity properties and gives…

Condensed Matter · Physics 2016-08-31 Bobby Hesselbo , R. B. Stinchcombe

A generalization of the microcanonical ensemble suggests a simple strategy for the simulation of first order phase transitions. At variance with flat-histogram methods, there is no iterative parameters optimization, nor long waits for…

Statistical Mechanics · Physics 2008-11-26 V. Martin-Mayor

The fluctuations of the atom number between a Bose-Einstein condensate and the surrounding thermal gas have been the subject of a long standing theoretical debate. This discussion is centered around the appropriate thermodynamic ensemble to…

Direct sampling of multi-dimensional systems with quantum Monte Carlo methods allows exact account of many-body effects or particle correlations. The most straightforward approach to solve the Schr\"odinger equation, Diffusion Monte Carlo,…

Quantum Physics · Physics 2017-09-07 Ilkka Ruokosenmäki , Tapio T. Rantala

To efficiently evaluate system reliability based on Monte Carlo simulation, importance sampling is used widely. The optimal importance sampling density was derived in 1950s for the deterministic simulation model, which maps an input to an…

Methodology · Statistics 2019-06-04 Quoc Dung Cao , Youngjun Choe

Calculating one-body density profiles in equilibrium via particle-based simulation methods involves counting of events of particle occurrences at (histogram-resolved) space points. Here we investigate an alternative method based on a…

Soft Condensed Matter · Physics 2018-11-07 Daniel de las Heras , Matthias Schmidt

We propose sequential Monte Carlo (SMC) methods for sampling the posterior distribution of state-space models under highly informative observation regimes, a situation in which standard SMC methods can perform poorly. A special case is…

Computation · Statistics 2015-07-10 Pierre Del Moral , Lawrence M. Murray

In this paper, we introduce a dynamical Monte Carlo algorithm for spin models in which the number of the spins fluctuates from zero to a given number by addition and deletion of spins with a probabilistic rule. Such simulations are realized…

Statistical Mechanics · Physics 2009-10-31 Yukito Iba

An efficient method for computing thermodynamic equilibrium states at the micromagnetic length scale is introduced, using the Markov chain Monte Carlo method. Trial moves include not only rotations of vectors, but also a change in their…

Mesoscale and Nanoscale Physics · Physics 2021-11-10 Serban Lepadatu

Increasing shares of fluctuating renewable energy sources induce higher and higher power flow variability at the transmission level. The question arises as to what extent existing networks can absorb additional fluctuating power injection…

Systems and Control · Computer Science 2014-11-18 Markus Schläpfer , Pierluigi Mancarella

An efficient Path Integral Monte Carlo procedure is proposed to simulate the behavior of quantum many-body dissipative systems described within the framework of the influence functional. Thermodynamic observables are obtained by Monte Carlo…

Statistical Mechanics · Physics 2009-11-07 Luca Capriotti , Alessandro Cuccoli , Andrea Fubini , Valerio Tognetti , Ruggero Vaia

We propose a new time quantifiable Monte Carlo (MC) method to simulate the thermally induced magnetization reversal for an isolated single domain particle system. The MC method involves the determination of density of states, and the use of…

Statistical Mechanics · Physics 2009-11-11 X. Z. Cheng , M. B. A. Jalil , H. K. Lee , Y. Okabe

Using a Hubbard-Stratonovich transformation coupled with Fourier path integral methods, expressions are derived for the numerical evaluation of the microcanonical density of states for quantum particles obeying Boltzmann statistics. A…

chem-ph · Physics 2009-10-22 David L. Freeman , J. D. Doll

Several approximations are made to study the microcanonical formalism that are valid in the thermodynamics limit. Usually it is assumed that: 1)Stirling approximation can be used to evaluate the number of microstates; 2) the surface entropy…

General Physics · Physics 2015-10-07 E. N. Miranda , Dalia S. Bertoldi

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

In this paper, we draw attention to the problem of phase transitions in systems with locally affine microcanonical entropy, in which partial equivalence of (microcanonical and canonical) ensembles is observed. We focus on a very simple spin…

Statistical Mechanics · Physics 2020-02-19 Agata Fronczak , Piotr Fronczak , Grzegorz Siudem

For a classical system of noninteracting particles we establish recursive integral equations for the density of states on the microcanonical ensemble. The recursion can be either on the number of particles or on the dimension of the system.…

Statistical Mechanics · Physics 2013-04-19 Loic Turban

A well-established numerical technique to study the dynamics of spin systems in which symmetries and conservation laws play an important role is to microcanonically integrate their reversible equations of motion, obtaining thermalization…

Statistical Mechanics · Physics 2023-06-27 Andrea Cavagna , Javier Cristín , Irene Giardina , Mario Veca