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Accueil > Séminaires > Archive des séminaires d’Utinam > 2019

Gábor Marton

Planet formation caught in the act

mardi 24 septembre 2019, 14h15

salle de conférences de l’observatoire

Gábor Marton

Observatoire de Konkoly Budapest (Hongrie)

Mots-clés :
Astrophysique, formation des étoiles et des planètes, Gaia, Machine Learning

Résumé :

The second Gaia Data Release (DR2) contains astrometric and photometric data for more than 1.6 billion objects with mean Gaia G magnitude <20.7, including many Young Stellar Objects (YSOs) in different evolutionary stages. In order to explore the YSO population of the Milky Way, we combined the Gaia DR2 database with WISE and Planck measurements and made an all-sky probabilistic catalogue of YSOs using machine learning techniques, such as Support Vector Machines, Random Forests, or Neural Networks. Our input catalogue contains 103 million objects from the DR2xAllWISE cross-match table. We classified each object into four main classes : YSOs, extragalactic objects, main-sequence stars and evolved stars. At a 90% probability threshold we identified 1.7 million YSO candidates. As Gaia measures the sources at multiple epochs, it can efficiently discover transient events, including sudden brightness changes of YSOs caused by dynamic processes of their circumstellar disk. A cross-check of the published Gaia alerts with our new catalogue shows that about 30% more alerts can most likely be attributed to YSO activity. Based on our results we suggested modifications to the Gaia Photometric Science Alerts pipeline, which were tested and implemented, now alerting for significantly more YSOs than before.