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Parallel random tunneling algorithm for structural optimization of Lennard-Jones clusters up to N=330.
Xueguang Shao1, Haiyan Jiang, Wensheng Cai
1Department of Chemistry, University of Science and Technology of China, Hefei, Anhui, 230026, PR China. xshao@ustc.edu.cn
Journal of Chemical Information and Computer Sciences
|January 27, 2004
Summary
A parallel random tunneling algorithm (PRTA) efficiently finds global minima for Lennard-Jones atomic clusters. This method successfully optimizes clusters up to size 330, revealing new structures.
Area of Science:
- Computational chemistry
- Materials science
- Algorithm development
Background:
- Global optimization of atomic clusters is computationally challenging.
- Lennard-Jones (LJ) clusters are a standard benchmark for optimization algorithms.
Purpose of the Study:
- To develop and apply an efficient parallel algorithm for global optimization of LJ atomic clusters.
- To locate global minima for LJ clusters of various sizes, including previously unstudied ranges.
Main Methods:
- Derivation of the random tunneling algorithm (RTA) from the TRUST algorithm.
- Parallelization of RTA using an island parallel paradigm.
- Incorporation of angular moving techniques and an improved seeding strategy.
Main Results:
- Successfully located all global minima for LJ clusters up to size 200.
- Applied an improved PRTA to optimize larger clusters (LJ151-LJ309).
- Provided novel optimized structures for LJ309-330 clusters.
Conclusions:
- The PRTA is a highly effective method for global optimization of LJ atomic clusters.
- The algorithm's scalability allows for the study of larger and more complex atomic systems.
- New structural insights were gained for specific LJ cluster sizes.
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