Dynamical tuning of the chemical potential in grand canonical Monte Carlo simulations to achieve target particle number

ORAL

Abstract

Here we discuss a method to adjust the chemical potential in grand canonical ensemble Monte Carlo simulations to achieve a target mean particle number that was recently introducted in Phys. Rev. E 105, 045311. The method applies a fictitious dynamics to the chemical potential that runs concurrently with the Monte Carlo sampling of the physical system. The resulting corrections to the chemical potential are made according to time-averaged estimates of the mean and variance of the particle number, with the latter being proportional to thermodynamic compressibility. We present results for a variety of tests, both within the context of classical and quantum Monte Carlo simulations, and in all cases find rapid convergence of the chemical potential---inexactness of the tuning algorithm contributes only a minor part of the total measurement error for realistic simulations.

*K. B. acknowledges support from the Center of Materials Theory as a part of the Computational Materials Science (CMS) program, funded by the U.S. Department of Energy, Office of Basic Energy Sciences. S. J., O. B., and R. T. S. acknowledge support from the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Award Number DE-SC0022311. C. M. acknowledges support by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Department of Energy Computational Graduate Fellowship under Award Number DESC0020347. B. C.-S. was funded by a U.C. National Laboratory In-Residence Graduate Fellowship through the U.C. National Laboratory Fees Research Program.

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Publication: Phys. Rev. E 105, 045311

Presenters

  • Benjamin Cohen-Stead

    • University of Tennessee Knoxville
    • University of Tennessee, Knoxville

Authors

  • Benjamin Cohen-Stead

    • University of Tennessee Knoxville
    • University of Tennessee, Knoxville

  • Cole M Miles

    • Cornell University

  • Owen Bradley

    • University of California, Davis

  • Steven S Johnston

    • University of Tennessee

  • Richard T Scalettar

    • University of California, Davis

  • Kipton M Barros

    • Los Alamos Natl Lab
    • Theoretical Division and CNLS, Los Alamos National Laboratory