Unbiased Global Optimization of Lennard-Jones Clusters forN≤201Using the Conformational Space Annealing Method

2003/07/29 by Julian Lee, In-Ho Lee, In‐Ho Lee +1 · 7 citations
Materials Science · Physics and Astronomy · #Advanced Chemical Physics Studies #Machine Learning in Materials Science #Nonlinear Optical Materials Research #cond-mat.stat-mech

paper · pdf · doi:10.1103/physrevlett.91.080201

revtex, 4 pages, 2 figures. Physical Review Letters, in press

arxiv created 2003/07/29 · openalex publication_date 2003/08/21 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28

Abstract

We apply the conformational space annealing method to the Lennard-Jones clusters and find all known lowest energy configurations up to 201 atoms, without using extra information of the problem such as the structures of the known global energy minima. In addition, the robustness of the algorithm with respect to the randomness of initial conditions of the problem is demonstrated by ten successful independent runs up to 183 atoms. Our results indicate that this method is a general and yet efficient global optimization algorithm applicable to many systems.

Citations

• Global Optimization by Basin-Hopping and the Lowest Energy Structures of Lennard-Jones Clusters Containing up to 110 Atoms
• On the limited memory BFGS method for large scale optimization
• Tetrahedral global minimum for the 98-atom Lennard-Jones cluster

Cited by

• Direct band gap carbon superlattices with efficient optical transition
• Coordination-driven magic numbers in protonated argon clusters
• Rich Ground-State Chemical Ordering in Nanoparticles: Exact Solution of a Model for Ag-Au Clusters
• Semimetallic carbon allotrope with a topological nodal line in mixed sp2-sp3 bonding networks
• Basin hopping with occasional jumping
• Continuous extremal optimization for Lennard-Jones clusters
• Relaxation dynamics and interrupted coarsening in irrationally frustrated superconducting arrays
• Conformational space annealing and an off-lattice frustrated model protein