skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Towards an optimal flow: Density-of-states-informed replica-exchange simulations

Abstract

Here we learn that replica exchange (RE) is one of the most popular enhanced-sampling simulations technique in use today. Despite widespread successes, RE simulations can sometimes fail to converge in practical amounts of time, e.g., when sampling around phase transitions, or when a few hard-to-find configurations dominate the statistical averages. We introduce a generalized RE scheme, density-of-states-informed RE, that addresses some of these challenges. The key feature of our approach is to inform the simulation with readily available, but commonly unused, information on the density of states of the system as the RE simulation proceeds. This enables two improvements, namely, the introduction of resampling moves that actively move the system towards equilibrium and the continual adaptation of the optimal temperature set. As a consequence of these two innovations, we show that the configuration flow in temperature space is optimized and that the overall convergence of RE simulations can be dramatically accelerated.

Authors:
 [1];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1239374
Alternate Identifier(s):
OSTI ID: 1225240
Report Number(s):
LA-UR-15-23605
Journal ID: ISSN 0031-9007; PRLTAO
Grant/Contract Number:  
AC52-06NA25396
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Physical Review Letters
Additional Journal Information:
Journal Volume: 115; Journal Issue: 19; Journal ID: ISSN 0031-9007
Publisher:
American Physical Society (APS)
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS; 97 MATHEMATICS AND COMPUTING

Citation Formats

Vogel, Thomas, and Perez, Danny. Towards an optimal flow: Density-of-states-informed replica-exchange simulations. United States: N. p., 2015. Web. doi:10.1103/PhysRevLett.115.190602.
Vogel, Thomas, & Perez, Danny. Towards an optimal flow: Density-of-states-informed replica-exchange simulations. United States. doi:10.1103/PhysRevLett.115.190602.
Vogel, Thomas, and Perez, Danny. Thu . "Towards an optimal flow: Density-of-states-informed replica-exchange simulations". United States. doi:10.1103/PhysRevLett.115.190602. https://www.osti.gov/servlets/purl/1239374.
@article{osti_1239374,
title = {Towards an optimal flow: Density-of-states-informed replica-exchange simulations},
author = {Vogel, Thomas and Perez, Danny},
abstractNote = {Here we learn that replica exchange (RE) is one of the most popular enhanced-sampling simulations technique in use today. Despite widespread successes, RE simulations can sometimes fail to converge in practical amounts of time, e.g., when sampling around phase transitions, or when a few hard-to-find configurations dominate the statistical averages. We introduce a generalized RE scheme, density-of-states-informed RE, that addresses some of these challenges. The key feature of our approach is to inform the simulation with readily available, but commonly unused, information on the density of states of the system as the RE simulation proceeds. This enables two improvements, namely, the introduction of resampling moves that actively move the system towards equilibrium and the continual adaptation of the optimal temperature set. As a consequence of these two innovations, we show that the configuration flow in temperature space is optimized and that the overall convergence of RE simulations can be dramatically accelerated.},
doi = {10.1103/PhysRevLett.115.190602},
journal = {Physical Review Letters},
issn = {0031-9007},
number = 19,
volume = 115,
place = {United States},
year = {2015},
month = {11}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 4 works
Citation information provided by
Web of Science

Save / Share:

Works referenced in this record:

New approach to Monte Carlo calculation of the free energy: Method of expanded ensembles
journal, February 1992

  • Lyubartsev, A. P.; Martsinovski, A. A.; Shevkunov, S. V.
  • The Journal of Chemical Physics, Vol. 96, Issue 3
  • DOI: 10.1063/1.462133

Exchange Monte Carlo Method and Application to Spin Glass Simulations
journal, June 1996

  • Hukushima, Koji; Nemoto, Koji
  • Journal of the Physical Society of Japan, Vol. 65, Issue 6
  • DOI: 10.1143/JPSJ.65.1604

Parallel tempering: Theory, applications, and new perspectives
journal, January 2005

  • Earl, David J.; Deem, Michael W.
  • Physical Chemistry Chemical Physics, Vol. 7, Issue 23
  • DOI: 10.1039/b509983h

