A Study of the Gross Pitaevskii Equation Ground State Solutions Using Artificial Neural Networks
Term of Award
Master of Science in Mathematics (M.S.)
Document Type and Release Option
Thesis (restricted to Georgia Southern)
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This work is licensed under a Creative Commons Attribution 4.0 License.
Department of Mathematical Sciences
Committee Member 1
Committee Member 2
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.
Iqbal, Mehtab, "A Study of the Gross Pitaevskii Equation Ground State Solutions Using Artificial Neural Networks" (2020). Electronic Theses and Dissertations. 2155.
Research Data and Supplementary Material