A maximum entropy approach to detect close-in giant planets around active stars
P. Petit, J.-F. Donati, E. H\'ebrard, J. Morin, C.P. Folsom, T., B\"ohm, I. Boisse, S. Borgniet, J. Bouvier, X. Delfosse, G. Hussain, S.V., Jeffers, S.C. Marsden, and J.R. Barnes

TL;DR
This paper introduces a maximum entropy-based method to detect close-in giant planets around active stars by extracting orbital parameters from distorted line profiles, improving detection capabilities where traditional methods struggle.
Contribution
The authors develop a simple, adaptable tomographic inversion technique that simultaneously maps stellar brightness and determines planetary orbital parameters, enhancing exoplanet detection around active stars.
Findings
Successfully recovers planetary signals with semi-amplitude down to 50 m/s
Robustly determines orbital period and phase even with high stellar activity
Identifies biases when planetary orbit is near co-rotation
Abstract
(shortened for arXiv) We aim to progress towards more efficient exoplanet detection around active stars by optimizing the use of Doppler Imaging in radial velocity measurements. We propose a simple method to simultaneously extract a brightness map and a set of orbital parameters through a tomographic inversion technique derived from classical Doppler mapping. Based on the maximum entropy principle, the underlying idea is to determine the set of orbital parameters that minimizes the information content of the resulting Doppler map. We carry out a set of numerical simulations to perform a preliminary assessment of the robustness of our method, using an actual Doppler map of the very active star HR 1099 to produce a realistic synthetic data set for various sets of orbital parameters of a single planet in a circular orbit. Using a simulated time-series of 50 line profiles affected by a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
