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Free energy surface reconstruction from umbrella samples using Gaussian process regression

Stecher, T and Bernstein, N and Csányi, G Free energy surface reconstruction from umbrella samples using Gaussian process regression. (Unpublished)

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Abstract

We demonstrate how the Gaussian process regression approach can be used to efficiently reconstruct free energy surfaces from umbrella sampling simulations. By making a prior assumption of smoothness and taking account of the sampling noise in a consistent fashion, we achieve a significant improvement in accuracy over the state of the art in two or more dimensions or, equivalently, a significant cost reduction to obtain the free energy surface within a prescribed tolerance in both regimes of spatially sparse data and short sampling trajectories. Stemming from its Bayesian interpretation the method provides meaningful error bars without significant additional computation. A software implementation is made available on www.libatoms.org.

Item Type: Article
Uncontrolled Keywords: cond-mat.stat-mech cond-mat.stat-mech
Subjects: UNSPECIFIED
Divisions: Div C > Applied Mechanics
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 18:59
Last Modified: 21 Sep 2017 01:35
DOI: