Analytic and machine learning approaches to composite quantum impurities

Rzadkowski W. 2022. Analytic and machine learning approaches to composite quantum impurities. IST Austria.

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Thesis | PhD | Published | English
Series Title
IST Austria Thesis
Abstract
In this Thesis, I study composite quantum impurities with variational techniques, both inspired by machine learning as well as fully analytic. I supplement this with exploration of other applications of machine learning, in particular artificial neural networks, in many-body physics. In Chapters 3 and 4, I study quasiparticle systems with variational approach. I derive a Hamiltonian describing the angulon quasiparticle in the presence of a magnetic field. I apply analytic variational treatment to this Hamiltonian. Then, I introduce a variational approach for non-additive systems, based on artificial neural networks. I exemplify this approach on the example of the polaron quasiparticle (Fröhlich Hamiltonian). In Chapter 5, I continue using artificial neural networks, albeit in a different setting. I apply artificial neural networks to detect phases from snapshots of two types physical systems. Namely, I study Monte Carlo snapshots of multilayer classical spin models as well as molecular dynamics maps of colloidal systems. The main type of networks that I use here are convolutional neural networks, known for their applicability to image data.
Publishing Year
Date Published
2022-02-21
Page
120
ISSN
IST-REx-ID

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Rzadkowski W. Analytic and machine learning approaches to composite quantum impurities. 2022. doi:10.15479/at:ista:10759
Rzadkowski, W. (2022). Analytic and machine learning approaches to composite quantum impurities. IST Austria. https://doi.org/10.15479/at:ista:10759
Rzadkowski, Wojciech. “Analytic and Machine Learning Approaches to Composite Quantum Impurities.” IST Austria, 2022. https://doi.org/10.15479/at:ista:10759.
W. Rzadkowski, “Analytic and machine learning approaches to composite quantum impurities,” IST Austria, 2022.
Rzadkowski W. 2022. Analytic and machine learning approaches to composite quantum impurities. IST Austria.
Rzadkowski, Wojciech. Analytic and Machine Learning Approaches to Composite Quantum Impurities. IST Austria, 2022, doi:10.15479/at:ista:10759.
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