Gravitational smoothing as a global optimization strategy

An optimization scheme for atomic cluster structures, based on exaggerating the importance of the gravitational force, is introduced. Results are presented for calculations on Lennard‐Jones clusters of 13, 38, and 55 atoms, and the 13‐atom Morse cluster. © 2002 Wiley Periodicals, Inc. J Comput Chem 11: 1100–1103, 2002

[1]  Richard H. Byrd,et al.  A Global Optimization Strategy for Predicting -helical Protein Tertiary Structure , 2000, Comput. Chem..

[2]  William H. Press,et al.  Numerical recipes , 1990 .

[3]  J. Straub,et al.  Global energy minimum searches using an approximate solution of the imaginary time Schroedinger equation , 1993 .

[4]  Thomas A. Weber,et al.  Inherent structure theory of liquids in the hard‐sphere limit , 1985 .

[5]  P. Kollman,et al.  Encyclopedia of computational chemistry , 1998 .

[6]  C. J. Tsai,et al.  Use of an eigenmode method to locate the stationary points on the potential energy surfaces of selected argon and water clusters , 1993 .

[7]  Frank H. Stillinger,et al.  Cluster optimization simplified by interaction modification , 1990 .

[8]  M. R. Hoare,et al.  Morphology and statistical statics of simple microclusters , 1983 .

[9]  Jonathan P. K. Doye,et al.  TOPICAL REVIEW: The effect of the range of the potential on the structure and stability of simple liquids: from clusters to bulk, from sodium to ? , 1996 .

[10]  M. Hoare,et al.  Physical cluster mechanics: Statics and energy surfaces for monatomic systems , 1971 .

[11]  J. Doll,et al.  Quantum annealing: A new method for minimizing multidimensional functions , 1994, chem-ph/9404003.

[12]  F. Stillinger,et al.  A strategy for finding classes of minima on a hypersurface: implications for approaches to the protein folding problem. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[13]  P. Pardalos,et al.  Optimization in computational chemistry and molecular biology : local and global approaches , 2000 .

[14]  D. Wales,et al.  How the range of pair interactions governs features of multidimensional potentials , 1990 .

[15]  R Elber,et al.  Novel methods for molecular dynamics simulations. , 1996, Current opinion in structural biology.

[16]  B. Berne,et al.  Novel methods of sampling phase space in the simulation of biological systems. , 1997, Current opinion in structural biology.

[17]  R. Berry.  POTENTIAL SURFACES AND DYNAMICS : WHAT CLUSTERS TELL US , 1993 .

[18]  F. Stillinger,et al.  Predicting polypeptide and protein structures from amino acid sequence: Antlion method applied to melittin , 1993 .

[19]  J. Doye,et al.  THE DOUBLE-FUNNEL ENERGY LANDSCAPE OF THE 38-ATOM LENNARD-JONES CLUSTER , 1998, cond-mat/9808265.

[20]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[21]  J. Doye,et al.  Global Optimization by Basin-Hopping and the Lowest Energy Structures of Lennard-Jones Clusters Containing up to 110 Atoms , 1997, cond-mat/9803344.

[22]  J. Doye,et al.  The effect of the range of the potential on the structures of clusters , 1995 .

[23]  Jianpeng Ma,et al.  Erratum: Simulated annealing using the classical density distribution [J. Chem. Phys. 101, 533 (1994)] , 1995 .

[24]  H. Scheraga,et al.  Global optimization of clusters, crystals, and biomolecules. , 1999, Science.

[25]  Straub,et al.  Generalized simulated annealing algorithms using Tsallis statistics: Application to conformational optimization of a tetrapeptide. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.