Numerical solution of the Schrödinger equation by a microgenetic algorithm

H. Nakanishi; M. Sugawara

doi:10.1016/S0009-2614(00)00913-1

Numerical solution of the Schrödinger equation by a microgenetic algorithm

H. Nakanishi, M. Sugawara

Department of Chemistry

Research output: Contribution to journal › Article › peer-review

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 language	English
Pages (from-to)	429-438
Number of pages	10
Journal	Chemical Physics Letters
Volume	327
Issue number	5-6
DOIs	https://doi.org/10.1016/S0009-2614(00)00913-1
Publication status	Published - 2000 Sep 15

ASJC Scopus subject areas

Physics and Astronomy(all)
Physical and Theoretical Chemistry

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abstract = "A new approach for solving the Schr{\"o}dinger 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.",

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