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Employing Modern Statistics To Explore the Universe with Type Ia Supernovae

Weyant, Anja (2014) Employing Modern Statistics To Explore the Universe with Type Ia Supernovae. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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The Large Synoptic Survey Telescope (LSST) anticipates observing hundreds of thousands of well-measured Type Ia supernovae (SNe Ia). These stellar remnant explosions are exceptional in that they have a standardizeable light curve which allows for an accurate measurement of their luminosity. The standard nature of SNe Ia allow us to measure relative distances in the Universe with better than 6\% precision in distance. With distance estimates in hand to large sets of galaxies through Type Ia Supernova (SN Ia) measurements, we can measure the expansion history of the Universe or create flow models of how galaxies (matter) near the Milky Way are moving.

In this new regime of large datasets, weaknesses and limitations of the current techniques for estimating cosmological parameters and modeling local flows are becoming apparent. As statistical errors are reduced systematic uncertainties ranging from calibration to survey design and cadence to host galaxy contamination are dominating the error budget and limiting our ability to make improvements on cosmological measurements. Similarly, recent comparisons of flow models reveal systematic inconsistencies between different approaches.

For my dissertation I have employed modern statistical methods to improve flow models in the local Universe by accounting for the non-uniform distribution of data across the sky and demonstrated how Approximate Bayesian Computation can tackle complicated likelihood functions in supernova cosmology. I also present the first results of a new near-infrared SN~Ia survey called "SweetSpot" whose focus is on improving our ability to standardize the total luminosity of SNe Ia.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Weyant, Anjaanw19@pitt.eduANW19
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairWood-Vasey, W. Michaelwmwv@pitt.eduWMWV
Committee MemberZentner, Andrewzentner@pitt.eduZENTNER
Committee MemberNewman, Jeffreyjanewman@pitt.eduJANEWMAN
Committee MemberShepard, Paulshepard@pitt.eduSHEPARD
Committee MemberWasserman,
Date: 25 September 2014
Date Type: Publication
Defense Date: 22 April 2014
Approval Date: 25 September 2014
Submission Date: 12 August 2014
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 192
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Physics
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Statistical methods, Type Ia Supernova, cosmology
Date Deposited: 25 Sep 2014 18:14
Last Modified: 15 Nov 2016 14:22


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