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Activity Number: 102 - SAMSI-ASTRO: New Innovations and Challenges in Astrostatistics
Type: Invited
Date/Time: Monday, July 30, 2018 : 8:30 AM to 10:20 AM
Sponsor: Statistical and Applied Mathematical Sciences Institute
Abstract #325455 Presentation
Title: Detecting Planets: Jointly Modeling Radial Velocity and Stellar Activity Time Series
Author(s): David Edward Jones* and David Stenning and Eric Ford and Robert Wolpert and Thomas Loredo and Xavier Dumusque
Companies: Duke University and SAMSI and Imperial College London and Penn State University and Duke University and Cornell University and Observatoire Astronomique de l'Universite de Geneve
Keywords: Guassian process; astronomy; model selection; neural networks
Abstract:

The radial velocity technique is one of the two most successful approaches for detecting planets outside our solar system. When a planet orbits a star it causes the star to move and this induces a Doppler shift (i.e. the star light appears redder or bluer than expected), and it is this effect that the radial velocity method attempts to detect. Unfortunately, these Doppler signals are typically contaminated by various stellar activity phenomena, such as dark spots on the star surface. We build on previous work in two ways: (i) we propose using dimension reduction techniques to construct high-information stellar activity proxies, as opposed to using existing proxies; (ii) we extend the Gaussian process stellar activity model proposed by Rajpaul et al. (2015) to a class of models and use a model comparison procedure to select the best model for the particular proxies at hand. Our approach results in substantially improved statistical power for planet detection compared with existing methods in the astronomy literature. Future work will include the use of neural networks to better learn the relationships between stellar activity proxies and radial velocity corruption.


Authors who are presenting talks have a * after their name.

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