Examining sharp restart in a Monte Carlo method for the linearized Poisson–Boltzmann equation

Thrasher W. John () and Mascagni Michael ()
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Thrasher W. John: Department of Computer Science, Florida State University, Tallahassee, FL 32306-4530, USA
Mascagni Michael: Department of Computer Science, Florida State University, Tallahassee, FL 32306-4530; and National Institute of Standards & Technology, ITL, Gaithersburg, MD 20899-8910, USA

Monte Carlo Methods and Applications, 2020, vol. 26, issue 3, 223-244

Abstract: It has been shown that when using a Monte Carlo algorithm to estimate the electrostatic free energy of a biomolecule in a solution, individual random walks can become entrapped in the geometry. We examine a proposed solution, using a sharp restart during the Walk-on-Subdomains step, in more detail. We show that the point at which this solution introduces significant bias is related to properties intrinsic to the molecule being examined. We also examine two potential methods of generating a sharp restart point and show that they both cause no significant bias in the examined molecules and increase the stability of the run times of the individual walks.

Keywords: Monte Carlo; walk on subdomains; Brownian motion; Poisson–Boltzmann; walk entrapment (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1515/mcma-2020-2069

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