11institutetext: Konkoly Observatory, Research Centre for Astronomy and Earth
Sciences, Eötvös Loránd Research Network (ELKH), H-1121 Budapest, Konkoly
Thege Miklós Út 15-17., H-1121, Hungary
11email<EMAIL_ADDRESS>22institutetext: CSFK, MTA Centre of
Excellence, Budapest, Konkoly Thege Miklós Út 15-17., H-1121, Hungary
33institutetext: ELTE Eötvös Loránd University, Institute of Physics, Pázmány
Péter sétány 1/A, H-1117 Budapest, Hungary 44institutetext: Max Planck
Institute for Astronomy, Königstuhl 17, D-69117 Heidelberg, Germany
55institutetext: Department of Astronomy, University of Geneva, Chemin
d’Ecogia 16, 1290 Versoix, Switzerland 66institutetext: Department of
Astronomy, University of Geneva, Chemin Pegasi 51, 1290 Versoix, Switzerland
77institutetext: RHEA for European Space Agency (ESA), Camino bajo del
Castillo, s/n, Urbanizacion Villafranca del Castillo, Villanueva de la
CaÃ±ada, 28692 Madrid, Spain 88institutetext: Sednai Sàrl, Geneva, Switzerland
99institutetext: Université de Caen Normandie, Côte de Nacre Boulevard
Maréchal Juin, 14032 Caen, France 1010institutetext: European Space Agency
(ESA), European Space Astronomy Centre (ESAC), Camino bajo del Castillo, s/n,
Urbanizacion Villafranca del Castillo, Villanueva de la Cañada, 28692 Madrid,
Spain

#  Gaia Data Release 3

Validating the classification of variable young stellar object candidates

Gábor Marton Gaia Data Release 3Gaia Data Release 3Gaia Data Release 3Gaia
Data Release 3 Péter Ábrahám Gaia Data Release 3Gaia Data Release 3Gaia Data
Release 3Gaia Data Release 3Gaia Data Release 3Gaia Data Release 3 Lorenzo
Rimoldini Gaia Data Release 3Gaia Data Release 3 Marc Audard Gaia Data Release
3Gaia Data Release 3Gaia Data Release 3Gaia Data Release 3 Mária Kun Gaia Data
Release 3Gaia Data Release 3Gaia Data Release 3Gaia Data Release 3 Zsófia Nagy
Gaia Data Release 3Gaia Data Release 3Gaia Data Release 3Gaia Data Release 3
Ágnes Kóspál Gaia Data Release 3Gaia Data Release 3Gaia Data Release 3Gaia
Data Release 3Gaia Data Release 3Gaia Data Release 3Gaia Data Release 3Gaia
Data Release 3 László Szabados Gaia Data Release 3Gaia Data Release 3Gaia Data
Release 3Gaia Data Release 3 Berry Holl Gaia Data Release 3Gaia Data Release
3Gaia Data Release 3Gaia Data Release 3 Panagiotis Gavras Gaia Data Release
3Gaia Data Release 3 Nami Mowlavi Gaia Data Release 3Gaia Data Release 3Gaia
Data Release 3Gaia Data Release 3 Krzysztof Nienartowicz Gaia Data Release
3Gaia Data Release 3 Grégory Jevardat de Fombelle Gaia Data Release 3Gaia Data
Release 3 Isabelle Lecoeur-Taïbi Gaia Data Release 3Gaia Data Release 3 Lea
Karbevska Gaia Data Release 3Gaia Data Release 3Gaia Data Release 3Gaia Data
Release 3 Pedro Garcia-Lario Gaia Data Release 3Gaia Data Release 3 Laurent
Eyer Gaia Data Release 3Gaia Data Release 3

(Received – –, 2022; accepted – –, 2022)

###### Abstract

Context. The Gaia third Data Release (DR3) presents the first catalogue of
full-sky variable young stellar object (YSO) candidates observed by the Gaia
space telescope during the initial 34 months of science operations.

Aims. Numerous types of variable stars were classified using photometric data
collected by Gaia. One of the new classes presented in the Gaia DR3 is the
class of YSOs showing brightness variability. We analysed 79 375 sources
classified as YSO candidates in order to validate their young nature and
investigate the completeness and purity of the sample.

Methods. We cross-matched the Gaia DR3 YSO sample with numerous catalogues
from the literature, including YSO catalogues based on optical and infrared
data, as well as catalogues of extragalactic sources and Galactic variable
stars. YSO catalogues were used to quantify the completeness of the Gaia DR3
YSO sample, while others were inspected to calculate the contamination.

Results. Among the 79 375 potential YSO candidates published in the Gaia DR3
variable star catalogue, the majority of these objects are distributed along
the line of sight of well-known star forming regions and the Galactic
midplane. We find that the upper limit of contamination is 26.7%, depending on
the external catalogue used for the estimation, but find an average of $\sim
10\%$ in general, while the completeness is at the percent level, taking into
account that the Gaia DR3 YSO sample is based on sources that showed
significant variability during the data-collection period. The number of
sources in our sample that had not previously been catalogued as YSO
candidates is $\sim$40 000 objects.

###### Key Words.:

Stars: early-type – Stars: formation – Stars: pre-main sequence – Galaxy:
structure

##  1 Introduction

Gaia (Gaia Collaboration et al., 2016) is a cornerstone mission of the
European Space Agency. The mission is not only the most ambitious stellar (and
extragalactic) astrometric project ever, but also one of the best transient
discovery machines today. While other surveys, such as YSOVAR (Morales-
Calderón et al., 2011), ASAS-SN (Shappee et al., 2014; Kochanek et al., 2017),
and ZTF (Masci et al., 2019), provide photometric data and light curves for
millions of sources, including young stellar objects (YSOs), Gaia has the
advantage of observing the whole sky. It collects photometric observations of
some 1.8 billion stars down to a faint limit of 20.7 mag in the $G$ band and
obtains low-resolution spectra down to $\sim$19 mag for an average of $\sim$80
epochs during the nominal five-year mission (which was completed and then
extended until the end of 2022; hopefully it will be extended to the end of
2025 but this remains to be confirmed), although the cadence is highly
dependent on the scanning law (Gaia Collaboration et al., 2016). Gaia started
monitoring the whole sky on 25 July 2014 and collects multi-epoch multi-band
spectrophotometry and astrometric data for sources crossing its two fields of
view (FoVs). A description of the Gaia mission (spacecraft, instruments,
survey, and measurement principles) as well as the structure and activities of
the Gaia Data Processing and Analysis Consortium (DPAC) can be found in Gaia
Collaboration et al. (2016). The Gaia Data Release 3 (DR3) became public on 13
June 2022, and among many different products that have the potential to
increase our fundamental understanding of the Galaxy it provides photometry in
three passbands (Gaia $G$, $G_{BP}$, and $G_{RP}$), five-parameter astrometry,
and radial velocities (RVs) collected over the initial 34 months of
observations; these are the most relevant quantities for our case. A summary
of the Gaia DR3 contents and survey properties is provided in Gaia
Collaboration et al. (2022).

One important research area, where collecting large amounts of data brings
fundamental new results, is star formation. How the Sun —and stars in general—
was born is identified as one of the most important questions of modern
astronomy. Throughout their early evolution, stars show different features in
their spectral energy distribution (SED). Initially, protostars are deeply
embedded in their parental clouds, surrounded by dense dust and gas envelopes,
which allow their detection only at sub-millimetre (mm) and far-infrared (FIR)
wavelengths. At later stages when the envelope dissolves, young stars become
apparent at optical wavelengths as well, which allows us to detect them with
the Gaia space telescope. However, at these evolutionary stages they still
have circumstellar matter, their protoplanetary discs are still evolving, the
stellar magnetosphere drives accretion columns, and accretion shocks are seen,
all of which lead to variability in their emitted light, which can be studied
to infer the underlying physics of star and planet formation.

Gaia scans the sky repeatedly with successive observations following an
irregular sequence in time —based on the scanning law— on a timescale from
hours to months, and with a varying number of FoV transits depending on the
celestial location (e.g. see Appendix A of Eyer et al., 2017). This allows the
construction of light curves, which can be analysed for variability. More
details about the general variability processing in Gaia DR3 are published in
Eyer et al. (2022). Variability in YSOs occurs on timescales that span a wide
range and depend on the physical processes (see Hillenbrand & Findeisen, 2015;
Fischer et al., 2022). Circumbinary disc occultations last for $\sim$100 days
and can cause dimmings of up to 4 mag. The EX Lup-type outbursts occur on a
timescale of couple of hundred days and can also cause brightenings of 2–4
mag, while FU Ori-type outbursts last even longer and cause brightenings of
even greater magnitude (see e.g. Audard et al., 2014). These latter are
therefore also a potential target of Gaia observations.

In this study, we focus on a new class introduced in the Gaia DR3 variability
classification, the class of YSOs, for which the classification process
resulted in a list of 79 375 candidates. This output of the classification
process was used in the current study. Our goal was threefold: (1) to validate
their young nature, (2) to put constraints on the completeness of the
catalogue, and (3) to check the purity and estimate the level of
contamination. Having a large and reliable catalogue of variable YSOs can help
further studies by providing a list of potential targets for more detailed
analysis. Such analyses can be used to infer the underlying physics of the
star and disc evolution, and their interaction.

##  2 Data

###  2.1 Gaia data

Gaia DR3 represents a significant improvement over Gaia DR2. The parallax
precisions increased by 30 percent and proper motion precision improved by a
factor of 2. Also, the systematic errors on the astrometry are lower by
30%–40% for the parallaxes, while those on the proper motions are lower by a
factor $\sim$2.5. The longer temporal baseline of the observations also
resulted in increased precision of the photometry and much better homogeneity
across colour, magnitude, and celestial position. While Gaia measures the
position and brightness of the objects in its FoV, many parameters are
provided that describe the quality of the data. Through the variability
processing pipeline (Eyer et al., 2022), many other parameters are derived,
which are helpful during the identification of variable sources and their
verification.

One of the Gaia DR3 products is the supervised classification of variable
sources (Rimoldini et al., 2022). Supervised classification was applied to
classify several variability types using per-FoV epoch photometry in the three
Gaia bands. Among the 60 000 training sources, 5148 were YSOs and included
subtypes such as T Tauri stars (classical, weak-lined, intermediate mass of
types F to early G, and late G to early K types), FU Orionis, Herbig Ae/Be,
and UX Orionis type stars. The time series were characterised by about two
dozen features (described in sect. 10.3.3 of Rimoldini, L. et al., 2022),
which were used to train classifiers employing Random Forest (Breiman, 2001)
and XGBoost (Chen & Guestrin, 2016) algorithms.

