An optimal exoplanet detection criterion

Nathan Hara (Université de Genève)
April 22, 2022 — 11:00 — Online

Abstract

Over 4000 exoplanets have been detected so far. They have deeply transformed our understanding of planetary system formation, and expanded our possibilities to search for life outside of Earth. The smaller and the more distant to their host stars exoplanets are, the harder they are to detect. Earth « twins » orbiting solar-type stars are still out of reach because of very complex astrophysical and instrumental noises. To overcome this difficulty, we need new methods to analyse unevenly sampled, multi-variate time series: better models, computational methods and decision rules to claim detections. In this talk I will mostly focus on the latter aspect. Exoplanet detections are claimed based on the value of a statistical significance metric: if it is greater than a certain threshold, a detection is claimed. I will address the question of the optimal significance metric in the general setting of detection of parametric signals, and advocate for a Bayesian hypothesis testing framework where hypotheses are indexed by continuous variables.

References

[1] A continuous multiple hypothesis testing framework for optimal exoplanet detection, submitted to Annals of Applied Statistics, Hara, de Poyferré, Delisle, Hoffmann https://arxiv.org/abs/2203.04957

[2] exoplanet detection capabilities with the false inclusion probability. Comparison with other detection criteria in the context of radial velocities, Astronomy and Astrophysics, accepted, https://arxiv.org/abs/2105.06995

Biography

Nathan Hara is a research fellow at the university of Geneva since 2017, which he joined after a PhD with Jacques Laskar and Gwenaël Boué at Paris Observatory. He works on statistical techniques to detect exoplanets, in particular Earth twins, which are prime candidates for the detection of life outside of Earth, and observational programs to unveil multi-planetary systems.