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  • Letter
  • Open Access

Global minima optimization via mirror-rotation transformation

Yi-Rong Liu1,*, Yan Jiang2, Shuai Jiang1, Chun-Yu Wang1, and Teng Huang3

  • 1School of Information Science and Technology, University of Science and Technology of China, Hefei, Anhui 230026, China
  • 2School of Vanadium and Titanium, Panzhihua University, Panzhihua, Sichuan 617000, China
  • 3Laboratory of Atmospheric Physico-Chemistry, Anhui Institute of Optics & Fine Mechanics, Chinese Academy of Sciences, Hefei, Anhui 230031, China

  • *yrliu@ustc.edu.cn
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Phys. Rev. Research 4, L042045 – Published 16 December, 2022

DOI: https://doi.org/10.1103/PhysRevResearch.4.L042045

Abstract

Rapidly finding low-energy structures on high-dimensional potential energy surfaces remains a challenging problem for cluster science. We present a fast optimization method for structure prediction named mirror-rotation searching, which is inspired by the idea of symmetry and conservation. Our search algorithm can quickly converge to the minima of energy valley by continuously performing mirror-rotation transformation on the cluster, and we introduce the term vaminima to describe these minima. For the selected Lennard-Jones cluster of size N≤150, convergence to a vaminima on average takes 413 relaxations, and finding fullerene C60 from a random initial structure is 49-fold faster than the traditional genetic algorithm. The approach is general and flexible and can greatly improve the search efficiency of unbiased global optimization algorithms and be applied to different kinds of problems, such as molecular structure search, crystal structure prediction, and protein folding.

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Phys. Rev. Research 4, L042045– Published 16 December, 2022
  • Received 16 July 2022
  • Accepted 27 November 2022
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