The results of this supervised classification were verified in a post-
processing phase, where the parameter space was analysed in order to maximise
the purity of the sample and minimise its contamination. Several cuts were
applied to variability parameters and astrometric values, such as parallax
errors and proper motion, to exclude sources that have distances that are too
small or too large to be taken into account as potential young stars (see
Rimoldini et al., 2022, for details).

###  2.2 KYSO catalogue

To help the identification of YSOs among the Gaia DR3 variable stars, we
created a catalogue, the Konkoly Optical YSO (hereafter KYSO) catalogue111The
KYSO table is only available in electronic form at the CDS via anonymous ftp
to cdsarc.cds.unistra.fr (130.79.128.5) or via
https://cdsarc.cds.unistra.fr/cgi-bin/qcat?J/A+A/., part of which served as a
training sample for the supervised classification of Gaia DR3 variable stars
(Rimoldini et al., 2022) and was also used in the post-processing verification
phase. The KYSO contains nearly 12 000 objects, which are carefully selected
young stars identified in the optical domain, and their young nature is mostly
confirmed using spectroscopic data. More details about how the KYSO catalogue
was compiled are described in Appendix A. The KYSO catalogue is published as a
Vizier table so that future classification studies can benefit from it. The
KYSO catalogue was also used as a first step in our validation process and a
detailed analysis was performed. We note that the KYSO catalogue has evolved
since it was provided for training purposes for the supervised classification,
as new sources have been added, and less reliable YSOs removed in order to
increase the reliability of the catalogue.

###  2.3 Other catalogues

We used several existing YSO catalogues from the literature based on optical
and infrared surveys and observations, including data from Gaia DR2, infrared
data from 2MASS, and the Spitzer and WISE surveys. These catalogues are the
Marton et al. (2019) probabilistic YSO catalogue, based on Gaia DR2 optical
data, 2MASS near-infrared (NIR) photometry, and WISE mid-infrared (MIR)
observations from the AllWISE catalogue, the SPICY (Spitzer/IRAC Candidate
YSO) catalogue of Kuhn et al. (2021) based on MIR observations of Spitzer, and
the Großschedl et al. (2018) study of Orion A based on the ESO–VISTA NIR
survey. While the Gaia DR3 YSO candidate sample is based on optical
variability, the listed catalogues from the literature used the IR excess in
the SED as a signature of the young nature. We also cross-matched the Gaia DR3
YSO candidates with the SIMBAD database (Wenger et al., 2000) and other large
catalogues listing extragalactic sources and other types of variable stars
identified in the optical domain, as these sources can show colours and light-
curve features that are similar to those of YSOs. Based on the results of the
cross-matches we calculated an estimated completeness and purity for the Gaia
DR3 YSO candidates.

It is important to note that the Gaia observations were of different angular
resolution and sensitivity when compared to other observations in the
literature. The 2MASS survey (Skrutskie et al., 2006) collected NIR data in
the $J$ (1.2 $\mu$m), $H$ (1.65 $\mu$m), and $K_{s}$ (2.16 $\mu$m) bands; the
system PSF was $\sim 2\aas@@fstack{\prime\prime}5$, and the average limiting
magnitude was $\sim$14\. The WISE mission (Wright et al., 2010) observed the
whole sky with an angular resolution $6\aas@@fstack{\prime\prime}1$,
$6\aas@@fstack{\prime\prime}4$, $6\aas@@fstack{\prime\prime}5$, and
$12\aas@@fstack{\prime\prime}0$ at 3.4, 4.6, 12, and 22 $\mu$m, respectively.
For the WISE data, we used the AllWISE catalogue, which is ¿95% complete for
sources with W1¡17.1 and W2¡15.7 mag. These differences and the apparent
motions of several objects make it difficult to simply cross-match such large
catalogues and make it challenging to avoid source confusion. In the case of
the AllWISE catalogue, 2MASS data are already included, where the position
reconstruction was done using bright 2MASS point sources as the astrometric
reference. For AllWISE, the proper motion of the reference stars in the 11
years separating the WISE and 2MASS surveys has been integrated into the
solutions to improve the absolute astrometric
accuracy222https://wise2.ipac.caltech.edu/docs/release/allwise/expsup/sec2_1.html.
The cross-match of the Gaia DR2 and the AllWISE catalogues was done by Marrese
et al. (2019). In cases where we used 2MASS and AllWISE data for the
validation, we relied on these catalogues, matched the Gaia DR3 YSO sources to
the DR2 positions, and inferred the data from the DR2xAllWISE (including
2MASS) table. In other cases, when the cross-match with such accuracy was not
already available, we used the TOPCAT software (Taylor, 2005) with a search
radius of 1$\arcsec$.

##  3 Validation

In this section, we consider three different aspects of the validation. In
Section 3.1, we compare the parameters of the Gaia DR3 YSO sample to those of
objects listed in different YSO catalogues from the literature in order to
validate the young nature of the Gaia DR3 objects. These catalogues are based
on different domains of the electromagnetic spectrum. The KYSO is based on
optical data, the Großschedl et al. (2018) uses NIR data, the Kuhn et al.
(2021) is based on MIR data, and finally the Marton et al. (2019) used
optical, NIR, and MIR photometry. We also investigate the distance
distributions of the Gaia DR3 YSOs on the all-sky and in individual star
forming regions and compare them to literature values.

In Section 3.2, we estimate the completeness of the Gaia DR3 YSO candidates by
comparing the total number of the sources listed in a given YSO catalogue to
the number of Gaia DR3 counterparts (meaning Gaia actually observed these
sources), to the number of counterparts that were part of the classification
process (for sufficiently sampled signals that were considered as variable in
Gaia DR3), and to the number of counterparts existing in the final Gaia DR3
YSO sample.

In Section 3.3, we estimate the contamination level of the Gaia DR3 YSO
sources by matching them to catalogues listing a specific type of objects,
mostly identified in the optical domain to make the comparison reasonable.

###  3.1 The young nature of the Gaia DR3 YSO candidates

Figure 1: Observational HRD of Gaia DR3 YSOs (red dots) and reference sources
based on 4.2 million Gaia objects (black dots) selected based on their highly
reliable parallax, sufficient S/N in both BP and RP bands, and the
sufficiently high number of data points in their light curves. The Gaia DR3
YSOs occupy a specific region above the main sequence and below the giant
branch. The contour levels are at 5%, 25%, 45%, 65%, and 85% of the maximum
density value. In the comparison with other catalogues, we use only the
contours of the DR3 distribution for better visibility of the underlying data
points.  Figure 2: Gaia DR3 YSOs on the 2MASS colour–colour diagram. The
contour levels are at 5%, 25%, 45%, 65%, and 85% of the maximum density value.
In the comparison with other catalogues, we use only the red contours of the
DR3 distribution for better visibility of the underlying data points. The
median, mean, standard deviation, and 5% and 95% quantiles of both colours are
listed in Table 1.

####  3.1.1 Cross-match with the KYSO catalogue

As a first step of the validation of the Gaia DR3 YSO candidate sample, we
cross-matched it with the KYSO catalogue. The KYSO catalogue provides a strong
bias as the sources included are from various catalogues and from well-known
star forming regions, while Gaia provides a relatively homogeneous all-sky
survey.

Figure 3: DR3 YSO sample (red dots) and the KYSO objects (blue dots) presented
in Hammer-Aitoff projection in Galactic coordinates. The KYSO sample is
heavily biased as it lists sources from well studied star forming regions,
while Gaia is an unbiased all-sky survey, and therefore Gaia DR3 YSO
candidates can be seen in all directions. YSO candidates are seen at high
Galactic latitudes ($|b|\geq 30\degr$), their number is 940, which is only
1.2% of all the candidates. The median distance of these high-latitude sources
is 363.6 pc, and 95% of them are within a distance of 869.4 pc.

In the case of a good classification, one would expect to see that YSOs occupy
the same regions on the observational HRD and also on the various
colour–colour diagrams. YSOs are seen in specific regions of the sky, and
therefore we expect overdensities in the YSO candidate surface density
distribution in the line of sight of the (1) regions where the training sample
showed overdensities and (2) the known star forming regions and the Galactic
midplane. Figure 3 shows their distribution on the sky in Galactic
coordinates, which clearly reflects the expected distribution.

As a next step, we checked the location of the Gaia DR3 YSO sources and that
of the KYSO objects on the observational Hertzsprung–Russell Diagram (HRD,
often referred to as simply the colour–magnitude diagram). We note here that
HRDs in this study are not corrected by Galactic extinction or reddening.
Figure 4 shows how the KYSOs are distributed in the median $G_{\rm BP}-G_{\rm
RP}$ colour versus $G$ band absolute magnitude diagram. As explained in
Bailer-Jones et al. (2021), a simple inversion of the parallax values does not
give a precise distance, because the inversion can lead to bias. Therefore,
the $G$ band absolute magnitudes were calculated using their distance values
obtained from the Bailer-Jones et al. (2021) distance catalogue instead of the
parallax listed in the Gaia DR3. In general, YSOs are mostly located above the
main sequence, but depending on their mass and evolutionary stage, they can
appear in other parts of the HRD as well (see Section 3.2.1). The Gaia DR3
YSOs are located in a smaller region on the HRD, but highly overlapping with
the KYSO catalogue, which shows that the classification process successfully
identified those candidates that are located in the same place as the majority
of the KYSOs.

Figure 4: Observational HRD of Gaia DR3 YSOs (red contours), KYSOs (blue dots
and blue contours), and reference sources (grey dots) as described in the
caption of Fig. 1. Most of the KYSOs are located above the main sequence, but
other parts of the HRD are also covered. The probability distributions of the
$G_{\rm BP}-G_{\rm RP}$ colour and the $G_{\mathrm{Abs}}$ are shown in Figs.
21 and 25. The main parameters of the distributions are listed in Table 1.

There are only a few sources located at the blue side of the HRD. The $G_{\rm
BP}-G_{\rm RP}$ colour distribution is shown in Fig. 21. While the histograms
show similarities, it is seen that there are more KYSOs at the blue end of the
diagram, where mostly high-mass YSOs and Ae/Be stars, are located. This means
that the YSO classification was more sensitive to the redder, fainter, and
lower-mass objects, because very few training objects were included below the
main sequence, and also because of the strong competition with other classes
at the blue end.

We also analysed the Gaia $G$ band absolute magnitude distribution of the KYSO
sources and that of the sources classified as Gaia DR3 YSOs; the results are
shown in Fig. 25. The distribution of KYSO sources is wider than that of the
Gaia DR3 YSOs, but the two samples show a significant overlap.

