Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/178684
Title: Monte Carlo simulations in the unconstrained ensemble
Author: Latella, Ivan
Campa, Alessandro
Casetti, L.
Di Cintio, Pierfrancesco
Rubí Capaceti, José Miguel
Ruffo, S.
Keywords: Mètode de Montecarlo
Partícules (Matèria)
Estadística matemàtica
Monte Carlo method
Particles
Mathematical statistics
Issue Date: 21-Jun-2021
Publisher: American Physical Society
Abstract: 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 these intensive variables as control parameters, because they are not independent and cannot account for the system size. When the range of the interactions is comparable with the size of the system, however, these variables are not truly intensive and may become independent, so equilibrium states defined by the values of these parameters may exist. Here, we derive a Monte Carlo algorithm for the unconstrained ensemble and show that simulations can be performed using chemical potential, pressure, and temperature as control parameters. We illustrate the algorithm by applying it to physical systems where either the system has long-range interactions or is confined by external conditions. The method opens up an avenue for the simulation of completely open systems exchanging heat, work, and matter with the environment.
Note: Reproducció del document publicat a: https://doi.org/10.1103/PhysRevE.103.L061303
It is part of: Physical Review e, 2021, vol. 103, num. 6, p. L061303
URI: http://hdl.handle.net/2445/178684
Related resource: https://doi.org/10.1103/PhysRevE.103.L061303
ISSN: 2470-0045
Appears in Collections:Publicacions de projectes de recerca finançats per la UE
Articles publicats en revistes (Física de la Matèria Condensada)

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