Date of Award

2013

Document Type

Thesis

Degree Name

Bachelors

Department

Natural Sciences

First Advisor

McDonald, Patrick

Keywords

Rotational Spectroscopy, Genetic Algorithm, Inverse Spectral Problem

Area of Concentration

Mathematics

Abstract

Genetic algorithms provide a useful scheme for approximating solutions to optimization problems; however na\"ively applying the technique can produce poor results. We explore a potential technique to improve the sensitivity of genetic algorithms in the context of fitting high resolution, high temperature spectral data; that of estimating the eigenvalues of the Hamiltonian rather than the rotational constants used to compute the Hamiltonian directly. We then attempt to develop solutions to a problem introduced by this technique; that of estimating a Hamiltonian with knowledge of only the form of the Hamiltonian and the associated eigenvalues. We explore the computational difficulty of this solution and develop ideas to resolve these issues.

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