To see the IR excess distribution of the KYSOs and the Gaia DR3 YSOs, we
cross-matched them with the 2MASS catalogue using a 1$\arcsec$ matching
radius. Of the 79 375 Gaia DR3 YSOs, 76 879 (97%) had a NIR counterpart, while
10 613 (91%) of the 11 665 KYSOs had a match in the 2MASS database.

Figure 5 shows the distributions of the Gaia DR3 YSO candidates and the KYSO
sources on the 2MASS $J-H$ versus $H-K_{s}$ colour–colour diagram. Both
samples occupy the same region on the diagram, and are mostly located between
$0<J-H<1.5$ and $0<H-K_{s}<1$.

Figure 5: KYSO sources (blue dots) and Gaia DR3 YSOs (red contours) on the
2MASS colour–colour diagram. The median, mean, standard deviation, and 5% and
95% quantiles of both colours are listed in Table 1. The colour probability
distributions are shown in Fig. 29 and 33. The main parameters of the
distributions are listed in Table 1.

Further details of the above-mentioned distributions are listed in Table 1,
where we list the median and mean values, the standard deviation, and the
threshold values below and above which 5% of the samples are located. Figures
showing the distributions are found in Appendix B.

We also investigated the distance distribution of the KYSOs and Gaia DR3 YSOs
based on the values of the median photogeometric distance posterior listed for
Gaia EDR3 by Bailer-Jones et al. (2021). While the overall distributions of
the distance values show strong similarities, the KYSO catalogue shows a small
excess of very nearby stars (¡100 pc); see Fig. 6.

Figure 6: Distance distribution of KYSO sources (blue bars) and of sources classified as Gaia DR3 YSOs (red bars). The values show strong similarities, except that there are more KYSOs within 100 pc of the Sun. These nearby KYSO sources (87 have distances of smaller than 100 pc) are mostly members of the TW Hydrae association. There are also three strong peaks in the distance distribution. The first one, between $\sim$125 and $\sim$175 pc, corresponds to the Ophiuchus, Sco OB2 association, and Taurus regions. The second strong peak is seen at distances of between $\sim$300 and $\sim$500 pc. The vast majority of these sources are located in Orion. The third peak is between $\sim$300 and $\sim$1000 pc. These sources are also seen towards Orion and towards the Galactic midplane as well.  Table 1: Median, mean, standard deviation, and 5% and 95% quantiles of the $G_{\rm Abs}$, $G_{\rm BP}-G_{\rm RP}$, $J-H$ and $H-K_{s}$ distributions of the Gaia DR3 YSO sample and other public catalogues used for the validation process. Each quantity is presented in magnitudes. Histograms for each sample and each quantity are presented in Appendix B. Parameter | Median | Mean | Stdev | 5% | 95%
---|---|---|---|---|---
| DR3 YSO candidate
$G_{\rm Abs}$ | 7.623 | 7.506 | 1.854 | 4.384 | 10.316
$G_{\rm BP}-G_{\rm RP}$ | 2.770 | 2.748 | 0.601 | 1.749 | 3.697
$J-H$ | 0.746 | 0.791 | 0.235 | 0.513 | 1.195
$H-K_{s}$ | 0.287 | 0.318 | 0.180 | 0.152 | 0.589
| KYSO
$G_{\rm Abs}$ | 7.764 | 7.609 | 2.431 | 3.321 | 11.281
$G_{\rm BP}-G_{\rm RP}$ | 2.569 | 2.534 | 0.879 | 0.935 | 3.889
$J-H$ | 0.796 | 0.881 | 0.368 | 0.495 | 1.549
$H-K_{s}$ | 0.377 | 0.455 | 0.306 | 0.143 | 1.025
| G19 Großschedl et al. (2019)
$G_{\rm Abs}$ | 9.838 | 8.594 | 1.990 | 5.133 | 11.351
$G_{\rm BP}-G_{\rm RP}$ | 2.562 | 2.465 | 0.884 | 0.778 | 3.709
$J-H$ | 0.951 | 1.203 | 0.745 | 0.568 | 2.778
$H-K_{s}$ | 0.549 | 0.719 | 0.521 | 0.246 | 1.783
| SPICY Kuhn et al. (2021)
$G_{\rm Abs}$ | 6.228 | 6.024 | 1.657 | 2.947 | 8.386
$G_{\rm BP}-G_{\rm RP}$ | 2.754 | 2.777 | 0.752 | 1.580 | 4.066
$J-H$ | 1.372 | 1.459 | 0.657 | 0.552 | 2.673
$H-K_{s}$ | 0.899 | 1.008 | 0.606 | 0.287 | 2.166
| M19 Marton et al. (2019)
$G_{\rm Abs}$ | 6.182 | 6.546 | 2.191 | 3.608 | 10.705
$G_{\rm BP}-G_{\rm RP}$ | 2.709 | 2.466 | 0.811 | 1.173 | 3.491
$J-H$ | 0.873 | 0.845 | 0.340 | 0.353 | 1.394
$H-K_{s}$ | 0.384 | 0.383 | 0.217 | 0.100 | 0.758

####  3.1.2 Cross-match with the Marton et al. (2019) YSO catalogue

In Marton et al. (2019) (referred to hereafter as the M19 catalogue), 101
million objects were classified from the DR2xAllWISE cross-match table into
four main categories (evolved stars (E), main sequence stars (MS),
extragalactic sources (EG), and YSOs (Y)) with the help of a Random Forest
classifier, and class membership probabilities were assigned to each source.
Koenig & Leisawitz (2014) investigated the spurious detections in the WISE W3
and W4 bands. Because M19 was heavily reliant on the WISE data, the
reliability of the W3 and W4 photometry values was also investigated. Another
Random Forest classifier was built to decide whether the W3 and W4 band
detections are spurious or reliable, and a probability value $R$ was given for
each detection, as detailed in Section 2.7 in Marton et al. (2019). If $R\geq
0.5$, one can assume that the W3 and W4 band photometry can be used and the
$LY$ probability values are used from the M19 sample, which gives the
probability that a source is a YSO; in the $LY$ acronym, the letter $Y$ refers
to YSO, while the letter $L$ refers to the inclusion of longer wavelength W3
and W4 bands in the classification. In cases where $R<0.5$, the $SY$ (where
the letter $S$ refers to the shorter wavelength W1 and W2 bands; in these
cases the WISE W3 and W4 bands were not part of the classification process)
probability was taken into account.

Based on the probability values, one can define a threshold above which one
feels confident to accept the source as a reliably classified object. For
analysing the properties of the Gaia DR3 sources and comparing it to the M19,
we used YSOs from the M19 catalogue, where $R\geq 0.5$ and $LY\geq 0.95$, or
$R<0.5$ and $SY\geq 0.95$, meaning 259 363 sources in total.

The observational HRD of the M19 and Gaia DR3 YSO candidates are shown in Fig.
7. Similarly to the comparison with the KYSOs, the Gaia DR3 YSO candidates
also show significant overlap with the distribution of the M19 sources, but
the M19 distribution shows additional peaks at the bluer and brighter part of
the HRD as well as close to the giant branch. The bright-blue tail of the
distribution can be explained by the less accurate training sample used in the
Marton et al. (2019) study, which allowed more evolved sources to be
classified as YSOs with relatively high probability without the long-
wavelength $W3$ and $W4$ measurements of the WISE telescope. The peak close to
the giant branch is also due to the uncertainty in the distance estimation of
the source, and therefore these sources may appear more distant than they
actually are. However, as listed in Table 1, 5% of the Gaia DR3 YSO candidates
are fainter than $\sim 10.3$ mag, while in the M19 catalogue this quantile
value is $\sim 10.7$ mag. The 5% quantile value at the bright end for the Gaia
DR3 YSO candidates is $\sim 4.4$ mag, while for the M19 YSOs, the same
threshold is at $\sim 3.6$ mag. Therefore, these differences cannot be
considered significant.

Figure 7: Same as Fig. 4 but for the Gaia DR3 (red contours) and M19 YSO
candidates with $R\geq 0.5$ and $LY\geq 0.95$, or $R<0.5$ and $SY\geq 0.95$
(green dots and contours). The probability distributions are shown in Figs. 24
and 28. The main parameters of the distributions are listed in Table 1.
Because the Gaia DR3 YSO distribution is narrower, for better visibility we
plotted them on the top of the M19 distribution.

On the 2MASS J$-$H versus H$-$Ks colour–colour diagram (Fig. 8), the Gaia DR3
YSOs are located in the same region as the M19 objects, but only show one
maximum in the distribution, unlike the M19 sources, which show bimodality. As
explained earlier, the method used for the M19 classification allowed more
evolved objects to be classified as YSOs with relatively high probability when
the long-wavelength WISE measurements were not taken into account.

Figure 8: Same as Fig. 5, but for the M19 sources (green dots and contours)
and Gaia DR3 YSO candidates (red contours). The colour probability
distributions are shown in Figs. 32 and 36, and the main parameters of the
distributions are listed in Table 1.

####  3.1.3 Cross-match with the Kuhn et al. (2021) YSO catalogue

Based on Spitzer space telescope surveys of the Galactic midplane between
$l\sim 255\degr$ and $110\degr$, including the GLIMPSE I, II, and 3D,
Vela–Carina, Cygnus X, and SMOG surveys (613 square degrees), Kuhn et al.
(2021) published a probabilistic YSO catalogue, the SPICY catalog. These
authors presented 117 446 Spitzer/IRAC candidate YSOs.

Because Spitzer observes the IR domain, it is an ideal tool for YSO discovery.
Therefore, it is expected that more of the YSOs in the SPICY catalogue are in
the earlier stages of evolution, showing more IR excess. Also, because the
SPICY contains sources seen towards the Galactic midplane, where the amount of
interstellar dust is very high and obscures the visible light, one can expect
that only the brighter, higher-mass YSOs are seen with Gaia. Figure 9 shows
the HRD for the Gaia DR3 YSO candidates and SPICY YSOs. The overlap is
significant, but we see more Gaia DR3 YSO candidates in the 3 ¡ $G_{\rm
BP}-G_{\rm RP}$ ¡ 4.5 and 5 ¡ $G_{\mathrm{Abs}}$ ¡ 10 region. These are
objects in nearby star forming regions and only a few of them are located in
the region covered by the SPICY catalogue. While the median $G_{\mathrm{Abs}}$
brightness of the Gaia DR3 YSOs is 7.6 mag, the SPICY objects are brighter by
1 mag, and the median value is 6.2 magnitude. The median value of the $G_{\rm
BP}-G_{\rm RP}$ is very similar, 2.7 for both samples.

