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Kinetic Transition Networks for the Thomson Problem and Smale's Seventh Problem.
Mehta, Dhagash; Chen, Jianxu; Chen, Danny Z; Kusumaatmaja, Halim; Wales, David J.
Afiliação
  • Mehta D; Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, Indiana 46556, USA.
  • Chen J; Centre for the Subatomic Structure of Matter, Department of Physics, School of Physical Sciences, University of Adelaide, Adelaide, South Australia 5005, Australia.
  • Chen DZ; Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, USA.
  • Kusumaatmaja H; Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana 46556, USA.
  • Wales DJ; Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana 46556, USA.
Phys Rev Lett ; 117(2): 028301, 2016 Jul 08.
Article em En | MEDLINE | ID: mdl-27447530
ABSTRACT
The Thomson problem, arrangement of identical charges on the surface of a sphere, has found many applications in physics, chemistry and biology. Here, we show that the energy landscape of the Thomson problem for N particles with N=132, 135, 138, 141, 144, 147, and 150 is single funneled, characteristic of a structure-seeking organization where the global minimum is easily accessible. Algorithmically, constructing starting points close to the global minimum of such a potential with spherical constraints is one of Smale's 18 unsolved problems in mathematics for the 21st century because it is important in the solution of univariate and bivariate random polynomial equations. By analyzing the kinetic transition networks, we show that a randomly chosen minimum is, in fact, always "close" to the global minimum in terms of the number of transition states that separate them, a characteristic of small world networks.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2016 Tipo de documento: Article