Machine Learning for Physics: from Symbolic Regression to Quantum Simulation
In this thesis, we explore the application of machine learning (ML) methods to problems in physics. Because ML has revolutionized a wide range of fields, it is natural to ask whether it may be a valuable tool for physics. Physics applications present a challenge as many physics problems have a p...
Main Author: | Dugan, Owen Michael |
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Other Authors: | Soljačić, Marin |
Format: | Thesis |
Published: |
Massachusetts Institute of Technology
2024
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Online Access: | https://hdl.handle.net/1721.1/155406 |
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