Term of Award

Summer 2020

Degree Name

Master of Science in Mathematics (M.S.)

Document Type and Release Option

Thesis (restricted to Georgia Southern)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


Department of Mathematical Sciences

Committee Chair

Shijun Zheng

Committee Member 1

Zhan Chen

Committee Member 2

Ionut Iacob


The last few years have seen an increased interest in the development of new neural network models to solve quantum computing problems. According to the Cybenko theorem, neural networks are universal approximators. In this thesis I introduce the study the Bose-Einstein condensate and its possible ground state solutions using artificial neural networks. I present an introduction to the derivation of the Gross Pitaevskii equation and the re-implementation of a recent neural network model to derive wave equation solutions. Additionally, I introduce the reader to advances in neural networks which allow an interesting direction towards future implementation.

Research Data and Supplementary Material