Uncovering Transient Physics and Optimizing Cosmological Inference with a Recommendation Engine for Rapid-Response Spectroscopy

Tuesday, 10 October 2023 7 a.m. — 8 a.m. MST

AURA Lecture Hall

NOIRLab South Colloquia
Amanda Rose Wasserman (University of Illinois Urbana-Champaign)

The Vera Rubin Observatory’s (VRO) Legacy Survey of Space and Time (LSST) will observe over 106 transients per year, increasing the number of yearly discovered transients by a factor of 100 (Zeljko Ivezic et al. 2019). With scarce spectroscopic resources, an expected 0.1% will be followed up spectroscopically (Hsu et al. 2022), despite being necessary for probing supernova progenitor physics and accurately estimating cosmological parameters. Due to the incoming immense quantity of transient sources, we require a method to determine what subset of the discovered supernovae should be investigated further. I propose adapting and implementing the Recommendation System for Spectroscopic Follow-up (RESSPECT) to select the most scientifically useful supernovae (Ishida et al. 2018; Kennamer et al. 2020). Additionally, we require the means to follow up on these supernovae. In preparation for LSST, I have triggered observations using the Gemini Multi-Object Spectrograph on transients discovered by precursor wide-field surveys. I will describe my previous, current, and proposed work to rapidly follow up on interesting transient objects and use their spectra to uncover transient physics and optimize cosmological inference by creating a purer training sample of type Ia supernovae.