Figure 9: DR3 YSO candidates (red contours) and SPICY YSOs (cyan dots and
contours) on the HRD. The $G_{\rm BP}-G_{\rm RP}$ and $G_{\rm Abs}$
distributions are shown in Figs. 23 and 27, and the main parameters of the
distributions are listed in Table 1.

The 2MASS colour–colour distribution is shown in Fig. 10. As expected, the
SPICY objects cover a larger area on the diagram. While the median $J-H$
colour of the Gaia DR3 YSOs is 0.7 mag, this value is 1.4 mag for the SPICY
objects. This difference is also seen in the median value of the $J-K_{s}$
colour distribution, as the median value for the Gaia DR3 YSO candidates is
0.3 magnitude while it is 0.9 for the SPICY objects.

Figure 10: SPICY sources (cyan dots and contours) and Gaia DR3 YSOs (red
contours) on the 2MASS colour–colour diagram. The $G_{\rm BP}-G_{\rm RP}$ and
$G_{\rm Abs}$ distributions are shown in Figs. 31 and 35, and the main
parameters of the distributions are listed in Table 1.

####  3.1.4 Cross-match with the Großschedl et al. (2019) paper

Großschedl et al. (2018) used the Gaia DR2 distances of MIR-selected YSOs in
the benchmark giant molecular cloud Orion A to infer its 3D shape and
orientation based on the ESO–VISTA NIR survey. At a later stage, an updated
source list was published in Großschedl et al. (2019). We used this source
list (hereafter G19) to match our sources to YSOs in the Orion A star forming
region.

Again, as a first step, we checked the observational HRD and analysed the
location of the objects shown in Fig. 11. The G19 YSOs are seen not only above
the main sequence, but also in the region between the main sequence and the
location of the white dwarfs. This feature of their distribution is discussed
in Section 3.2.1. It is also clear from Fig. 11 that the G19 objects tend to
have lower $G_{\mathrm{Abs}}$ values. As listed in Table 1, the median
$G_{\mathrm{Abs}}$ of the G19 objects is 9.8 mag, while this value is 7.6 for
the Gaia DR3 YSO candidates. Because the Orion A is a nearby star forming
region with an average distance of $\sim 420$ pc, it is expected that more of
the fainter YSOs are seen with Gaia.

Figure 11: Same as Fig. 4 but for Gaia DR3 (red contours) and G19 (purple dots
and contours) YSO candidates. Histograms of the two parameter distributions
are shown in Figs. 26 and 22. The main parameters of the distributions are
listed in Table 1. The distribution shows strong similarities to that seen in
Fig. 4.

The distributions of G19 sources and Gaia DR3 YSOs on the 2MASS colour–colour
diagram are presented in Fig. 12. The two samples show significant overlap,
except that fewer G19 objects have J$-$H ¡ 0.6 colour, but sources with larger
IR excess are also detected. This can be also explained with the fact that the
Orion A is a nearby system, and therefore those sources that do not emit the
majority of their energy in the optical domain are still observable with Gaia.

Figure 12: G19 sources (purple dots and contours) and Gaia DR3 YSOs (red
contours) on the 2MASS colour–colour diagram. Probability distributions are
shown in Figs. 30 and 34. The main parameters of the distributions are listed
in Table 1.

We also tested the Gaia DR3 YSO sample against the 3D shape of the Orion A
cloud that was analysed in Großschedl et al. (2018). Figures 13 and 14 clearly
show that the median distance values for the Gaia DR3 YSO sample as a function
of Galactic longitude are in very good agreement with the findings of these
latter authors, and we can confirm that the Orion A cloud is an elongated
structure with its head part closer to us and its tail at a greater distance
towards higher longitude values.

Figure 13: Distance of the Gaia DR3 YSO candidates (red dots) and the
Großschedl et al. (2018) YSOs (black dots) as a function of Galactic
longitude. Large dots represent the $med(D)$, which is median of the
individual distance values in $0.25\degr$ bins, while error bars represent the
$med(D-D_{L})$ and $med(D-D_{U})$, where $D_{L}$ and $D_{U}$ are the lower and
upper limits of the individual distance values of the Gaia DR3 YSO candidates
(blue dots) and of the Großschedl et al. (2018) YSOs (green dots).  Figure 14:
Distances of the DR3 YSO candidates versus those of the G19 YSOs in the star
forming region Orion A. The error bars represent the same values as in Fig.13.

####  3.1.5 Distances of star forming regions

Zucker et al. (2019) presented a uniform catalogue of accurate distances to
local molecular clouds based on Gaia DR2. These authors used a sophisticated
method to derive distances to 27 nearby star forming clouds, and reported
upper and lower corner coordinates of regions in which they calculated average
distances based on Gaia astrometry and optical–NIR photometry. In this
comparison, we simply calculated a median distance of the Gaia DR3 YSOs based
on the distance values of Bailer-Jones et al. (2021). The values are listed in
Table 2. As shown in Fig. 15, with the exception of two regions, the Gaia DR3
YSO results are in good agreement with the findings of Zucker et al. (2019).

The two exceptions are the Gem OB1 and the Maddalena regions. In the case of
the Gem OB1, the reported distance was 1786$\pm$89 pc, while the Gaia DR3 YSO
sources showed a strong peak between 320 and 450 pc, and the farthest object
was found to be at a distance of 1067.5 pc. In the direction of the Maddalena
star forming region, we also see a peak in the distance distribution between
320 and 420 pc and the farthest object being at a distance of 1079.5 pc. For
the case of Maddalena, it is known that despite its large mass, only low level
star formation is happening in the cloud (e.g. see Schneider et al., 2015).

Figure 15: Median distance of Gaia DR3 YSOs in regions defined by Zucker et al. (2019) versus the distances reported by these latter authors based on Gaia DR2 data. Horizontal error bars represent the standard deviation of distances of Gaia DR3 YSOs in the given region. Vertical error bars are the systematic errors given in Table 1 of Zucker et al. (2019).  Table 2: Distances of star-forming clouds based on the Gaia DR3 YSO sample in comparison with those reported by Zucker et al. (2019). Cloud name | DR3 median | DR3 parallax | B.-J.(2021) | B.-J.(2021) | Zucker et al. | Zucker et al. | DR3 YSO
---|---|---|---|---|---|---|---
| parallax [mas] | MAD [mas] | med. dist. [pc] | dist. MAD [pc] | dist. [pc] | dist. err. [pc] | member count
AquilaS | 2.473 | 1.581 | 385.138 | 144.398 | 133 | 7 | 62
California | 2.771 | 0.633 | 352.502 | 147.169 | 470 | 24 | 770
Chamaeleon | 2.968 | 1.733 | 337.852 | 253.633 | 183 | 9 | 394
CMaOB1 | 0.892 | 0.188 | 1098.853 | 158.152 | 1209 | 60 | 408
CoronaAustralis | 6.351 | 2.106 | 156.923 | 275.613 | 151 | 8 | 28
Crossbones | 1.051 | 0.304 | 918.044 | 140.597 | 886 | 44 | 176
GemOB1 | 2.348 | 0.931 | 414.320 | 209.351 | 1786 | 89 | 64
Lupus | 6.141 | 2.233 | 161.129 | 267.720 | 189 | 9 | 1059
Maddalena | 2.351 | 0.835 | 398.265 | 207.223 | 2072 | 104 | 17
MonOB1 | 1.373 | 0.175 | 709.091 | 121.870 | 745 | 37 | 577
MonR2 | 1.146 | 0.264 | 844.402 | 132.447 | 778 | 39 | 473
Ophiuchus | 6.978 | 1.435 | 141.990 | 150.515 | 144 | 7 | 791
OrionA | 2.531 | 0.267 | 388.360 | 65.817 | 432 | 22 | 2072
OrionB | 2.439 | 0.457 | 402.371 | 136.768 | 423 | 21 | 854
OrionLam | 2.493 | 0.374 | 393.914 | 87.140 | 402 | 20 | 1075
Perseus | 3.164 | 0.496 | 310.011 | 117.780 | 294 | 15 | 435
Polaris | 1.420 | 0.439 | 682.982 | 174.088 | 352 | 18 | 15
Rosette | 0.950 | 0.581 | 1092.109 | 233.491 | 1304 | 65 | 78
SerpensAqr | 1.576 | 0.470 | 650.556 | 273.240 | 484 | 24 | 1136
Taurus | 4.355 | 2.535 | 232.237 | 260.722 | 141 | 7 | 432
UrsaMajor | 2.154 | 1.596 | 453.741 | 258.613 | 371 | 19 | 12

####  3.1.6 Cross-match with the Gaia Photometric Science Alerts

The KYSO catalogue was also used to improve the classification of the Gaia
Photometric Science Alerts (GSA) (Hodgkin et al., 2021) with other YSO
catalogues from the literature. Still, numerous objects remained unknown among
the alerting sources, including possible YSOs. Therefore, we also checked
which of the Gaia DR3 YSOs were also among the alerts. At the beginning of
February 2022, 478 alerts appeared on the GSA Index
website333http://gsaweb.ast.cam.ac.uk/alerts/alertsindex classified as YSOs or
mentioned in the comment section as possible YSOs from the total of 18 976
alerts. A cross-match revealed that 8905 (46.9%) of them are in the Gaia DR3
catalogue. The number of Gaia DR3 YSO candidates present in the alert list was
found to be 159, which is 33.3% of the possible YSOs alerts. Also, 41 sources
were not identified as confirmed or possible YSOs. In the alert system, these
are listed as mostly unknown, red stars in the direction of the Galactic
midplane. Below, we present a list of YSO alerts that were or are being
investigated with follow-up observations in more detail to infer the
underlying physics of their brightness changes and in uncertain cases to
confirm their YSO nature. The distance estimates for each source are based on
the Gaia EDR3 distance catalogue of Bailer-Jones et al. (2021), while the
probability value of being a YSO is from Marton et al. (2019).

  * •

Gaia22afv ($\alpha_{\rm J2000}$ = 04h 03m 38$\aas@@fstack{s}$86, $\delta_{\rm
J2000}$ = 32$\degr$ 15′ 49$\aas@@fstack{\prime\prime}$93) is a candidate YSO,
which triggered the Gaia Alerts system on 2022 January 18 because of its
brightening by $\sim$0.7 mag. Its distance is $263.7^{+6.5}_{-4.8}$ pc and the
probability of being a YSO is 67.22%

  * •

Gaia18dlf ($\alpha_{\rm J2000}$ = 20h 57m 03$\aas@@fstack{s}$36, $\delta_{\rm
J2000}$ = 43$\degr$ 41′ 44$\aas@@fstack{\prime\prime}$45) is a known YSO,
which had a Gaia alert on 2018 November 19 because of its long-term (on a
timescale of a year) brightening by more than 1 mag. Its distance is
$782^{+31}_{-34}$ pc. Rebull et al. (2011) classified it as a flat-spectrum
source based on the near- to mid-IR SED slope.

