Cosmological analyses with Type Ia Supernovae (SNe Ia) have traditionally been reliant on spectroscopy for both classifying the type of supernova and obtaining reliable redshifts to measure the distance-redshift relation. While obtaining a host galaxy spectroscopic redshift for most SNe is feasible for our current datasets, it will be physically impossible for upcoming surveys such as the Vera Rubin Legacy Survey of Space and Time (LSST), which will observe on the order of millions of SNe. In this talk, I will present work using data from the Dark Energy Survey (DES) to address this problem by utilizing photometric redshifts inferred directly from the SN light-curve in combination with priors from host galaxy photometric redshift estimates (SN+host photo-z) to measure cosmological parameters with Type Ia Supernovae. I will discuss preliminary results to evaluate cosmological biases and validate our analysis using detailed catalog-level simulations. This work lays the foundation for fully photometric SNe Ia cosmological analyses to be done without the limitations of spectroscopy.
Séminaire donné par Rebecca Chen -- Duke University
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