Browsing Science (Faculty of) by Subject "machine learning"
Now showing items 1-11 of 11
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Applications of the Quantum Kernel Method on a Superconducting Quantum Processor
(University of Waterloo, 2020-05-29)The widespread benefits of classical machine learning along with promised speedups by quantum algorithms over their best performing classical counterparts have motivated development of quantum machine learning algorithms ... -
Creating and probing laser-cooled atomic ensembles inside a hollow-core optical fibre
(University of Waterloo, 2024-01-26)A laser-cooled atomic ensemble confined inside a hollow-core optical fiber offers a unique platform for enhanced light-matter interactions and their applications. At the same time, transferring a cloud of laser-cooled ... -
Determining Molecular Physicochemical Properties Using Differential Mobility Spectrometry
(University of Waterloo, 2019-09-26)This thesis aims to explore the usage of differential mobility spectrometry (DMS) and quantum chemical calculations to separate and identify drug compounds, as well as the use of machine learning (ML) to predict physicochemical ... -
Explorations in machine learning for interacting many-body systems.
(University of Waterloo, 2020-09-03)Most interacting many-body systems in physics are not analytically solvable. Instead, numerical methods are needed for the study of these complex and high-dimensional problems. At present, there are many interesting problems ... -
Machine Learning Topological Defects of Liquid Crystals in Two Dimensions
(University of Waterloo, 2019-08-26)Over the recent few years, condensed matter physics has keenly been testing out the compelling techniques from the toolbox of machine learning. Order parameters, phase transitions, and other thermodynamic quantities have ... -
Mitigating Fiber Nonlinearity with Machine Learning
(University of Waterloo, 2021-12-20)Nowadays, optical communication transmission is based mainly on optical fiber networks. Increasing demands for higher-capacity systems are hampered by signal distortions due to nonlinear effects of the commercial optic ... -
Neural networks and quantum many-body physics: exploring reciprocal benefits.
(University of Waterloo, 2021-08-03)One of the main reasons why the physics of quantum many-body systems is hard lies in the curse of dimensionality: The number of states of such systems increases exponentially with the number of degrees of freedom ... -
Predicting the thioflavin fluorescence of retinal amyloid deposits in association with Alzheimer’s disease and differentiating amyloid protein from alpha-syn
(University of Waterloo, 2020-09-02)Alzheimer’s disease (AD) is a neurodegenerative disease and the most common cause of dementia. According to the World Health Organization (WHO) in 2019, dementia affects around 50 million people worldwide and this number ... -
Probing High Energy Physics Through Gravitational Waves
(University of Waterloo, 2021-09-22)Over the last few years, gravitational wave detections have become ubiquitous, giving the physics community vast information about fundamental physics. As some of the universe’s highest energy events, neutron mergers ... -
Probing universality with entanglement entropy via quantum Monte Carlo
(University of Waterloo, 2019-08-30)Our understanding of physical phenomena hinges on finding universal core mechanisms that unite them. The concept of universality is deeply ingrained in the study of quantum many-body systems. At zero temperature, microscopically ... -
Studies of Reentrance in Pyrochlore Magnets and Machine Learning of Quenched Gauge Symmetries
(University of Waterloo, 2020-09-18)In this thesis, we present two explorations: (1) understanding the mechanism causing reentrant behavior in the rare-earth pyrochlore magnet Er2Sn2O7, and (2) determining if unsupervised machine learning is capable of ...