Theory of Adaptive Optimization for Umbrella Sampling | Zendy

Soohyung Park | Zendy; Wonpil Im | Zendy

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Theory of Adaptive Optimization for Umbrella Sampling

Author(s) -

Soohyung Park,

Wonpil Im

Publication year - 2014

Publication title -

journal of chemical theory and computation

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.001

H-Index - 185

eISSN - 1549-9626

pISSN - 1549-9618

DOI - 10.1021/ct500504g

Subject(s) - umbrella sampling , replica , adaptive sampling , sampling (signal processing) , computer science , window (computing) , constant (computer programming) , mathematical optimization , mathematics , molecular dynamics , statistics , physics , monte carlo method , art , filter (signal processing) , visual arts , computer vision , programming language , operating system , quantum mechanics

We present a theory of adaptive optimization for umbrella sampling. With the analytical bias force constant obtained from the constrained thermodynamic length along the reaction coordinate, the windows are distributed to optimize the overlap between neighbors. Combining with the replica exchange method, we propose a method of adaptive window exchange umbrella sampling. The efficiency gain in sampling by the present method originates from the optimal window distribution, in which windows are concentrated to the region where the free energy is steep, as well as consequently improved random walk.

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