Exoplanet Detection using Joint Signal Estimation

Athol Kemball, University of Illinois at Urbana-Champaign

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One half of the 2019 Nobel Prize in Physics was awarded for the discovery of the first exoplanet in 1995. Transiting exoplanet detection telescopes and missions such as CoRoT(L´eger et al. 2009), Kepler (Borucki et al. 2010), K2 (Howell et al. 2014), and TESS (Ricker et al. 2014) have been crucial to expanding the catalog of known exoplanets and their populations statistics. Exoplanet detection is a data-and compute-intensive process and detection efficiency is limited both by the data processing algorithm and instrument sensitivity. Here we propose to expand on prior work on Blue Waters (Taaki et al 2020) in which we developed a novel joint Bayesian detection framework and demonstrated increased detection efficiency compared to standard detection approaches. Our detection framework uses a complete signal model and jointly estimates systematic instrumental noise and the transit signal, avoiding the distortion of weak exoplanet signals by prior signal processing steps. Our prior work focused on targets from the Kepler dataset. TESS follows as the successor to the Kepler mission, launched in 2018. In this proposal we request an allocation to perform the first independent large-scale search for undetected exoplanets among the persistent targets in the first year of TESS data using our new algorithm. All codes to perform this research have been developed and tested in the previous allocation. Joint Bayesian estimation is statistically superior but requires petascale computational resources. This proposal represents a unique opportunity for Blue Waters to participate in the discovery of new exoplanets in a recent space mission.