Stochastic diagonalization of hamiltonian:A genetic algorithm-based approach

摘要

We propose and demonstratethe workability of a genetic-algorithmbased technique of finding the eigenvalues and eigenfunctions of a real symmetric Hamiltonian matrix.The algorithm can be tailored to extract all the eigenvalues at a time or to extract only the lowest or the highest eigenvalue first and then sequentially determine the next few higher 9lower)eigenvalues.The algorithm is generalized to handle diagonalization problems in which the basis functions themselves areoptimized simultaneously.Several model applications are reported.