Equilibrium free energies from nonequilibrium measurements using maximum-likelihood methods.

We present a maximum likelihood argument for the Bennett acceptance ratio method, and derive a simple formula for the variance of free energy estimates generated using this method. This derivation of the acceptance ratio method, using a form of logistic regression, a common statistical technique, allows us to shed additional light on the underlying physical and statistical properties of the method. For example, we demonstrate that the acceptance ratio method yields the lowest variance for any estimator of the free energy which is unbiased in the limit of large numbers of measurements.

[1]  E. L. Lehmann,et al.  Theory of point estimation , 1950 .

[2]  R. Zwanzig High‐Temperature Equation of State by a Perturbation Method. I. Nonpolar Gases , 1954 .

[3]  J. Anderson Separate sample logistic discrimination , 1972 .

[4]  Charles H. Bennett,et al.  Efficient estimation of free energy differences from Monte Carlo data , 1976 .

[5]  R. Pyke,et al.  Logistic disease incidence models and case-control studies , 1979 .

[6]  P. McCullagh,et al.  Generalized Linear Models , 1992 .

[7]  Peter A. Kollman,et al.  The lag between the Hamiltonian and the system configuration in free energy perturbation calculations , 1989 .

[8]  T. Straatsma,et al.  Multiconfiguration thermodynamic integration , 1991 .

[9]  C. Jarzynski Nonequilibrium Equality for Free Energy Differences , 1996, cond-mat/9610209.

[10]  Peter T. Cummings,et al.  Precision and accuracy of staged free-energy perturbation methods for computing the chemical potential by molecular simulation , 1998 .

[11]  Xiao-Li Meng,et al.  Simulating Normalizing Constants: From Importance Sampling to Bridge Sampling to Path Sampling , 1998 .

[12]  T. Schaefer,et al.  Instantons in QCD , 1998 .

[13]  D. Kofke,et al.  Optimal intermediates in staged free energy calculations , 1999 .

[14]  G. Crooks Path-ensemble averages in systems driven far from equilibrium , 1999, cond-mat/9908420.

[15]  David A. Kofke,et al.  Accuracy of free-energy perturbation calculations in molecular simulation. II. Heuristics , 2001 .

[16]  David A. Kofke,et al.  Accuracy of free-energy perturbation calculations in molecular simulation. I. Modeling , 2001 .

[17]  C. Jarzynski,et al.  A “fast growth” method of computing free energy differences , 2001 .

[18]  Thomas B Woolf,et al.  Theory of a systematic computational error in free energy differences. , 2002, Physical review letters.

[19]  I. Tinoco,et al.  Equilibrium Information from Nonequilibrium Measurements in an Experimental Test of Jarzynski's Equality , 2002, Science.

[20]  G. Hummer Fast-growth Thermodynamic Integration∶ Results for Sodium Ion Hydration , 2002 .

[21]  Daniel M. Zuckerman,et al.  Overcoming finite-sampling errors in fast-switching free-energy estimates: extrapolative analysis of a molecular system , 2002 .

[22]  David A. Kofke,et al.  Appropriate methods to combine forward and reverse free-energy perturbation averages , 2003 .

[23]  D. Ruppert The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .

[24]  P. Cummings,et al.  Fluid phase equilibria , 2005 .