  * •

Gaia21egm (or V733 Cep, $\alpha_{\rm J2000}$ = 22h 53m 33$\aas@@fstack{s}$25,
$\delta_{\rm J2000}$ = 62$\degr$ 32′ 23$\aas@@fstack{\prime\prime}$60) is a
known FUor (Reipurth et al., 2007), which triggered a Gaia alert on 2021
September 25 because of a drop in its brightness following a long-term fading.
Its distance is $724.3^{+31.3}_{-26.8}$ pc. It exhibited a slow rise in its
brightness by $\sim$4.5 mag between 1971 and 1993, after which it stayed at
maximum brightness for several decades (Peneva et al., 2010).

  * •

Gaia21arq ($\alpha_{\rm J2000}$ = 05h 34m 28$\aas@@fstack{s}$94, $\delta_{\rm
J2000}$ = $-$05$\degr$ 08′ 38$\aas@@fstack{\prime\prime}$40) is a known YSO,
which triggered a Gaia alert on 2021 February 9, due to its brightening by 0.8
mag. Its distance is $354.6^{+17.7}_{-14.9}$ pc. It is a classical T Tauri
star, which was part of the H$\alpha$ survey of the Orion Nebula Cluster by
Szegedi-Elek et al. (2013).

  * •

Gaia18eap ($\alpha_{\rm J2000}$ = 02h 34m 34$\aas@@fstack{s}$63, $\delta_{\rm
J2000}$ = 61$\degr$ 21′ 53$\aas@@fstack{\prime\prime}$64) is a YSO candidate,
which had a Gaia alert on 2018 December 29 because of its more than 1 mag
brightening. The duration of the brightening event was about a year: the
source returned to its original brightness by early 2020. Its distance is
$980^{+248}_{-189}$ pc. It is classified as a flat-spectrum source (Sung et
al., 2017).

  * •

Gaia21eox ($\alpha_{\rm J2000}$ = 00h 04m 13$\aas@@fstack{s}$63, $\delta_{\rm
J2000}$ = 67$\degr$ 24′ 45$\aas@@fstack{\prime\prime}$50) is a YSO candidate
at a distance of $977.02^{+56.72}_{-53.84}$ pc. It had a Gaia alert on 2021
October 10 because of a 1 mag dimming episode, which ended by January 2022.
Its probability of being a YSO is 98%.

As shown by the list above, the DR3 YSO candidate sample has the potential to
contain eruptive YSOs, which are excellent targets for detailed observations
aiming to better understand the fundamentals of the disc- and planet formation
and evolution.

###  3.2 Completeness

####  3.2.1 Completeness based on the KYSOs

The KYSOs also occupy a region on the observational HRD close to or above the
giant branch and below the main sequence, while the Gaia DR3 YSOs have a
narrower distribution as seen in Fig. 4. After visualising their distances, as
shown in Fig. 16, we realised that many of them are distant objects (plotted
with dark blue or black colours) and also their $\varpi/\sigma_{\varpi}$ value
is below 3, while for the Gaia DR3 YSOs we set a requirement for
$\varpi/\sigma_{\varpi}\geq 3$. This also means that the distance estimates of
the KYSOs are less reliable in some cases and this can cause a less precise
position on the colour–magnitude diagrams. Another feature in the distribution
of the KYSOs on the observational HRD is an overdensity of sources with
$G_{\rm BP}-G_{\rm RP}$ colour between 0 and 1 mag and with an absolute median
$G$ band brightness of between 11 and 5 mag, located between the main and
white dwarf sequences. The vast majority (¿95%) of these sources are located
in the Orion star forming region and have M spectral type, and all are
reported in the study of Hillenbrand et al. (2013). They are most likely YSOs
for which we do not see their photosphere but scattered light from their
protoplanetary discs. At high inclination, when the disc is seen edge-on, the
sources appear to be fainter and bluer than they actually are (Guarcello et
al., 2010). We note that this feature on the colour–magnitude diagram also
appears in Fig. 11, where the literature YSOs are also from the Orion.

Figure 16:  KYSOs on the observational HRD. Colour coding corresponds to the
distance of the individual objects. Grey dots represent the reference objects
on the HRD. Many of the YSOs close to the giant branch or above it seem to be
distant objects. Also, many of them have parallax errors that make the proper
distance estimation problematic, and therefore their position on the diagram
is more uncertain.

As a further step in our investigation, we checked the distribution of the
parallax over its uncertainty ($\varpi/\sigma_{\varpi}$) for those sources
that were included in the Gaia DR3 YSO sample from the KYSO catalogue and the
excluded ones. The distribution of the values is shown in Fig. 17. The
excluded KYSO objects clearly tend to have lower values, meaning that their
parallax is less reliable.

Figure 17: Distribution of parallax over its uncertainty
$\varpi/\sigma_{\varpi}$ for KYSO sources classified as Gaia DR3 YSOs (green
bars) and those KYSOs that were excluded from the final Gaia DR3 YSO candidate
list (grey bars). The vertical red line at $\varpi/\sigma_{\varpi}=3$
indicates the threshold below which we excluded all sources.

In total, 4656 KYSO sources were included in the final Gaia DR3 YSO sample,
which means a $\sim$40% completeness in this comparison. Of the KYSOs, 5 286
were included in the classification process with the supervised classifier
(Rimoldini et al., 2022), and 361 of them ended up in a class other than YSO.
A quarter of the 11 671 sources listed in the KYSO table were rejected based
on data quality cuts applied in the classification verification phase to
ensure that the Gaia DR3 YSO sample, while not complete, provides a reliable
list of confirmed variable YSOs and potential YSO candidates.

####  3.2.2 Completeness based on Marton et al. (2019)

A 1$\arcsec$ radius was used to match the Gaia DR3 YSO source positions to the
M19 catalogue, resulting in 40 320 objects being in both the M19 and Gaia DR3
YSO samples, which means 51% of the Gaia DR3 YSO candidates. While Gaia DR3
provides information on sources from all over the sky, the M19 catalogue was
restricted to an area where the dust opacity value based on the Planck
foreground maps (Planck Collaboration et al., 2016) was higher than $1.3\times
10^{-5}$. This means that YSOs were searched for on 25.4% of the sky. Because
of this cut, as many as 6 037 Gaia DR3 YSO candidates cannot have a
counterpart in the M19 sample. In the common area, 55% of the sources have a
match.

In this completeness study, we used sources from the M19 catalogue that had
YSO as their best label, meaning that the probability of being a YSO was
higher than any of the other probabilities, which means that in cases where
$R\geq 0.5$, then $LY>LMS$, $LY>LEG$, and $LY>LE$, while if $R<0.5$, then
$SY>SMS$, $SY>SEG$, and $SY>SE$, where $MS$, $EG$, and $E$ refer to the
probability of being a main sequence source, an extragalactic object, and an
evolved star, respectively. The number of sources in the M19 catalogue
fulfilling these criteria is 15 052 388.

In this case, 6 488 Gaia DR3 YSO candidates were found to have $R\geq 0.5$ and
the highest probability label was $LY$ from the M19 catalogue, while 21 897
candidates had $R<0.5$ and best label $SY$. This means that, in total, 28 385
Gaia DR3 YSO candidates were classified as possible YSOs according to the M19
catalogue. Compared to the total number of such sources in the M19 catalogue,
the estimated completeness level is 0.19%.

If we compare to those M19 sources with $R\geq 0.5$ and $LY\geq 0.95$ or
$R<0.5$ and $SY\geq 0.95$ (259 363 in total), the overlap with the Gaia DR3
YSO candidates is 6 087 sources, and the completeness level is 2.35%. The best
labels (the object type with the highest probability for a given object) of
possible evolved star, possible extragalactic source, and possible main
sequence star were assigned to 9482 (23.5%), 2143 (5.3%), and 307 (0.8%)
sources, respectively. We cross-matched these sources with SIMBAD in order to
investigate the completeness and contamination in more detail. Our findings
are summarised in Table 3. Based on the numbers, we find that 879 (65.5%) out
of the 1 343 sources classified as evolved stars in the M19 are listed as some
kind of YSO in SIMBAD, 142 (67%) of the 212 M19 extragalactic sources that are
in SIMBAD are also potential YSOs, and finally 146 (55.5%) of the 264 SIMBAD
counterparts of the M19 main sequence stars are also possibly YSOs.

Table 3: SIMBAD classification of Gaia DR3 YSO candidates classified as possible contaminants in the M19 catalogue. The first row lists the total number of Gaia DR3 YSO candidates classified as either evolved star (E), extragalactic source (EG), or main sequence star (MS) in the M19. The second row shows the number of objects also found in SIMBAD. Rows (3)-(6) detail how many of these are classified in SIMBAD as some sort of YSO. The last row shows the number of sources that are not YSO related. | M19 E | M19 EG | M19 MS
---|---|---|---
Total | 9482 | 2143 | 307
in SIMBAD | 1343 | 212 | 264
YSO | 278 | 24 | 41
Candidate_YSO | 392 | 112 | 54
Orion V* | 54 | 2 | 12
TTau* | 155 | 4 | 39
Probably not YSO | 464 | 70 | 118

Combining the M19 classifications with the SIMBAD classifications results in
28 385+1167=29 552 YSOs. This means a small increase in completeness to 0.20%.

####  3.2.3 Completeness based on Kuhn et al. (2021)

As the SPICY catalogue did not require data from the optical domain and is
heavily concentrated on the Galactic midplane, one may expect a low fraction
of matching sources. Using a 1$\arcsec$ radius, we find only 753 objects
present in both the Gaia DR3 YSO sample and the SPICY catalogue. These can all
be considered as possible YSOs, because the SPICY catalogue includes only
sources that were classified as YSO with a probability of greater than 0.5 in
at least one of the three classifiers used in their study.

SPICY also provided an estimated evolutionary class based on the IR slope of
the SED. The age of a YSO is increasing in the following order: Class I, flat
spectrum, Class II, and finally Class III. We found 8 Class I, 87 flat
spectra, 598 Class II, 57 Class III objects, and 3 with uncertain class. In
the SPICY catalogue, the numbers of objects in the respective classes are 15
943, 23 810, 59 949, and 5 352, meaning that 0.05%, 0.4%, 1%, and 1.1% of each
class was found, which reflects that more evolved sources —which we expect to
be more visible in Gaia— are found more reliably. The detailed numbers are
listed in Table 4, which also shows that among the sources that were present
in the variability analysis, the completeness is much higher as it was found
to be 20.3% considering all evolutionary classes, being the highest among
Class II YSOs (23.36%).

