Flare Statistics for Young Stars from a Convolutional Neural Network Analysis of TESS Data

All-sky photometric time-series missions have allowed for the monitoring of thousands of young (t(age) < 800 Myr) stars in order to understand the evolution of stellar activity. Here, we developed a convolutional neural network (CNN), stella, specifically trained to find flares in Transiting Exop...

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Bibliographic Details
Published in:	The Astronomical journal Vol. 160; no. 5; pp. 219 - 234
Main Authors:	Feinstein, Adina D., Montet, Benjamin T., Ansdell, Megan, Nord, Brian, Bean, Jacob L., Günther, Maximilian N., Gully-Santiago, Michael A., Schlieder, Joshua E.
Format:	Journal Article
Language:	English
Published:	Goddard Space Flight Center The American Astronomical Society 01.11.2020 IOP Publishing / American Astronomical Society IOP Publishing IOP Publishing - AAAS
Subjects:	Amplitudes Artificial neural networks Astronomy ASTRONOMY AND ASTROPHYSICS Astrophysics Convolutional neural networks Extrasolar planets INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY Light curve Network analysis Neural networks Planet detection PMS stars Pre-main sequence stars Source code Stars Stellar activity Stellar age Stellar evolution Stellar flares Stellar rotation Time series analysis Toolkits Transit
ISSN:	0004-6256, 1538-3881, 1538-3881
Online Access:	Get full text
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