A “fast growth” method of computing free energy differences

By David A. Hendrix, Christopher Jarzynski. 2001

149 citations recorded by the source corpus.

Subfields: Condensed Matter Physics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/8a9956a9f1b91885260dadec9923d92619d09bb0

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In Condensed Matter Physics

In Statistical and Nonlinear Physics

Citations in the corpus

Estimating Ratios of Normalizing Constants Using Linked Importance Sampling (2005, methodology): “As shown by Jarzynski (1997, 2001), and later independently by myself (Neal 2001), an estimate for Z1/Z0 using intermediate distributions as in equation (3) will be exactly unbiased if each of the ratios Zηj+1/Zηj is estimated using the simple importance sampling estimate of equation (2) with N =…”
Fluctuation Relations for Diffusion Processes (2007, methodology): “9) in which it has become a tool to compute the differences between free energies of equilibrium states from nonequilibrium processes [45, 17, 71, 72].”
Nonequilibrium fluctuations in small systems: From physics to biology (2007, background): “In numerical simulations the question about the best strategy for free energy recovery has been considered in several papers [111, 112, 113, 102].”
QM/MM Methods for Biological Systems (2006, background): “This relation has become the foundation for “fast-growth” [351] or “multiple-steering” [349, 352, 353] simulations, in which irreversible-work values from deliberately non-adiabatic switching processes are accumulated and exponentially averaged according to Eq.”
Stochastic thermodynamics, fluctuation theorems and molecular machines (2012, background): “Such a result has previously been expected [69, 70] or justified by invoking arguments based on the central limit theorem [71].”
Fluctuation-dissipation: Response theory in statistical physics (2008, background): “However it has been shown [264,265] that a range of τ exists where the estimate is reliable.”