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Insights on galaxy evolution from studies of the multiphase interstellar medium
Descriptive
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Title
Insights on galaxy evolution from studies of the multiphase interstellar medium
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Wu
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John
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1991-
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John Wu
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author
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Baker
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Andrew J
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Andrew J Baker
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Advisory Committee
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chair
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Jha
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Saurabh
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Saurabh Jha
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Advisory Committee
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internal member
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(type = family)
Cizewski
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Jolie A
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Jolie A Cizewski
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Advisory Committee
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internal member
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(type = family)
Gawiser
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(type = given)
Eric
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Eric Gawiser
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Advisory Committee
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internal member
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(type = family)
Leroy
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Adam
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Adam Leroy
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Advisory Committee
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outside member
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Rutgers University
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School of Graduate Studies
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theses
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2019
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2019-10
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English
Abstract
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Modern galaxy formation and evolution models are able to match the statistical properties of galaxy populations across most of cosmic history. However, detailed observations and sophisticated analytical methods are still needed to test theoretical predictions in extreme scenarios, where the complex interplay of gas accretion, star formation, galaxy interactions, feedback, and other physical processes can have compounded impacts on interstellar medium properties. I discuss results from new far-infrared and submillimeter observations of star-forming galaxies in four massive galaxy clusters at redshifts 0.3 ≲ z ≲ 1.1. Despite being surrounded by hot intracluster plasma, some cluster members are able to retain their cold gas reservoirs, and have high dust-obscured star formation rates. I find that the prevalence of star-forming cluster galaxies increases with increasing redshift. I also present results from integral field spectroscopy, centered on the Paα line, targeting a sample of rare, low-redshift, compact starbursts that strongly resemble z ~ 3 Lyman break galaxies (LBGs). H2 ro-vibrational emission is measured for the first time in either distant LBGs or their low-z analogs. Warm molecular gas and ionized gas properties suggest that star formation feedback is the dominant excitation mechanism in these systems. I also find that, compared to typical nearby star-forming galaxies, LBG analogs are characterized by high velocity dispersions and low ordered-to-disordered velocity ratios. LBG analogs deviate from kinematic scaling relations such as the stellar mass and baryonic Tully-Fisher relations; their anomalously low kinematic support may be attributed to their small physical sizes. Finally, I optimize a deep convolutional neural network (CNN) to predict the gas-phase metallicities of typical low-z star-forming galaxies from three-band optical imaging. The trained CNN is not only able to accurately estimate metallicity, but also can reconstruct the empirical mass-metallicity relation with zero additional scatter. These results imply that multi-color morphological features are important for understanding the connection between galaxies' stellar mass assembly and chemical enrichment histories.
Subject
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Topic
Physics and Astronomy
Subject
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Topic
Extragalactic astronomy
Subject
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Topic
Galaxies -- Evolution
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Rutgers University Electronic Theses and Dissertations
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ETD_10114
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1 online resource (xviii, 211 pages) : illustrations
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Ph.D.
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Includes bibliographical references
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School of Graduate Studies Electronic Theses and Dissertations
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rucore10001600001
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doi:10.7282/t3-b1d7-2j50
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ETD doctoral
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Rights
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The author owns the copyright to this work.
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Name
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Wu
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John
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Permission or license
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2019-07-10 10:08:49
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John Wu
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Rutgers University. School of Graduate Studies
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Author Agreement License
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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2019-10-31
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2021-10-30
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after October 30th, 2021.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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2019-07-10T10:06:24
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