Numerical solution of the Schrödinger equation by neural network and genetic algorithm

M. Sugawara

研究成果: Article査読

22 被引用数 (Scopus)

抄録

A new approach for solving the Schrödinger equation based on genetic algorithm (GA) and artificial neural network (NN) is presented. Feed-forward perceptron-type network is used to represent the wavefunction, while network parameters are optimized by micro-genetic algorithm so that the NN satisfies the Schrödinger equation. In the GA breeding process, random point evaluation method (RPEM) for fitness evaluation is introduced to improve the convergence. Final solution is obtained by invoking deterministic optimizer which corresponds to a "learning process" of the NN. The present method is tested in the calculation of one-dimensional harmonic oscillator and other model potentials.

本文言語English
ページ(範囲)366-380
ページ数15
ジャーナルComputer Physics Communications
140
3
DOI
出版ステータスPublished - 2001 11 1

ASJC Scopus subject areas

  • Hardware and Architecture
  • Physics and Astronomy(all)

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