| dc.description.abstract | Type Ia supernovae are some of the most luminous transient events in our universe, but their ultraviolet (UV) properties remain relatively unexplored when compared to the optical and infrared properties. In this dissertation I introduce various techniques that take advantage of the Neil Gehrels Swift Observatory Ultra-Violet/Optical Telescope’s (UVOT) multi-wavelength coverage in order to connect the well known optical properties of Type Ia supernovae with the lesser-known UV properties. First, I statistically compare the light curves of 97 nearby supernovae, showing for the first time that the UV and optical light curve properties of Type Ia supernovae are strongly correlated and have similar variability The light curves were modeled with templates, which were created by a technique called functional principal component analysis. This modeling technique allows for almost any light curve to be described as a linear combination of various weighted templates. Next I measure the intrinsic brightness, dust extinction, and k-corrections for a sample of 40 supernovae. With this I characterize the intrinsic variability of supernovae in the UV and optical, which when combined with the light curve correlations will pave the way for future cosmology studies that utilize the rest-frame UV emission. I accomplish this by creating multi-color models of the supernova’s spectral energy density with a range of artificial template spectra. Finally I demonstrate a light curve modeling technique that is capable of estimating the peak magnitudes of a supernova with as little as three epochs of observation. All of these modeling techniques and statistical analyses will be highly useful when the next generation of high redshift transient surveys, such as the Rubin Observatory and the Roman Space Telescope, come online and observe the rest-frame UV light of supernovae. | |
