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Maskininlärning för kvantmekaniska problem
KTH, School of Engineering Sciences (SCI).
KTH, School of Engineering Sciences (SCI).
2019 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Machine learning for problems in quantum mechanics (English)
Abstract [sv]

I den här artikeln undersökts hurvida maskininlärning kan vara till hjälp för att lösa fysika-liska problem. Detta undersöks genom att ett artificiellt neuralt nätverk implementeras ochtränas upp för att hitta energinivåerna för den harmoniska oscillatorn med och utan elekt-riskt fält. För att skapa nätverket användes radiella basfunktioner. Monte Carlo-metoderanvändes för stora beräkningar. Metoden visade sig fungera väl i vissa sammanhang menhade problem för stora elektriska fält. De problem som uppstod var att konvergensen blevinstabil med hopp i energin och att systemet inte alltid konvergerade mot rätt energi.

Abstract [en]

In this article we analyze whether machine learning can be used to help solve problemsin physics. This is examined by implementing an artificial neural network which is trainedto find the energy levels for the quantum harmonic oscillator with and without an externalelectric field. Radial basis functions were used to make the neural network. Monte Carlomethods were used for heavy calculations. The method was shown to work well in somecases but had problems for large electric fields. The problems that occured were that theconvergence became unstable, with leaps in the energy and that the system did not alwaysconverge to the right energy level.

Place, publisher, year, edition, pages
2019.
Series
TRITA-SCI-GRU ; 2019:205
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-255698OAI: oai:DiVA.org:kth-255698DiVA, id: diva2:1341320
Supervisors
Examiners
Available from: 2019-08-08 Created: 2019-08-08 Last updated: 2019-08-08Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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