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Diffusion in periodic potentials with path integral hyperdynamics.

T Ikonen1, M D Khandkar, L Y Chen

  • 1Department of Applied Physics and Centre of Excellence in Computational Nanoscience (COMP), Aalto University School of Science, P.O. Box 11000, FI-00076 Aalto, Espoo, Finland.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|September 21, 2011
PubMed
Summary
This summary is machine-generated.

Stochastic Path Integral Hyperdynamics (PIHD) enhances rare event transitions but has optimal bias force due to sampling errors. PIHD also works for driven systems, though with modest speedups.

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Area of Science:

  • Statistical Mechanics
  • Computational Chemistry
  • Physical Chemistry

Background:

  • Brownian motion in periodic potentials is a key model for rare event dynamics.
  • Stochastic Path Integral Hyperdynamics (PIHD) is a novel method for accelerating simulations.
  • Understanding the efficiency and limitations of PIHD is crucial for its application.

Purpose of the Study:

  • To evaluate the performance of the stochastic path integral hyperdynamics (PIHD) scheme.
  • To investigate PIHD's effectiveness in enhancing transition rates for rare events.
  • To explore PIHD's behavior in driven systems and its comparison with molecular dynamics (MD).

Main Methods:

  • Simulating Brownian particle diffusion in 1D periodic potentials.
  • Applying PIHD to accelerate rare event transitions under high friction and low temperature.
  • Analyzing the boost factor relative to molecular dynamics (MD) as a function of bias force.
  • Investigating PIHD with parallel resampling for systems driven by an external AC force.

Main Results:

  • The boost factor for PIHD is not monotonic and shows an optimal maximum due to finite path sampling errors.
  • PIHD performance can be sensitive to the choice of numerical integration algorithm.
  • No stochastic resonance was observed in the driven system.
  • PIHD provided modest speedups for the driven system due to the simplicity of the dynamics.

Conclusions:

  • PIHD is a promising method for enhancing rare event simulations but requires careful tuning of the bias force.
  • The method's efficiency depends on the system's complexity and the chosen numerical algorithms.
  • PIHD can be applied to driven systems, offering a way to explore multiple bias values, albeit with limited acceleration.