==========================================================================
II/360 Gaia DR2 x AllWISE catalogue (Marton+, 2019)
The following files can be converted to FITS (extension .fit or fit.gz)
catalog.dat
==========================================================================
Query from: http://vizier.cds.unistra.fr/viz-bin/VizieR?-source=II/360
==========================================================================
drwxr-xr-x 351 cats archive 8192 Mar 25 10:13 [Up]
drwxr-xr-x 4 cats archive 4096 Jan 8 16:58 [TAR file]
-rw-r--r-- 1 cats archive 462 Jan 8 16:57 .message
-r--r--r-- 1 cats archive 7370 Feb 20 2020 ReadMe
-rw-r--r-- 1 cats archive 2612 Jan 8 16:57 +footg5.gif
-rw-r--r-- 1 cats archive 38038 Jan 8 16:57 +footg8.gif
-r--r--r-- 1 cats archive 332000 Feb 20 2020 catalog.sam
-r--r--r-- 1 cats archive 11099418201 Jun 4 2019 catalog.txt.gz [Uncompressed]
-rw-r--r-- 1 cats archive 601920 Aug 22 2022 tab_2360_1_II_360_catalog.moc.fits Beginning of ReadMe :II/360 Gaia DR2 x AllWISE catalogue (Marton+, 2019)
================================================================================
Identication of Young Stellar Object candidates in the Gaia DR2 x AllWISE
catalogue with machine learning methods.
Marton G., Abraham P., Szegedi-Elek E., Varga J., Kun M., Kospal A.,
Varga-Verebelyi E., Hodgkin S., Szabados L., Beck R., Kiss Cs.
<Mon. Not. R. Astron. Soc., 487, 2522-2537 (2019)>
=2019MNRAS.487.2522M
=2019yCat.2360....0M
================================================================================
ADC_Keywords: Surveys ; Photometry, G band ; Photometry, infrared ;
Cross identifications
Keywords: accretion, accretion discs - methods: data analysis -
methods: statistical - astronomical data bases: Gaia -
stars: evolution - stars: pre-main-sequence -
stars: variables: T Tauri, Herbig Ae/Be
Abstract:
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% prob- ability
threshold we identified 1 129 295 YSO candidates. To demonstrate the
quality and potential of our YSO catalogue, here we present two
applications of it. (1) We explore the 3D structure of the Orion A
star forming complex and show that the spatial distribution of the
YSOs classified by our procedure is in agreement with recent results
from the literature. (2) We use our catalogue to classify published
Gaia Science Alerts. 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. However, in many cases the physical nature of the
published alert sources are not known. A cross-check with our new
catalogue shows that about 30% more of the published Gaia alerts can
most likely be attributed to YSO activity. The catalogue can be also
useful to identify YSOs among future Gaia alerts.
Description:
We presented a classification of those sources in the Gaia DR2
catalogue that have a counterpart in the All-WISE catalogue.