Date of Award

2012

Document Type

Thesis

Degree Name

Bachelors

Department

Natural Sciences

First Advisor

Shipman, Steven

Keywords

Genetic Alogorithims, Spectroscopy, Distributed Computing

Area of Concentration

Applied Mathematics

Abstract

Fitting molecular parameters to microwave spectra is difficult, especially for room tem-perature spectra, which are very dense. The current method is to manually match peaks and tweak parameters, an extremely time consuming process. Because the forward prob-lem of predicting a spectrum given molecular parameters is much easier, a genetic algo-rithm is potentially well-suited to automated spectral fitting. A genetic algorithm was de-veloped to fit spectra by optimizing the rotational and distortion parameters of the mole-cule for the best match between the predicted and observed spectra. The algorithm was tested on a variety of simulated and experimentally observed spectra with some success. The use of parallel, distributed, and cloud computing to run the genetic algorithm faster also posed some interesting challenges.

Rights

This bibliographic record is available under the Creative Commons CC0 public domain dedication. The New College of Florida, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.

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