All the lenses : large-scale hierarchical inference of the hubble constant from strong gravitational lenses with Bayesian deep learning

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Abstract/Contents

Abstract
Unprecedented volumes of data from upcoming sky surveys will yield precise constraints on parameters governing the evolution history of the Universe. One that has received particular attention over the past decade is the Hubble constant (H0) describing the expansion rate of the Universe. This thesis focuses on measuring H0 from an astrophysical phenomenon called strong gravitational lensing. The Vera Rubin Observatory's Legacy Survey of Space and Time (LSST) will increase the sample size of strong lenses from ~100 to ~100,000. This creates an opportunity to obtain the most precise measurement of H0 to date. Fully realizing the potential of LSST data entails rapidly extracting cosmological information from the images, tables, and time series associated with these lenses. My research has focused on developing analysis techniques using Bayesian deep learning, which combines the efficiency of deep learning with principled uncertainty quantification. The techniques promise to automate the analysis of tens of thousands of strong lensing systems in a robust manner. They constitute core methodology that can combine information from all the LSST lenses -- with varying types and signal-to-noise ratios -- into a large-scale hierarchical inference of H0.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2022; ©2022
Publication date 2022; 2022
Issuance monographic
Language English

Creators/Contributors

Author Park, Ji Won
Degree supervisor Roodman, Aaron J. (Aaron Jay), 1964-
Thesis advisor Roodman, Aaron J. (Aaron Jay), 1964-
Thesis advisor Burchat, P. (Patricia)
Thesis advisor Kahn, Steven M. (Steven Michael)
Degree committee member Burchat, P. (Patricia)
Degree committee member Kahn, Steven M. (Steven Michael)
Associated with Stanford University, Department of Physics

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Ji Won Park.
Note Submitted to the Department of Physics.
Thesis Thesis Ph.D. Stanford University 2022.
Location https://purl.stanford.edu/cd335wx5645

Access conditions

Copyright
© 2022 by Ji Won Park
License
This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).

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