Measuring Dark Energy with 1,345 Supernovae: Reducing Statistical Uncertainties on the Equation of State and Understanding the Dependence of Type Ia Supernovae on Their Local Environments
| dc.contributor.advisor | Riess, Adam | |
| dc.contributor.committeeMember | Bennett, Charles L. | |
| dc.contributor.committeeMember | Kamionkowski, Marc P. | |
| dc.contributor.committeeMember | Rest, Armin | |
| dc.contributor.committeeMember | Fox, Ori | |
| dc.creator | Jones, David Oscar | |
| dc.creator.orcid | 0000-0002-6230-0151 | |
| dc.date.accessioned | 2018-01-09T03:43:38Z | |
| dc.date.available | 2018-01-09T03:43:38Z | |
| dc.date.created | 2017-08 | |
| dc.date.issued | 2017-06-21 | |
| dc.date.submitted | August 2017 | |
| dc.date.updated | 2018-01-09T03:43:38Z | |
| dc.description.abstract | The acceleration of the universe at late cosmic times is one of the fundamental questions in astrophysics today. Larger and larger samples of Type Ia supernovae (SNeIa) have been compiled to measure the expansion history of the universe and in so doing deduce the nature of the dark energy driving the expansion. The goals of this thesis are to improve SNIa classification, better understand the relationship between SNe Ia and their host galaxy properties, and measure the dark energy equa- tion of state parameter, w, with the largest current sample of SNe Ia. First, I present observations of a SNIa at redshift 1.914, one of the most distant SNeIa to be dis- covered. I develop new methods to classify this SN using both its light curve and spectrum, and discuss the unique challenges of determining SN types at high redshift. Second, I study the dependence of SNe Ia on the star formation environment near the progenitor. It has been suggested that this dependence is a possible source of large systematic uncertainties on w. I find no evidence of a relationship between SNeIa and their local star formation environments. Third, I measure spectroscopic host galaxy redshifts for over 3,000 SNe discovered in the Pan-STARRS survey, ∼1,150 of which can be used to measure cosmological parameters. These SNe can be used to measure cosmological parameters if precise redshifts are known. I develop a Bayesian framework to marginalize over the contaminating distribution of core-collapse (CC) SNe and find that even with significant CC SN contamination, I can measure w with a bias of just 0.004 (8% of its statistical uncertainty). Finally, I use these methods to combine 1,345 SNe from Pan-STARRS and low-redshift compilations with constraints from the cosmic microwave background, baryon acoustic oscillations, and the locally measured Hubble constant to measure w. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://jhir.library.jhu.edu/handle/1774.2/44692 | |
| dc.language.iso | en_US | |
| dc.publisher | Johns Hopkins University | |
| dc.publisher.country | USA | |
| dc.subject | cosmology: observations--cosmology: dark energy--supernovae: general | |
| dc.title | Measuring Dark Energy with 1,345 Supernovae: Reducing Statistical Uncertainties on the Equation of State and Understanding the Dependence of Type Ia Supernovae on Their Local Environments | |
| dc.type | Thesis | |
| dc.type.material | text | |
| thesis.degree.department | Physics and Astronomy | |
| thesis.degree.discipline | Physics | |
| thesis.degree.grantor | Johns Hopkins University | |
| thesis.degree.grantor | Krieger School of Arts and Sciences | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Ph.D. |