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We introduce a general Monte Carlo scheme for achieving atomistic simulations with monoelectronic Hamiltonians including the thermalization of both nuclear and electronic degrees of freedom. The kinetic Monte Carlo algorithm is used to…

Materials Science · Physics 2009-11-07 F. Calvo , F. Spiegelman

A method is presented to tackle the sign problem in the simulations of systems having indefinite or complex-valued measures. In general, this new approach is shown to yield statistical errors smaller than the crude Monte Carlo using…

High Energy Physics - Lattice · Physics 2008-11-26 T D Kieu , C J Griffin

Monte Carlo simulations have boosted the numerical study of several different physical systems and in particular, the canonical ensemble has been especially useful because of the existence of easy and efficient relaxation algorithms…

Statistical Mechanics · Physics 2019-10-29 G. Palma , A. Riveros

We describe a Monte Carlo scheme which, in a single simulation, yields a measurement of the chemical potential of a crystalline solid. Within the isobaric ensemble, this immediately provides an estimate of the system free energy, with…

Statistical Mechanics · Physics 2015-06-11 Nigel B. Wilding , Peter Sollich

Monte Carlo techniques play a central role in statistical mechanics approaches for connecting macroscopic thermodynamic and kinetic properties to the electronic structure of a material. This paper describes the implementation of Monte Carlo…

Materials Science · Physics 2023-09-22 Brian Puchala , John C. Thomas , Anton Van der Ven

The unconstrained ensemble describes completely open systems whose control parameters are chemical potential, pressure, and temperature. For macroscopic systems with short-range interactions, thermodynamics prevents the simultaneous use of…

Statistical Mechanics · Physics 2021-06-30 Ivan Latella , Alessandro Campa , Lapo Casetti , Pierfrancesco Di Cintio , J. Miguel Rubi , Stefano Ruffo

Metropolis Monte Carlo simulation is a powerful tool for studying the equilibrium properties of matter. In complex condensed-phase systems, however, it is difficult to design Monte Carlo moves with high acceptance probabilities that also…

Statistical Mechanics · Physics 2014-05-27 Jerome P. Nilmeier , Gavin E. Crooks , David D. L. Minh , John D. Chodera

Monte Carlo computer simulations are virtually the only way to analyze the thermodynamic behavior of a system in a precise way. However, the various existing methods exhibit extreme differences in their efficiency, depending on model…

Statistical Mechanics · Physics 2011-07-05 Michael Bachmann

The Hamiltonian Monte Carlo (HMC) method allows sampling from continuous densities. Favorable scaling with dimension has led to wide adoption of HMC by the statistics community. Modern auto-differentiating software should allow more…

Computation · Statistics 2022-08-17 Ian Langmore , Michael Dikovsky , Scott Geraedts , Peter Norgaard , Rob von Behren

We introduce a quantum Monte Carlo method at finite temperature for interacting fermionic models in the canonical ensemble, where the conservation of the particle number is enforced. Although general thermodynamic arguments ensure the…

Statistical Mechanics · Physics 2017-10-19 Zhenjiu Wang , Fakher F. Assaad , Francesco Parisen Toldin

We describe a Monte Carlo procedure which allows sampling of the disjoint configuration spaces associated with crystalline and fluid phases, within a single simulation. The method utilises biased sampling techniques to enhance the…

Statistical Mechanics · Physics 2009-10-31 N. B. Wilding , A. D. Bruce

Monte Carlo simulations are performed in classical phase space for a one-dimensional quantum harmonic crystal. Symmetrization effects for spinless bosons and fermions are quantified. The algorithm is tested for a range of parameters against…

Quantum Physics · Physics 2019-04-25 Phil Attard

We present a Monte Carlo simulation technique by which the free energy of disordered systems can be computed directly. It is based on thermodynamic integration. The central idea is to construct an analytically solvable reference system from…

Statistical Mechanics · Physics 2015-05-14 Tanja Schilling , Friederike Schmid

Ab initio Monte Carlo simulations have been performed to determine the equilibrium properties of liquid lithium and lithium clusters at different temperatures. First-principles density-functional methods were employed to calculate the…

Materials Science · Physics 2007-05-23 Sanwu Wang , Steven J. Mitchell , Per Arne Rikvold

We use single-cluster Monte Carlo simulations to study the role of topological defects in the three-dimensional classical Heisenberg model on simple cubic lattices of size up to $80^3$. By applying reweighting techniques to time series…

High Energy Physics - Lattice · Physics 2009-10-22 Christian Holm , Wolfhard Janke

We study in this paper the melting transition of a crystal of fcc structure with the Lennard-Jones potential, by using isobaric-isothermal Monte Carlo simulations. Local and collective updates are sequentially used to optimize the…

Statistical Mechanics · Physics 2009-10-31 Liliana Gomez , Ariel Dobry , Hung Diep

The combination of continuum Many-Body Quantum physics and Monte Carlo methods provide a powerful and well established approach to first principles calculations for large systems. Replacing the exact solution of the problem with a…

Computational Physics · Physics 2009-10-01 J. R. Trail

Computational codes based on the Diffusion Monte Carlo method can be used to determine the quantum state of two-electron systems confined by external potentials of various nature and geometry. In this work, we show how the application of…

Chemical Physics · Physics 2021-02-24 Gaia Micca Longo , Carla Maria Coppola , Domenico Giordano , Savino Longo

We report microcanonical Monte Carlo simulations of melting and superheating of a generic, Lennard-Jones system starting from the crystalline phase. The isochoric curve, the melting temperature $T_m$ and the critical superheating…

Statistical Mechanics · Physics 2017-03-20 Sergio Davis , Gonzalo Gutiérrez

When properly tuned, Hamiltonian Monte Carlo scales to some of the most challenging high-dimensional problems at the frontiers of applied statistics, but when that tuning is suboptimal the performance leaves much to be desired. In this…

Methodology · Statistics 2016-04-05 Michael Betancourt
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