Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/180883
Title: Solving the Schrödinger equation with machine learning
Author: Rozalén Sarmiento, Javier
Director/Tutor: Ríos Huguet, Arnau
Keywords: Aprenentatge automàtic
Equació de Schrödinger
Treballs de fi de grau
Machine learning
Schrödinger equation
Bachelor's theses
Issue Date: Jul-2021
Abstract: The Schrödinger equation is known to be a great tool for understanding small physical systems, yet an analytical solution exists solely for some simple cases. As a consequence of this, a wide variety of numerical methods are used to solve real systems, and machine learning methods, namely Artificial Neural Networks (ANNs), are amidst the newest. In this work we use an ANN to find the ground state wave function of the deuteron -this is, the nuclear two-body bound state-, achieving energy values that are within 0.05% of the exact results and wave functions that overlap up to 99.9997% with the exact ones. We also compare the performance of a single-layer ANN against a two-layer ANN, the latter not showing significant improvements over the former
Note: Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2021, Tutor: Arnau Rios Huguet
URI: http://hdl.handle.net/2445/180883
Appears in Collections:Treballs Finals de Grau (TFG) - Física

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