| dc.description.abstract | Local measurements of the Hubble constant rely on extragalactic distance measurements, which are made using observations of Type Ia supernovae and certain variable stars. This dissertation focuses on two classes of variable star that are used to make distance measurements: Classical Cepheids and Mira variables.
The Legacy Survey of Space and Time (LSST), which will be conducted at the Vera C. Rubin Observatory, will return time-series data that have an ideal cadence for Mira studies. In anticipation of these data, we perform a search for Miras in the LSST photometric bands. We use archival optical and near-infrared observations of the galaxy M33 taken with the Canada-France-Hawaii Telescope’s MegaCam and WIRCam instruments. We use machine learning classifiers to efficiently identify strong Mira candidates, which are visually confirmed. We also use period-luminosity relations for Miras in the Large Magellanic Cloud to identify Mira candidates in M33. We present the first empirical characterization of Miras in the LSST bands. We also recover approximately 70 percent of a sample of previously identified Miras and identify 2,916 new Mira candidates. For the first time, we find evidence for a first-overtone pulsation sequence in M33’s Miras.
We also present H-band Milky Way Cepheid light curves extracted via difference imaging from observations taken with the United Kingdom InfraRed Telecope’s Wide-Field Infrared Camera. The crowded nature of the Cepheid fields renders traditional photometric methods less effective, so we adapt and deploy a difference imaging pipeline originally written for data from the Transiting Exoplanet Survey Satellite. The light curves are used to derive corrections to “mean light” for random-phase Hubble Space Telescope observations. The phase corrections obtained from the H-band light curves are in good agreement with similar corrections obtained from VI light curves from the literature. | |
