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Probing dark energy with large galaxy surveys: systematics quantification and mitigation

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TitleInfo
Title
Probing dark energy with large galaxy surveys: systematics quantification and mitigation
Name (type = personal)
NamePart (type = family)
Awan
NamePart (type = given)
Humna
DisplayForm
Humna Awan
Role
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author
Name (type = personal)
NamePart (type = family)
Gawiser
NamePart (type = given)
Eric
DisplayForm
Eric Gawiser
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
School of Graduate Studies
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school
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Text
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theses
OriginInfo
DateCreated (encoding = w3cdtf); (keyDate = yes); (qualifier = exact)
2020
DateOther (encoding = w3cdtf); (qualifier = exact); (type = degree)
2020-05
Language
LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
Abstract (type = abstract)
Dark energy is a leading theory to explain cosmic acceleration, and forthcoming astronomical surveys have been specifically designed to probe this mysterious energy component of our universe. This thesis addresses aspects of using large galaxy surveys to study dark energy, which requires an unprecedented understanding and mitigation of systematics -- a challenge that can be addressed on two fronts: quantification of the impacts of systematics, and new tools to mitigate them. Here, we specifically study the impacts of three key systematics: those induced by 1) the telescope observing strategy, 2) the Milky Way dust, and 3) uncertain photometric redshifts. Focusing on the Legacy Survey of Space and Time (LSST) carried out by the Vera C. Rubin Observatory, we quantify the impacts of LSST observing strategy on large-scale structure studies, which is a probe of dark energy. We demonstrate the effectiveness of large translational dithers -- telescope-pointing offsets -- in increasing LSST survey uniformity and reducing systematic uncertainties (Awan et al., 2016; LSST Science Collaboration et al., 2017) -- a result that has now been adopted for the baseline LSST observing strategy. We also study the impacts of Milky Way dust on dark energy science and demonstrate that ~25% of the default LSST survey area would not be useful for extragalactic static science given the Milky Way dust extinction, motivating the reconfiguration of the LSST survey footprint to avoid high-extinction regions of the sky (Lochner et al., 2018; Olsen et al., 2018). And finally, we present a new formalism that provides a novel way to correct for redshift contamination arising from photometric redshift estimation (Awan & Gawiser, 2020). Specifically, we first introduce a general formalism to correct for sample contamination for photometric galaxy samples when measuring two-point angular correlation functions, and then a new weighted estimator that assigns each galaxy a weight in each redshift bin based on its probability of being in that bin, thereby fully utilizing the probabilistic distance information available for photometric galaxies. While these techniques are motivated by preparations for LSST, they are applicable to other large galaxy surveys like Dark Energy Survey (DES), Dark Energy Spectroscopic Instrument (DESI), Hobby-Eberly Telescope Dark Energy Experiment (HETDEX), Euclid, and Wide-Field Infrared Survey Telescope (WFIRST).
Subject (authority = LCSH)
Topic
Dark energy (Astronomy)
Subject (authority = RUETD)
Topic
Physics and Astronomy
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
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ETD_10743
PhysicalDescription
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application/pdf
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text/xml
Extent
1 online resource (ix, 116 pages) : illustrations
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
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TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/t3-snnr-4709
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Awan
GivenName
Humna
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2020-04-14 19:47:15
AssociatedEntity
Name
Humna Awan
Role
Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
AssociatedObject
Type
License
Name
Author Agreement License
Detail
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.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

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2020-04-14T19:39:57
DateCreated (point = end); (encoding = w3cdtf); (qualifier = exact)
2020-04-14T19:39:57
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