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Entropy 2017, 19(11), 571;

Transport Coefficients from Large Deviation Functions

Department of Chemistry, University of California, Berkeley, CA 94609, USA
Kavli Energy NanoScience Institute, Berkeley, CA 94609, USA
Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94609, USA
Author to whom correspondence should be addressed.
Received: 16 September 2017 / Revised: 18 October 2017 / Accepted: 19 October 2017 / Published: 25 October 2017
(This article belongs to the Special Issue Understanding Molecular Dynamics via Stochastic Processes)
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We describe a method for computing transport coefficients from the direct evaluation of large deviation functions. This method is general, relying on only equilibrium fluctuations, and is statistically efficient, employing trajectory based importance sampling. Equilibrium fluctuations of molecular currents are characterized by their large deviation functions, which are scaled cumulant generating functions analogous to the free energies. A diffusion Monte Carlo algorithm is used to evaluate the large deviation functions, from which arbitrary transport coefficients are derivable. We find significant statistical improvement over traditional Green–Kubo based calculations. The systematic and statistical errors of this method are analyzed in the context of specific transport coefficient calculations, including the shear viscosity, interfacial friction coefficient, and thermal conductivity. View Full-Text
Keywords: transport coefficients; diffusion Monte Carlo; large deviation function; molecular dynamics transport coefficients; diffusion Monte Carlo; large deviation function; molecular dynamics

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Gao, C.Y.; Limmer, D.T. Transport Coefficients from Large Deviation Functions. Entropy 2017, 19, 571.

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