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Characterization and efficient Monte Carlo sampling of disordered microphases.

Mingyuan Zheng1, Patrick Charbonneau1

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This study characterizes disordered microphases in systems with competing interactions. Advanced Monte Carlo methods show specific sampling schemes are most efficient for different structures, aiding simulation efficiency.

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Area of Science:

  • Materials Science
  • Computational Chemistry
  • Statistical Physics

Background:

  • Systems with competing short-range attractive and long-range repulsive (SALR) interactions exhibit complex disordered microphases.
  • These microphases, including cluster, void cluster, and percolated fluids, display heterogeneous and slow relaxation dynamics.
  • The relationship between these structures and efficient configurational sampling remains poorly understood.

Purpose of the Study:

  • To thoroughly characterize the disordered microphases of a schematic SALR model.
  • To develop structural relaxation functions tailored to each distinct microphase regime.
  • To assess the sampling efficiency of advanced Monte Carlo methods for these systems.

Main Methods:

  • Characterization of disordered microphases in a schematic SALR model.
  • Devising structural relaxation functions specific to cluster, void cluster, and percolated fluid regimes.
  • Assessing the computational efficiency of Virtual-Move Monte Carlo (VMMC), Aggregation-Volume-Bias Monte Carlo (AVBMC), and Event-Chain Monte Carlo (ECMC) sampling schemes.

Main Results:

  • A combination of VMMC and AVBMC sampling is computationally most efficient for cluster fluids.
  • Event-Chain Monte Carlo (ECMC) becomes relatively more efficient as system density increases.
  • The study provides a comprehensive description of the equilibrium disordered phase and dynamical benchmarks.

Conclusions:

  • Different microphase structures in SALR systems necessitate tailored sampling strategies for efficient simulation.
  • The findings offer valuable insights into the behavior of microphase-forming systems and guide the selection of appropriate computational methods.
  • This work establishes dynamical benchmarks for evaluating advanced sampling techniques in complex fluid systems.