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The Journal of Chemical Physics· 2026Q1

Efficient searches for low-energy structures in clusters with thousands of particles: Application to the Thomson problem

Paolo Amore, David J. Wales

Short summary

A new algorithm efficiently finds low-energy structures in spherical particle clusters of thousands, improving upon previous Thomson problem solutions, especially for larger systems.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Proposes an algorithm for efficient low-energy structure searches in large spherical particle clusters.
  • Uses symmetric seeds and size-range searches to propagate information through configuration space.
  • Substantially improves Thomson problem solutions, especially for larger system sizes.
  • Newly characterized defect patterns may inform structure prediction for spherical topology systems.

AI-generated from the title and abstract; the full text is not read.

Abstract

We propose an algorithm for identifying low-energy minima in systems containing thousands of particles, at moderate computational cost. We focus on spherical crystals, in which particles form ordered structures on the surface of a sphere. Our method uses symmetric seed configurations, or known structures, to initialize searches across contiguous ranges of system sizes. Newly identified minima are then used to guide searches at neighboring sizes, allowing information to propagate efficiently through configuration space. We have tested this approach on the Thomson problem, one of the few interacting-particle systems for which global optimization has been considered for systems of this size. We substantially improve on many previous solutions, particularly at larger system sizes, where systematic global optimization is computationally expensive. Since favorable packings for the Thomson problem are reflected in systems spanning atomistic to mesoscopic length scales, the newly characterized defect patterns may inform structure prediction for a broad range of problems with spherical topology.

The authors' abstract, as published at the source. The Journal of Chemical Physics, 2026 · DOI ↗

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Field: Numerical Analysis

Numerical AnalysisMathematics