Table 4: Number of objects in the different samples from the SPICY catalogue. The meanings of the columns are as follows: (1) source type as reported in SPICY; (2) number of sources reported in SPICY; (3) number of sources from the SPICY catalogue also present in the Gaia DR3; (4) number of sources participating in the variability classification; (5) number of sources classified as YSO during variability classification; (6) fraction of SPICY sources classified as YSO, i.e. column (5) divided by column (2); (7) fraction of Gaia DR3 sources classified as YSO, i.e. column (5) divided by column (3); (8) fraction of those sources participating in the variability classification and classified as YSO, i.e. column (5) divided by column (4). Source type | SPICY |  Gaia DR3 | in var. |  Gaia DR3 |  Gaia DR3 YSO |  Gaia DR3 YSO |  Gaia DR3 YSO
---|---|---|---|---|---|---|---
|  |  | class. | YSO | % of SPICY | % of Gaia DR3 | % of var. class.
Total | 117 446 | 37 693 | 3 693 | 751 | 0.64 | 1.99 | 20.30
Class I | 15 943 | 2 529 | 130 | 8 | 0.05 | 0.32 | 6.15
Flat spectrum | 23 810 | 5 480 | 514 | 87 | 0.37 | 1.59 | 16.93
Class II | 59 949 | 24 486 | 2 560 | 598 | 1.00 | 2.44 | 23.36
Class III | 5 352 | 3 413 | 462 | 57 | 1.07 | 1.67 | 12.34

####  3.2.4 Completeness based on Großschedl et al. (2019)

Similarly to the SPICY catalogue, this study also reported evolutionary stages
for the YSOs, and therefore we were able to estimate completeness as a
function of age. The study lists 3117 sources and they are classified into
several types as listed in the first column of Table 5. The number of sources
classified into each type is listed in column 2. In order to obtain an
estimate of the completeness of the Gaia DR3 YSO sample, we calculated three
quantities. First, we checked how many of the different types of sources were
visible to Gaia based on Gaia DR3 (column 3), how many of them participated in
the variability classification (column 4), and how many are among the Gaia DR3
YSOs (column 5). The ratio of columns 5 and 2 is listed in column 6. Column 7
is the ratio of columns 5 and 3, and column 8 is the ratio of columns 5 and 4.

The total completeness was found to be 19.9%. As expected, the completeness is
very low for Class 0 and I sources, as they emit most of their radiation at IR
wavelengths, but completeness grows with the evolutionary stage and for
transition discs it reaches 38.3%.

Table 5: Number of objects in the different samples from the G19 catalogue. The columns list: (1) the source type as reported in G19; (2) the number of sources reported by G19; (3) the number of sources from the G19 catalogue also present in Gaia DR3; (4) the number of sources participating in the variability classification; (5) the number of sources classified as YSOs during variability classification; (6) the fraction of G19 sources classified as YSO, i.e. column (5) divided by column (2); (7) the fraction of Gaia DR3 sources classified as YSO, i.e. column (5) divided by column (3); (8) the fraction of those sources participating in the variability classification and classified as YSO; i.e. column (5) divided by column (4). Source type | Großschedl |  Gaia DR3 | in var. |  Gaia DR3 |  Gaia DR3 YSO |  Gaia DR3 YSO |  Gaia DR3 YSO
---|---|---|---|---|---|---|---
| et al. |  | class. | YSO | % of G19 | % of Gaia DR3 | % of var. class.
Total | 3117 | 2339 | 672 | 621 | 19.9 | 26.5 | 92.4
Class 0 | 60 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0
Class I | 128 | 9 | 1 | 1 | 0.8 | 11.1 | 11.1
Flat spectrum | 185 | 91 | 20 | 13 | 7.0 | 14.3 | 65.0
Class II/III PMS | 2012 | 1685 | 503 | 473 | 23.5 | 28.1 | 94.0
with disc |  |  |  |  |  |  |
Anemic disc | 394 | 332 | 63 | 57 | 14.5 | 17.2 | 90.5
Transition disc | 201 | 195 | 83 | 77 | 38.3 | 39.5 | 92.8
Galaxy | 39 | 7 | 1 | 0 | 0.0 | 0.0 | 0.0
Nebulosity, fuzzy | 45 | 2 | 0 | 0 | 0.0 | 0.0 | 0.0
contamination |  |  |  |  |  |  |
MS star | 4 | 2 | 0 | 0 | 0.0 | 0.0 | 0.0
Class III w/o | 3 | 3 | 0 | 0 | 0.0 | 0.0 | 0.0
IR excess |  |  |  |  |  |  |
Image artefact | 5 | 0 | 0 | 0 | 0.0 | 0.0 | 0.0
Galaxy candidate | 20 | 4 | 0 | 0 | 0.0 | 0.0 | 0.0
Uncertain YSO | 21 | 9 | 0 | 0 | 0.0 | 0.0 | 0.0
candidate |  |  |  |  |  |  |

####  3.2.5 Cross-match with the SIMBAD database

The Object Type in SIMBAD is defined as a hierarchical classification, which
emphasises the physical nature of the object rather than a peculiar emission
in some region of the electromagnetic spectrum or the location in a peculiar
cluster or external galaxy. Therefore, objects are only classified as peculiar
emitters (in radio, IR, red, blue, UV, X-ray, or gamma ray) if nothing more
about the nature of the object is known; that is, if it cannot be decided
whether the object is a star, a multiple system, a nebula, or a galaxy (Wenger
et al., 2000).

Table 6: Number of sources associated with different SIMBAD objects types. Simbad main_type | Number | %
---|---|---
Candidate_YSO | 8683 | 42.29
YSO | 3975 | 19.36
Star | 2950 | 14.37
TTau* | 1898 | 9.24
Em* | 821 | 4.00
Orion_V* | 773 | 3.77
RotV* | 389 | 1.89
low-mass* | 359 | 1.75
V* | 187 | 0.91
Ae* | 48 | 0.23
Candidate_LP* | 48 | 0.23
EB* | 46 | 0.22
* | 33 | 0.16
BYDra | 25 | 0.12
RGB* | 25 | 0.12
RSCVn | 20 | 0.10
SB* | 20 | 0.10
X | 20 | 0.10
Pec* | 19 | 0.09
Candidate_TTau* | 17 | 0.08
NIR | 15 | 0.07
RRLyr | 14 | 0.07
EllipVar | 13 | 0.06
PulsV* | 13 | 0.06
Eruptive* | 9 | 0.04
MIR | 8 | 0.04
Candidate_EB* | 7 | 0.03
LPV* | 7 | 0.03
Be* | 6 | 0.03
Candidate_AGB* | 6 | 0.03
Candidate_brownD* | 6 | 0.03
HB* | 6 | 0.03
Irregular_V* | 6 | 0.03
PM* | 6 | 0.03
brownD* | 5 | 0.02
deltaCep | 4 | 0.02
Mira | 4 | 0.02
Planet | 4 | 0.02
PulsV*WVir | 4 | 0.02
V*? | 4 | 0.02
Candidate_Ae* | 3 | 0.01
IR | 3 | 0.01
AGN_Candidate | 2 | 0.01
Candidate_Cepheid | 2 | 0.01
Candidate_Mi* | 2 | 0.01
Candidate_RRLyr | 2 | 0.01
Cepheid | 2 | 0.01
BLLac_Candidate | 1 | 0.00
denseCore | 1 | 0.00
FIR | 1 | 0.00
gammaDor | 1 | 0.00
Nova | 1 | 0.00
Planet? | 1 | 0.00
PN | 1 | 0.00
post-AGB* | 1 | 0.00
PulsV*delSct | 1 | 0.00
Radio | 1 | 0.00
RotV*alf2CVn | 1 | 0.00
S* | 1 | 0.00

The total number of objects we find in the SIMBAD database using a 1$\arcsec$
search radius is 20 531. The first column in Table 6 is the SIMBAD main_type,
the second column shows how many objects with the given SIMBAD main_type were
found in the Gaia DR3 YSO sample, while the last column is the percentage of
the given main_type according to the total number of 20 531 associated SIMBAD
objects. As one can see from Table 6, there are multiple object types that we
can use to estimate the completeness, because they can be considered as
potential YSOs. We calculated the sum of objects belonging to the following
types: Candidate_YSO, YSO, TTau*, Candidate_TTau*, Orion_V*, Ae*,
Candidate_Ae*, and Be*. The total number of these objects is 15 363, which
means that 74.8% of the total SIMBAD associations can be considered as
potential YSOs. However, the number of sources listed in SIMBAD with the same
main_types is the following: 49 945 YSO, 99 097 Candidate_YSO, 5 079 TTau*,
317 Candidate_TTau*, 2 887 Orion_V*, 147 Ae*, 67 Candidate_Ae*, and 2 215 Be*;
in total, 159 754 sources can be considered as possible YSOs. Based on these
numbers, the estimated completeness using the SIMBAD catalogue is 9.6%. This
number is mostly determined by the large number of Candidate_YSO type objects.
If we do not take these into account, the estimated completeness is 11%.

####  3.2.6 Magnitude and extinction limitations

The completeness in astronomy is mainly determined by the apparent brightness
of the objects in the sky. This is especially true for YSOs, as in their early
evolutionary stages most of their energy is emitted at wavelengths invisible
to Gaia. Moreover, they are located in obscure regions where the interstellar
dust can modify their observed SEDs, resulting in lower apparent brightness at
the visible wavelengths.

Therefore, we also analysed the completeness of the Gaia DR3 YSO candidate
sample as a function of the Planck dust opacity value ($\tau$, Planck
Collaboration et al., 2016). As shown in Fig. 18, we had no objects in the
Gaia DR3 YSO candidate sample above $\tau=0.0064$. We find that 99% of the
YSOs from the combined KYSO, SPICY, M19, and G19 catalogues are located above
$\tau=0.0018,$ while 99% of the Gaia DR3 YSO candidates are in regions where
$\tau\geq 0.0008$.

Figure 18: Cumulative distribution of the Planck $\tau$ values in the
directions of the YSOs from the KYSO, SPICY, M19, and G19 catalogues (blue
bars) and that of the Gaia DR3 YSO candidates (red bars)).

We also analysed the completeness as a function of the absolute G band
magnitude and Planck $\tau$. As shown in Fig. 19, very faint YSOs were not
recovered by the classification process and also sources at high $\tau$ values
are missing, even if they are bright. On the other hand, sources brighter than
19 mag were found with a completeness of higher than 30% in regions where
$\tau$ is very low, but for all magnitude bins, the completeness decreases as
$\tau$ increases.

