Type: Poster
Session: Posters (Wednesday & Thursday)
Author: Anna Khalid

Abstract: Our project goal is to measure cosmological parameters from a sample of supernovae. We will use the Joint Light Curve Analysis and Pantheon Type Ia supernova data to measure cosmological parameters applying massive optimal data compression. In collaboration with Catalyst Fellow Dr. Arrykrishna Mootoovaloo, we will test his Bayesian analysis pipelines that allow the measurement of cosmology using likelihood-free inference. Additionally, we will use Type Ia supernovae from the Rubin Observatory's DP0.2 dataset to test the pipeline and verify if the input cosmological parameters are accurately recovered.