Numerical solution of the Schrödinger equation by a microgenetic algorithm

H. Nakanishi, Michihiko Sugawara

Research output: Contribution to journalArticle

36 Citations (Scopus)

Abstract

A new approach for solving the Schrödinger equation based on a microgenetic algorithm (μ-GA) is presented. Feed forward neural network is used to represent the solution, while random point evaluation method (RPEM) is introduced to define the fitness score to be maximized in the μ-GA breeding procedure. Convergence of the final stage of searching is accelerated by invoking the deterministic optimizer. The algorithm is tested in the calculation of one-dimensional harmonic oscillator and double-well potential systems.

Original languageEnglish
Pages (from-to)429-438
Number of pages10
JournalChemical Physics Letters
Volume327
Issue number5-6
Publication statusPublished - 2000 Sep 15

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fitness
Feedforward neural networks
harmonic oscillators
evaluation

ASJC Scopus subject areas

  • Physical and Theoretical Chemistry
  • Spectroscopy
  • Atomic and Molecular Physics, and Optics

Cite this

Numerical solution of the Schrödinger equation by a microgenetic algorithm. / Nakanishi, H.; Sugawara, Michihiko.

In: Chemical Physics Letters, Vol. 327, No. 5-6, 15.09.2000, p. 429-438.

Research output: Contribution to journalArticle

Nakanishi, H & Sugawara, M 2000, 'Numerical solution of the Schrödinger equation by a microgenetic algorithm', Chemical Physics Letters, vol. 327, no. 5-6, pp. 429-438.
Nakanishi, H. ; Sugawara, Michihiko. / Numerical solution of the Schrödinger equation by a microgenetic algorithm. In: Chemical Physics Letters. 2000 ; Vol. 327, No. 5-6. pp. 429-438.
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