Parallel tempering algorithm for conformational studies of biological molecules
journal, December 1997


A biased Monte Carlo scheme for zeolite structure solution
journal, January 1999

  • Falcioni, Marco; Deem, Michael W.
  • The Journal of Chemical Physics, Vol. 110, Issue 3
  • DOI: 10.1063/1.477812

Prediction of absolute crystal-nucleation rate in hard-sphere colloids
journal, February 2001

  • Auer, Stefan; Frenkel, Daan
  • Nature, Vol. 409, Issue 6823
  • DOI: 10.1038/35059035

Efficient, Multiple-Range Random Walk Algorithm to Calculate the Density of States
journal, March 2001


Escaping free-energy minima
journal, September 2002

  • Laio, A.; Parrinello, M.
  • Proceedings of the National Academy of Sciences, Vol. 99, Issue 20
  • DOI: 10.1073/pnas.202427399

Statistical-Temperature Monte Carlo and Molecular Dynamics Algorithms
journal, August 2006


Molecular Dynamics in the Multicanonical Ensemble: Equivalence of Wang–Landau Sampling, Statistical Temperature Molecular Dynamics, and Metadynamics
journal, April 2014

  • Junghans, Christoph; Perez, Danny; Vogel, Thomas
  • Journal of Chemical Theory and Computation, Vol. 10, Issue 5
  • DOI: 10.1021/ct500077d

Adaptive biasing force method for scalar and vector free energy calculations
journal, April 2008

  • Darve, Eric; Rodríguez-Gómez, David; Pohorille, Andrew
  • The Journal of Chemical Physics, Vol. 128, Issue 14
  • DOI: 10.1063/1.2829861

Dynamical Approach to Temperature
journal, February 1997


Configurational temperature: Verification of Monte Carlo simulations
journal, October 1998

  • Butler, B. D.; Ayton, Gary; Jepps, Owen G.
  • The Journal of Chemical Physics, Vol. 109, Issue 16
  • DOI: 10.1063/1.477301

Some comments on Monte Carlo and molecular dynamics methods
journal, December 2013


Microcanonical entropy inflection points: Key to systematic understanding of transitions in finite systems
journal, July 2011


Replica exchange and expanded ensemble simulations as Gibbs sampling: Simple improvements for enhanced mixing
journal, November 2011

  • Chodera, John D.; Shirts, Michael R.
  • The Journal of Chemical Physics, Vol. 135, Issue 19
  • DOI: 10.1063/1.3660669

Optimal allocation of replicas in parallel tempering simulations
journal, January 2005

  • Rathore, Nitin; Chopra, Manan; de Pablo, Juan J.
  • The Journal of Chemical Physics, Vol. 122, Issue 2
  • DOI: 10.1063/1.1831273

Feedback-optimized parallel tempering Monte Carlo
journal, March 2006

  • Katzgraber, Helmut G.; Trebst, Simon; Huse, David A.
  • Journal of Statistical Mechanics: Theory and Experiment, Vol. 2006, Issue 03
  • DOI: 10.1088/1742-5468/2006/03/P03018

Optimized parallel tempering simulations of proteins
journal, May 2006

  • Trebst, Simon; Troyer, Matthias; Hansmann, Ulrich H. E.
  • The Journal of Chemical Physics, Vol. 124, Issue 17
  • DOI: 10.1063/1.2186639

Make Life Simple: Unleash the Full Power of the Parallel Tempering Algorithm
journal, September 2008


An embedded-atom potential for the Cu–Ag system
journal, May 2006

  • Williams, P. L.; Mishin, Y.; Hamilton, J. C.
  • Modelling and Simulation in Materials Science and Engineering, Vol. 14, Issue 5
  • DOI: 10.1088/0965-0393/14/5/002

Generalized Replica Exchange Method
journal, June 2010

  • Kim, Jaegil; Keyes, Thomas; Straub, John E.
  • The Journal of Chemical Physics, Vol. 132, Issue 22
  • DOI: 10.1063/1.3432176

Generic, Hierarchical Framework for Massively Parallel Wang-Landau Sampling
journal, May 2013


Scalable replica-exchange framework for Wang-Landau sampling
journal, August 2014