Characterizing the Slow Dynamics of the Swap Monte Carlo Algorithm
Kumpei Shiraishi1, Ludovic Berthier1,2
1Laboratoire Charles Coulomb (L2C), Université de Montpellier, CNRS, 34095 Montpellier, France.
The Journal of Physical Chemistry. B
|December 1, 2024
Summary
The swap Monte Carlo algorithm accelerates supercooled liquid simulations but alters dynamics. It reduces dynamic heterogeneity, suggesting local kinetic constraints are key to slow liquid dynamics.
Area of Science:
- Condensed Matter Physics
- Computational Chemistry
- Statistical Mechanics
Background:
- Supercooled liquids exhibit slow dynamics and dynamic heterogeneity.
- The swap Monte Carlo (SMC) algorithm accelerates simulations using nonphysical moves.
- Understanding the impact of SMC on liquid dynamics is crucial.
Purpose of the Study:
- Analyze the slow dynamics generated by SMC in supercooled liquids at low temperatures.
- Compare SMC dynamics to local Monte Carlo (LMC) dynamics.
- Investigate the effect of swap moves on dynamic heterogeneity and kinetic constraints.
Main Methods:
- Simulated two glass-forming models using swap Monte Carlo at very low temperatures.
- Analyzed single-particle and collective dynamics.
- Quantified dynamic heterogeneity and compared static and dynamic fluctuations.
Main Results:
- SMC dynamics are qualitatively distinct from LMC dynamics.
- SMC significantly suppresses dynamic heterogeneity at both single-particle and collective levels.
- Swap moves reduce local kinetic constraints, leading to near-Gaussian, diffusive dynamics.
Conclusions:
- SMC algorithms drastically alter the nature of slow dynamics in supercooled liquids.
- Swap moves effectively reduce local kinetic constraints, simplifying dynamics.
- Further advancements in simulating dense liquids may require collective or driven algorithms beyond SMC.
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