I study type Ia supernovae. With good measurements, these supernovae can be used as “standard candles,” meaning their apparent brightness gives their distances. These distances help us measure the expansion history of the universe while the objects themselves are astrophysically important.
- Collecting a large number of supernovae allows us to plot the expansion history of the universe. To this end, I am the cofounder and now the overseer of the Union compilations of SNe Ia. Read more about the Union compilations.
Using these supernovae for cosmology requires many careful steps, from the search, to detailed pixel-level models of the images for accurate photometry (brightness measurements), to statistical techniques for the accurate estimation of uncertainties.
The Search for SNe
- Combining ground and space telescopes—Subaru and Hubble—we can collect the largest sample of high-redshift SNe (z>1) in a single survey. The SUbaru Supernovae with Hubble Infrared (SUSHI) HST program (co-PI’d with Nao Suzuki) is currently collecting IR data on these high-redshift SNe discovered in the Subaru Strategic Program. Read more about the SUSHI program.
- The next generation of space-based observing will rely on two telescopes, James Webb (under construction) and the Nancy Grace Roman Space Telescope (RST, under construction). I am currently calculating the specifications of RST for optimal supernova cosmology. Read more about my work on RST.
Modeling the Images
- Calibrating our telescopes’ instruments reduces a significant source of systematic uncertainties and, in turn, improves our estimates. Read more about my work on calibration and photometry.
Statistical Techniques and other Computation Considerations
- Current cosmological analyses are limited by their inability to properly model outliers, selection effects, shape- and color-standardization relations, unexplained dispersion, and heterogeneous observations… until UNITY. Using Bayesian Hierarchical modeling, my framework, the Unified Nonlinear Inference for Type-Ia cosmologY (UNITY), simultaneously models each of these factors and significantly reduces our statistical and systematic uncertainties. Read more about my work on UNITY.
- When possible, I perform my studies using “blinded analyses,” which help protect researchers from inadvertently tweaking their analysis steps until they obtain their expected results.