Identifying Exoplanets with Deep Learning. IV. Removing Stellar Activity Signals from Radial Velocity Measurements Using Neural Networks

Autor: Zoe. L. de Beurs, Andrew Vanderburg, Christopher J. Shallue, Xavier Dumusque, Andrew Collier Cameron, Christopher Leet, Lars A. Buchhave, Rosario Cosentino, Adriano Ghedina, Raphaëlle D. Haywood, Nicholas Langellier, David W. Latham, Mercedes López-Morales, Michel Mayor, Giusi Micela, Timothy W. Milbourne, Annelies Mortier, Emilio Molinari, Francesco Pepe, David F. Phillips, Matteo Pinamonti, Giampaolo Piotto, Ken Rice, Dimitar Sasselov, Alessandro Sozzetti, Stéphane Udry, Christopher A. Watson

Publikováno v: de Beurs, Z L, Vanderburg, A, Shallue, C J, Dumusque, X, Collier Cameron, A, Buchhave, L A, Cosentino, R, Ghedina, A, Haywood, R D, Langellier, N, Latham, D W, López-Morales, M, Mayor, M, Micela, G, Milbourne, T W, Mortier, A, Molinari, E, Pepe, F, Phillips, D F, Pinamonti, M, Piotto, G, Rice, K, Sasselov, D, Sozzetti, A, Udry, S & Watson, C A 2022, ' Identifying Exoplanets with Deep Learning. IV. Removing Stellar Activity Signals from Radial Velocity Measurements Using Neural Networks ', Astronomical Journal, vol. 164, no. 2, 49 . https://doi.org/10.3847/1538-3881/ac738e

Exoplanet detection with precise radial velocity (RV) observations is currently limited by spurious RV signals introduced by stellar activity. We show that machine learning techniques such as linear regression and neural networks can effectively remo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::be2c2272b48eb4a11cd7581d89345f2f