Figure 19: Completeness calculated based on objects from the KYSO, SPICY, M19,
and G19 catalogues as a function of Planck dust opacity ($\tau$) and the
absolute median Gaia G band magnitude. Colour coding presents the fraction of
objects that are in any of the mentioned catalogues and also in the Gaia DR3
YSO sample in $5\times 10^{-5}\times 0.25$ mag size bins on a logarithmic
scale.

###  3.3 Contamination

In the previous sections, we mainly focus on the confirmation of the young
nature of the sources and show that the Gaia DR3 YSO sample shows strong
similarities to known YSOs in the colour–magnitude and colour–colour space,
and that their distribution in the sky shows overdensities in the directions
of the known star forming regions and towards the Galactic midplane. We also
give estimations about the completeness of our catalogue, not only in general,
but also as a function of evolutionary stage. In this subsection the SIMBAD
and M19 catalogues are used to estimate the contamination rate of the Gaia DR3
YSO sample, complemented with various catalogues accessible through the VizieR
service (Ochsenbein et al., 2000). Our goal is to find large catalogues
listing sources classified into several object types that are potential
contaminants of the Gaia DR3 YSO set. In all cases, we used a 1$\arcsec$
radius to find a counterpart to Gaia DR3 YSOs.

####  3.3.1 Marton et al. (2019)

In the M19 catalogue, the number of sources that are likely not related to
YSOs after cross-matching them with SIMBAD and also do not have the best label
of $SY$ or $LY$ (depending on the $R$ value) but are either main sequence
stars, extragalactic sources, or evolved stars was found to be 652 (35.8% of
the 1819 sources listed in SIMBAD). If we assume that the contamination rate
is 35.8% among that sample of sources for which the best label is not YSO,
then the expected number of such sources is 4272. This is 10.6% of the total
number of sources present in both the M19 and Gaia DR3 YSO samples and gives a
lower limit of contamination for the whole Gaia DR3 YSO candidate list.
However, a more realistic approach could be to estimate the upper limit of the
contamination. As described in Sect. 3.2.2, there are 40 320 sources common in
the M19 and Gaia DR3 YSO candidate catalogues and 29 552 of them were
identified as a possible YSO by either the M19 classification or the SIMBAD
classification. Assuming that these classifications are realistic and that all
the other sources are contaminant, 26.7% of the Gaia DR3 YSO candidates are
not young stars.

####  3.3.2 SIMBAD

In some cases, as a result of the cross-match with SIMBAD, the listed main
type is too generic (like Star, Em*, low-mass*, etc.; see Table 6). Therefore,
in order to estimate the contamination, we took into account only the well-
defined object types that definitely cannot be YSOs. The number of objects
included the following object types: BYDra, RGB*, RSCVn, SB*, RRLyr,
Candidate_AGB*, Candidate_brownD*, HB*, brownD*, deltaCep, Mira, Planet,
PulsV*WVir, AGN_Candidate, Candidate_Cepheid, Candidate_Mi*, Candidate_RRLyr,
Cepheid, BLLac_Candidate, gammaDor, Nova, Planet?, PN, post-AGB*,
PulsV*delSct, Radio, RotV*alf2CVn, and S*. In total, these add up to 130
sources, 0.6% of the Gaia DR3 YSO associated with sources in Simbad. We
consider this number as a lower limit for the contamination. As an upper
limit, we consider all types that cannot be YSOs as contaminants, which means
all types except those in Sect. 3.2.2 (YSO, Candidate_YSO, OrionV* and TTau*).
Subtracting the number of these objects from the total number of 20 531
objects common with SIMBAD leaves 5 202 sources, meaning 25.3% contamination.

####  3.3.3 Cross-match with Gavras et al. (2022)

Rimoldini et al. (2022) compared the DR3 variable YSO candidates with the
catalogues of variable objects collected by Gavras et al. (2022) as part of
the evaluation process of the machine-learning-based classification. As a
result Rimoldini et al. (2022) found a contamination rate of 79.8%. We
analysed the 5 236 matching sources, including 1 057 true positives (after
excluding the trained YSO sources from the evaluation of completeness and
contamination) and 4 179 false positives. The majority of the contamination
comes from two types of stars: RS CVn binaries (1542) and BY Dra-type stars
(1435).

About 99% of the contaminants that have the label BY and 98% of those with the
label RS are from the Zwicky Transient Facility (ZTF) catalogue of Chen et al.
(2020). Chahal et al. (2022) investigated this ZTF catalogue, paying special
attention to the BY Dra-type objects, and collected additional photometric
data to validate their nature. These authors found that most of the sources in
their catalogue are rapid rotators, and are therefore very likely young stars
for which a spin-down has not yet occurred.

To investigate the other main type of contamination, RS CVn-type stars, we did
not find any paper that looks at ZTF data in a similar way to Chahal et al.
(2022), but found that Martínez et al. (2022) analysed the activity cycles in
RS CVn-type stars. We analysed the reported rotational periods and found that
while 90% of the DR3 YSO candidates labelled RS have periods shorter than 9.41
days, 54% of the Martínez et al. (2022) RS CVn stars have periods longer than
this threshold. The median period for those YSO candidates labelled RS is 3.67
days (MAD=2.27 days), while the median period for the Martínez et al. (2022)
objects is 11.26 days (MAD=8.68 days). Therefore, we conclude that a
significant portion of the objects in our sample labelled RS CVn were likely
misclassified by Chen et al. (2020) and are more likely YSOs.

Among the 1202 remaining sources that might contaminate the YSO sample, 487
are rotational variables (ROTs), which are defined as a generic class of
spotted stars and are scattered all over the colour–magnitude diagram (Gavras
et al., 2022), and therefore cannot be considered as contamination with
certainty.

####  3.3.4 Other catalogues

In Table 7, we summarise the results of the cross-matches with large tables
from the VizieR listing a total of 4 828 588 objects of specific types. We
find 11 sources that might be galaxies, 16 sources that are listed as
eclipsing or ellipsoidal binaries, 32 sources that are also listed as
Cepheid/RR Lyrae-type variables, 5 objects listed as Miras, and 1 star
identified as a Mira-type variable. Also 36 sources are listed in the ASAS-SN
catalogue of variable stars associated with objects that are certainly not YSO
related. The sum of these numbers is 101 objects, which is 0.12% of the
variable Gaia DR3 YSO candidates. We also checked how many of our sources are
located in the same regions as the catalogues used for the cross-match. To do
so we used the HEALPix (Górski et al., 2005) pixelisation of the sky with
nside=256 resolution. This corresponds to $1.5978967\times 10^{-5}$ sr pixel
size. In some cases, the contamination in the areas covered by the different
catalogues increases by an order of magnitude, but still remains at the
percent level, except for the Stringer et al. (2019), where the number of
cross-matches suggests a contamination level of $\sim$15.6%. in the
overlapping area.

Table 7: Catalogues cross-matched with the Gaia DR3 YSO sample in order to
quantify its contamination. Column 1 lists the titles of the corresponding
papers. Column 2 lists the references to the papers. Column 3 gives the number
of sources in the given catalogue. Column 4 is the number of Gaia DR3 YSO
candidates that are found in the same HEALpixels as the sources of the given
catalogue are located. Column 5 is the number of cross-matching Gaia DR3 YSOs
found in the catalogue.

Paper title | Reference | Nr. of entries | Nr. of Gaia | Nr. of matches
---|---|---|---|---
|  | in the catalogue | DR3 YSOs in the | with Gaia
|  |  | same region | DR3 YSOs
HYPERLEDA I. Catalogue of galaxies | Paturel et al. (2003) | 983 261 | 7 600 | 2
6dF galaxy survey final redshift release | Jones et al. (2009) | 124 647 | 1 867 | 0
The Half Million Quasars (HMQ) catalogue | Flesch (2015) | 510 764 | 988 | 0
OGLE fundamental-mode RR Lyrae in | Collinge et al. (2006) | 1 913 | 334 | 0
Galactic Bulge RRab sample |  |  |  |
Galactic bulge eclipsing and ellipsoidal binaries | Soszyński et al. (2016) | 450 598 | 5 677 | 16
Identification of RR Lyrae stars from the DES | Stringer et al. (2019) | 713 816 | 192 | 30
JHKs photometry of VVV RR Lyrae stars | Dékány et al. (2018) | 1 892 | 965 | 0
OGLE Galactic center Cepheids and RR Lyrae | Soszyński et al. (2017) | 40 112 | 5 319 | 2
SDSS quasar catalogue, fourteenth data release | Pâris et al. (2018) | 526 356 | 345 | 0
General Catalogue of Galactic Carbon Stars | Alksnis et al. (2001) | 6 891 | 2 994 | 0
LCs re-analysis of Mira variables in ASAS | Vogt et al. (2016) | 2 875 | 363 | 0
Mira-like variables from the KELT survey | Arnold et al. (2020) | 4 132 | 997 | 5
Mira Variables in the OGLE Bulge fields | Groenewegen & Blommaert (2005) | 2 691 | 345 | 0
Compiled catalogue of stellar data of Miras | Kharchenko et al. (2002) | 1 103 | 78 | 0
Extended catalogue of NSVS red AGB | Usatov & Nosulchik (2008) | 794 | 374 | 1
variable stars |  |  |  |
LEDA galaxies with DENIS measurements | Paturel et al. (2005) | 753 153 | 5 917 | 2
PSCz catalogue | Saunders et al. (2000) | 18 351 | 1 272 | 7
ASAS-SN catalogue of variable stars (*) | Jayasinghe et al. (2018) | 666 502 | 55 160 | 36
Groups of galaxies in 2MASS survey | Crook et al. (2007) | 18 737 | 394 | 0

444(*) The ASAS-SN catalogue provides a classification for each of their
sources. Herein, we take into account sources that should not be considered as
YSOs, such as CWB, EA, EB, EW, GCAS, and RCB: variables.

