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Generalized simulated tempering for exploring strong phase transitions.

Jaegil Kim1, John E Straub

  • 1Department of Chemistry, Boston University, Boston, Massachusetts 02215, USA. jaegilkim89@gmail.com

The Journal of Chemical Physics
|October 26, 2010
PubMed
Summary
This summary is machine-generated.

A new simulation tempering algorithm efficiently explores first-order phase transitions. This method enhances sampling for systems with hysteresis, like spin models, by transforming unstable states and smoothly joining phases.

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Area of Science:

  • Computational Physics
  • Statistical Mechanics

Background:

  • First-order phase transitions often exhibit complex behavior like backbending.
  • Exploring these transitions requires advanced simulation techniques to overcome energy barriers.

Purpose of the Study:

  • To propose an extended simulation tempering algorithm for enhanced exploration of first-order phase transitions.
  • To address challenges in sampling systems with significant hysteresis and metastable states.

Main Methods:

  • A guided Markov process in auxiliary parameter space combining Tsallis-weight ensemble simulations.
  • Transforming unstable/metastable states into stable ones for canonical ensembles.
  • Adaptive updating of biasing weights for rapid convergence and optimal parameter selection.

Main Results:

  • Demonstrated accelerated tunneling transitions and comprehensive sampling of phase-coexistent states.
  • Successfully applied to systems with strong hysteresis, including Potts and Ising spin models and a Lennard-Jones cluster.
  • The algorithm effectively smooths transitions between ordered and disordered phases.

Conclusions:

  • The proposed simulation tempering extension is highly effective for studying first-order phase transitions.
  • This method provides a robust approach for simulating systems with hysteresis and complex energy landscapes.