INQUIMAE   12526
INSTITUTO DE QUIMICA, FISICA DE LOS MATERIALES, MEDIOAMBIENTE Y ENERGIA
Unidad Ejecutora - UE
artículos
Título:
On the accurate estimation of free energies using the jarzynski equality
Autor/es:
SZRETTER, MARIA EUGENIA; RODRIGUEZ, DANIELA; BOUBETA, FERNANDO MARTÍN; BOECHI, LEONARDO; ARRAR, MEHRNOOSH; SUED, MARIELA
Revista:
JOURNAL OF COMPUTATIONAL CHEMISTRY
Editorial:
JOHN WILEY & SONS INC
Referencias:
Lugar: Hoboken, NJ; Año: 2018 vol. 40 p. 688 - 688
ISSN:
0192-8651
Resumen:
The Jarzynski equality is one of the most widely celebrated and scrutinized nonequilibrium work theorems, relating free energy to the external work performed in nonequilibrium transitions. In practice, the required ensemble average of the Boltzmann weights of infinite nonequilibrium transitions is estimated as a finite sample average, resulting in the so-called Jarzynski estimator, (Formula presented.). Alternatively, the second-order approximation of the Jarzynski equality, though seldom invoked, is exact for Gaussian distributions and gives rise to the Fluctuation-Dissipation estimator (Formula presented.). Here we derive the parametric maximum-likelihood estimator (MLE) of the free energy (Formula presented.) considering unidirectional work distributions belonging to Gaussian or Gamma families, and compare this estimator to (Formula presented.). We further consider bidirectional work distributions belonging to the same families, and compare the corresponding bidirectional (Formula presented.) to the Bennett acceptance ratio ((Formula presented.)) estimator. We show that, for Gaussian unidirectional work distributions, (Formula presented.) is in fact the parametric MLE of the free energy, and as such, the most efficient estimator for this statistical family. We observe that (Formula presented.) and (Formula presented.) perform better than (Formula presented.) and (Formula presented.), for unidirectional and bidirectional distributions, respectively. These results illustrate that the characterization of the underlying work distribution permits an optimal use of the Jarzynski equality. © 2018 Wiley Periodicals, Inc.