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Funnel hopping Monte Carlo: An efficient method to overcome broken ergodicity

Finkler, Jonas A. and Goedecker, Stefan. (2020) Funnel hopping Monte Carlo: An efficient method to overcome broken ergodicity. Journal of Clinical Physics, 152 (16). p. 164106.

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Abstract

Monte Carlo simulations are a powerful tool to investigate the thermodynamic properties of atomic systems. In practice, however, sampling of the complete configuration space is often hindered by high energy barriers between different regions of configuration space, which can make ergodic sampling completely infeasible within accessible simulation times. Although several extensions to the conventional Monte Carlo scheme have been developed, which enable the treatment of such systems, these extensions often entail substantial computational cost or rely on the harmonic approximation. In this work, we propose an exact method called Funnel Hopping Monte Carlo (FHMC) that is inspired by the ideas of smart darting but is more efficient. Gaussian mixtures are used to approximate the Boltzmann distribution around local energy minima, which are then used to propose high quality Monte Carlo moves that enable the Monte Carlo simulation to directly jump between different funnels. We demonstrate the method's performance on the example of the 38 as well as the 75 atom Lennard-Jones clusters, which are well known for their double funnel energy landscapes that prevent ergodic sampling with conventional Monte Carlo simulations. By integrating FHMC into the parallel tempering scheme, we were able to reduce the number of steps required significantly until convergence of the simulation.
Faculties and Departments:05 Faculty of Science > Departement Physik > Physik > Physik (Goedecker)
UniBasel Contributors:Goedecker, Stefan
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:American Institute of Physics
ISSN:0021-9606
e-ISSN:1089-7690
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
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Last Modified:23 Dec 2020 11:30
Deposited On:23 Dec 2020 11:30

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