##  4 Summary and conclusions

We validate the first catalogue of variable YSO candidates observed during the
first 34 months of operation of the Gaia space telescope. As a result of the
classification process, the catalogue lists 79 375 YSO candidates as part of
the third Gaia Data Release (DR3). After analysing the different parameter
distributions, such as colours, brightness, distance, and apparent positions
on the sky, we conclude that the Gaia DR3 YSO sample contains sources that are
very similar to confirmed YSOs, mainly including the lower-mass objects. By
comparing the Gaia DR3 YSOs to catalogues listing evolutionary stages, we
confirm that Gaia is more sensitive to the more evolved Class II/III YSOs,
which are visible in the optical bands covered by Gaia. The estimated
completeness at the very early stages of star formation, when most of the
energy of YSOs is emitted at FIR and MIR wavelengths, is close to zero, but it
can range from a few percent to $\sim$40% for objects with transitional discs,
depending on the distance of the star forming regions they are located in. The
lower limit of contamination level is at least 0.6% (according to SIMBAD), but
the upper limit is 26.7%. More realistically, the contamination is lower than
the upper limit, but still around the 10% level. Estimates of the
contamination based on the cross-match with several other catalogues
containing specific object types are even lower (below 0.2%), but these
objects are mostly located at higher galactic latitudes where only a small
fraction of our sources are located. The estimated number of potentially new
YSOs presented in the Gaia DR3 variable star catalogue is on the order of a
few tens of thousands of objects, but below 44 651. These objects were not
classified as YSOs in the YSO catalogues we used for the validation and were
not classified as a different type of object by the other catalogues used in
this study.

###### Acknowledgements.

We are thankful for our anonymous referee for all the comments and suggestion
that helped us to improve the paper. This work has made use of data from the
European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia),
processed by the Gaia Data Processing and Analysis Consortium (DPAC,
https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has
been provided by national institutions, some of which participate in the Gaia
Multilateral Agreement, which include, for Switzerland, the Swiss State
Secretariat for Education, Research and Innovation through the ESA Prodex
program, the ‘Mesures d’accompagnement’, the ‘Activités Nationales
Complémentaires’, the Swiss National Science Foundation, and the Early
Postdoc. Mobility fellowship; for Hungary, the ESA PRODEX contract
nr.4000129910. G.M. acknowledges support from the European Union’s Horizon
2020 research and innovation programme under grant agreement No. 101004141.
This project has received funding from the European Research Council (ERC)
under the European Union’s Horizon 2020 research and innovation programme
under grant agreement No 716155 (SACCRED). This research has made use of the
SIMBAD database, operated at CDS, Strasbourg, France. This research has made
use of the VizieR catalogue access tool, CDS, Strasbourg, France (DOI :
10.26093/cds/vizier). This work made use of software R (R Core Team, 2018) and
TOPCAT/STILTS (Taylor, 2005).

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##  Appendix A KYSO - The Konkoly Optical YSO catalogue

We compiled a large catalogue of optically detected, bona fide YSOs.555The
KYSO table is only available in electronic form at the CDS via anonymous ftp
to cdsarc.cds.unistra.fr (130.79.128.5) or via
https://cdsarc.cds.unistra.fr/cgi-bin/qcat?J/A+A/. The main source of our
compilation was the Handbook of Star Forming Regions (Volumes I and II,
Reipurth 2008a, b) which consists of 62 chapters, with each chapter describing
a region of the sky (mostly one constellation or a part of it) and not a well-
defined star forming region. All of the included regions are located within
$\sim$2 kpc of the Sun. Most chapters contain a list of YSOs located in the
specific star forming regions, but sometimes only references to the catalogues
are given. In the latter case, we took the list of the YSOs from the original
(discovery) papers. We also performed an extensive literature search to
include YSO catalogues published after the Handbook of Star Forming Regions.
Furthermore, we included the stars of the comprehensive Herbig and Bell (1988)
catalogue of pre-main sequence stars, and Herbig Ae/Be stars from Thé et al.
(1994) and Vieira et al. (2003). The celestial distribution of the KYSOs is
shown in Fig. 20.

Most of the stars of the KYSO catalogue were classified as YSOs based on
optical spectra, i.e. they exhibited strong emission lines and/or strong
lithium absorption. Moreover, we included H$\alpha$ emission stars located in
star forming regions and detected by slitless spectroscopy. In addition to the
spectroscopically identified YSOs, we included a few datasets containing
optical counterparts of candidate YSOs selected by IR and X-ray observations.
These are listed as follows: (i) IR variable stars detected by Carpenter et
al. (2001) in the Orion A cloud; (ii) optically visible low-mass stars
classified as YSOs based on combined X-ray and IR criteria by Getman et al.
(2009) in Cepheus B, and by Wolk et al. (2008) in RCW 108; (iii) optical
counterparts of IR sources in Barnard 59, classified as YSOs by IR
spectroscopy (Covey et al. 2010); (iv) candidate YSOs in the Camelopardalis
region, classified by optical–IR SED (Straižys & Kazlauskas 2010).

The individual YSO catalogues that we collected are very diverse regarding
data structure, detection methods, limiting magnitude, and angular resolution.
Our aim is to create a unified database from these various sources. As a first
step, we extracted the celestial coordinates and names of the objects from the
individual catalogues. In the case of older measurements, we converted the
epoch from B1950 to J2000 and checked the positions in original finding
charts. These data were then loaded into a database using a common scheme.
Apart from the name, coordinates, and the detection method, no other
information was used from the YSO catalogues.

A major issue with the data is that a source can be present in several
catalogues under different names and with slightly different coordinates. For
the detection of duplicate sources, we applied a semi-automatic approach. The
automatic part of the process was the identification of clusters of objects
within a search radius of 1$\aas@@fstack{\prime\prime}$5\. Then we manually
examined the duplicate candidates. We checked the probability of being a
duplicate based on the distribution of positions from the various catalogues,
known binarity, and the naming of objects from the SIMBAD database. When a
duplicate was found, we removed the duplicate entries from our database and
retained the data from the most recent catalogue. Binary stars can also appear
as duplicate candidates. Three criteria were used in the identification of
multiple stars: (1) When duplicate candidates are present in the same
catalogue, this suggests that the sources are indeed distinct, probably
binaries. (2) In other cases, the names of the objects indicate binarity. (3)
The source is present in the Young Visual Binary Star
Database666http://www2.lowell.edu/users/lprato/YBIN/Binary_Star_Database.html.

Next, we consistently associated all of the KYSO objects with their parent
star forming regions. Generally, we took the names of the regions from the
individual papers describing the catalogues. In some cases, we found
inconsistencies in the naming, when, e.g. the same region had different
designations. To resolve these issues, we chose the naming convention present
in SIMBAD. In the case of some smaller regions, where there is a known larger
star forming region to which the given smaller region belongs, we used both
names in the following arrangement: ‘Large star forming region: Small region’
(e.g. ‘Rosette Complex: NGC 2244’). In total, the KYSO catalogue contains 124
star forming regions.

We supplemented the catalogue with the columns of YSO type and variability
type of the sources. YSO types are as follows: CTT* – classical T Tauri star,
K–M type stars with emission spectra and accretion disc, GTT* – similar to
CTT* with G0–K0 spectral type (see Herbst & Shevchenko 1999), IMTT* –
intermediate-mass TT* similar to CTT* with F5–F8 spectral type; WTT* – weak-
line T Tauri stars identified by G–M spectral types and strong Li I absorption
line at 6707 Å. PTT* is for post-T Tauri stars (Mamajek et al. 2002). HAeBe
stars are B–F5 type pre-main sequence stars. FU Ori and EX Lupi type stars are
regarded as distinct classes. TT* is assigned when no data were available on
the accretion; Y*O is assigned when this was the only information. We have not
included normal, main sequence OB stars, but included a few objects classified
as high-mass YSOs (HMY*O). Variability data were obtained from an extensive
search in VizieR. In addition to the published variability types, we inspected
the light curves available in various VizieR catalogues. A previous version of
the catalogue is described in Varga-Verebélyi et al. (2020).

Figure 20:  Konkoly Optical YSO (KYSO) catalogue of optically selected young
stars presented in Aitoff projection in Galactic coordinates.

##  Appendix B Parameter distributions

###  B.1 $G_{\rm BP}-G_{\rm RP}$ distributions

Figure 21: $G_{\rm BP}-G_{\rm RP}$ colour distribution of the Gaia DR3 YSOs
(red bars) and KYSOs (blue bars) on a logarithmic scale. KYSOs show an excess
towards bluer colours.  Figure 22: Same as Fig. 21 but for the Gaia DR3 YSOs
(red bars) and the Großschedl et al. (2019) G19 YSOs (grey bars).  Figure 23:
Same as Fig. 21 but for the Gaia DR3 YSOs (red bars) and the Kuhn et al.
(2021) SPICY YSOs (yellow bars).  Figure 24: Same as Fig. 21 but for the Gaia
DR3 YSOs (red bars) and the Marton et al. (2019) M19 YSOs with $R\geq 0.5$ and
$LY\geq 0.95$ or $R<0.5$ and $SY\geq 0.95$ (green bars). The M19 YSOs show a
significant excess at $G_{\rm BP}-G_{\rm RP}$ =1. These are all YSO candidates
seen towards the Galactic midplane.

###  B.2 Absolute median $G$

Figure 25: Gaia absolute $G$-band magnitude distribution of the Gaia DR3 YSOs
(red bars) and KYSOs (blue bars) on a logarithmic scale. KYSOs show a slight
excess towards both ends, showing that very faint and bright sources were not
classified as YSOs.  Figure 26: Same as Fig. 25, but for the Gaia DR3 YSOs
(red bars) and the G19 YSOs (grey bars).  Figure 27: Same as Fig. 25, but for
the Gaia DR3 YSOs (red bars) and the SPICY YSOs (yellow bars).  Figure 28:
Same as Fig. 25, but for the Gaia DR3 YSOs (red bars) and the M19 YSOs (green
bars).

###  B.3 J-H 2MASS colour

Figure 29: 2MASS J$-$H colour distribution of the Gaia DR3 YSOs (red bars) and
KYSOs (blue bars) on a logarithmic scale.  Figure 30: Same as Fig. 29, but for
the Gaia DR3 YSOs (red bars) and the G19 YSOs (grey bars).  Figure 31: Same as
Fig. 29, but for the Gaia DR3 YSOs (red bars) and the SPICY YSOs (yellow
bars).  Figure 32: Same as Fig. 29, but for the Gaia DR3 YSOs (red bars) and
the M19 YSOs (green bars).

###  B.4 H-Ks 2MASS colour

Figure 33: 2MASS H$-$Ks colour distribution of the Gaia DR3 YSOs (red bars)
and KYSOs (blue bars) on a logarithmic scale.  Figure 34: Same as Fig. 33, but
for the Gaia DR3 YSOs (red bars) and the G19 YSOs (grey bars).  Figure 35:
Same as Fig. 33, but for the Gaia DR3 YSOs (red bars) and the SPICY YSOs
(yellow bars).  Figure 36: Same as Fig. 33, but for the Gaia DR3 YSOs (red
bars) and the M19 YSOs (green bars).