An Evolutionary approach for solving Shrödinger Equation
This addresses the problem of solving complex quantum equations for researchers in computational physics, but it appears incremental as it applies existing evolutionary methods to a known equation.
The paper tackles solving the Schrödinger Equation by using Genetic Algorithms and Grammatical Evolution to generate analytical trial solutions, achieving results for a quantum system's minimal energy that are compared to traditional analytical methods.
The purpose of this paper is to present a method of solving the Shrödinger Equation (SE) by Genetic Algorithms and Grammatical Evolution. The method forms generations of trial solutions expressed in an analytical form. We illustrate the effectiveness of this method providing, for example, the results of its application to a quantum system minimal energy, and we compare these results with those produced by traditional analytical methods