J/A+A/705/A172 Young stars variability with Gaia DR3 light curves (Mas+, 2026)
Exploring the variability of young stars with Gaia DR3 light curves.
Mas C., Roquette J., Audard M., Madarasz M., Marton G., Hernandez D.,
Gezer I., Dionatos O.
<Astron. Astrophys. 705, A172 (2026)>
=2026A&A...705A.172M 2026A&A...705A.172M (SIMBAD/NED BibCode)
ADC_Keywords: Stars, variable ; Photometry ; Optical ; Infrared
Keywords: stars: formation - stars: pre-main sequence - stars: protostars -
stars: rotation - stars: variables: general -
stars: variables: T Tauri, Herbig Ae/Be
Abstract:
Photometric variability is a defining characteristic of young stellar
objects (YSOs) that can be traced back to a range of physical
processes that occur at different stages in the formation and early
evolution of young stars. The Gaia third Data Release (GDR3) has
provided an unprecedented dataset of photometric time series,
including 79375 light curves for sources classified as YSO
candidates. Through its all-sky coverage, Gaia provides a unique
opportunity for large-scale studies of YSO variability.
Our goal was to characterise the GDR3 sample of YSO variables to
better identify the recurrence of YSO variability modes (caused by
accretion, extinction, rotation modulation, etc.). We made a pilot
study of the applicability of the asymmetry (M) and periodicity (Q)
variability metrics to characterise YSO variability with Gaia light
curves. By adapting the Q-M metrics for sparse and long-term light
curves, we sought to bridge the gap between low- and high-cadence
survey insights on YSO variability.
We adapted the Q-M method for Gaia. Through a refined sample
selection, we identified sources with an appropriate sampling for the
Q-M method. We used the generalised Lomb Scargle periodogram and
structure functions to derive characteristic variability timescales.
We successfully derived Q-M indices for 23000 sources in the GDR3 YSO
sample. These variables were then classified into eight variability
morphological classes. We linked the morphological classes with
physical mechanisms using Hα as a proxy of accretion and
αIR indices to gauge whether circumstellar material was present.
We demonstrate that the Q-M metrics can be successfully applied to
study the sparse time series of Gaia. We applied it successfully to
distinguish between the various variability modes of YSOs. While our
results are generally consistent with previous high-cadence short-term
studies, the long GDR3 time span yields a larger variety of
variability mechanisms.
Description:
We conducted a pilot study to assess the applicability of the
asymmetry (M) and periodicity (Q) variability metrics (Cody et al.,
2014AJ....147...82C 2014AJ....147...82C, Cat. J/AJ/147/82) for characterizing the
variability of young stellar objects (YSOs) using Gaia light curves.
By adapting the Q-M metrics for sparse and long-term light curves, we
aimed to bridge the gap between insights gained from low-cadence and
high-cadence surveys on YSO variability. We successfully derived Q-M
indices for 23000 sources in the Gaia DR3 YSO sample, which were
classified into eight variability morphological classes. We linked the
morphological classes with physical mechanisms using Hα as a
proxy of accretion and alphaIR indices to gauge whether
circumstellar material was present.
We classify the G-band light curves of 28 179 YSOs according to light
curve morphology and discuss classes also in terms of their
variability amplitude and timescale. These were classified into 8
classes: strictly periodic (P), eclipsing binary (EB), quasi- periodic
symmetric (QPS), quasi-periodic dippers (QPD), aperiodic dipper (APD),
burster (B), stochastic (S), and long-trend (L). To access the links
of variability modes with possible physical origins, we also provide -
when possible - estimatives of sources' spectral type, disc infrared
index classification, and CTTS/WTTS labels based on EW(H_alpha).
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
tabled1.dat 310 28179 Catalog
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See also:
J/AJ/147/82 : Monitoring of disk-bearing stars in NGC 2264 (Cody+, 2014)
J/ApJS/208/9 : Intrinsic colors and temperatures of PMS stars (Pecaut+, 2013)
J/A+A/674/A21 : KYSO - The Konkoly Optical YSO catalogue (Marton+, 2023)
J/A+A/702/A63 : NEMESIS catalogue of YSOs in Orion (Roquette+, 2025)
Byte-by-byte Description of file: tabled1.dat
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Bytes Format Units Label Explanations
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1- 19 I19 --- GaiaDR3 Gaia DR3 source identifier
21- 40 F20.16 deg RAdeg Right Ascension (J2000)
42- 61 F20.16 deg DEdeg Declination (J2000)
63- 81 F19.16 mas plx Gaia DR3 parallax
83- 92 F10.7 mag Gmag Gaia DR3 mean G magnitude
94- 98 F5.1 --- o_Gmag Number of epochs for G magnitude
100-101 I2 --- CTTS ? Classical T Tauri star flag (1)
103-121 F19.14 --- longTimeScale ? Long timescale
123-125 A3 --- f_longTimeScale [FGLS ] Timescale derivation method
for long timescale (2)
127-129 A3 --- f_TimeScale [FGLS ] Timescale derivation method (2)
131-150 F20.16 d TimeScale ? Variability timescale
152-156 A5 --- Primary [true/false ] Primary sample flag
158-179 E22.17 --- Mindex M-index from Cody et al.
(2014AJ....147...82C 2014AJ....147...82C, Cat. J/AJ/147/82)
181-199 F19.16 --- Qindex ? Q-index from Cody et al.
(2014AJ....147...82C 2014AJ....147...82C, Cat. J/AJ/147/82)
201-218 F18.16 mag Amp G band Variability amplitude
220-222 A3 --- MClass Variability morphological class inferred
from Q-M indices (3)
224-244 E21.16 --- alpha-ir ? alpha IR index for 2-24um
246-249 F4.1 --- NSED ? Number of SED points used
for alphair calculation
251-268 F18.16 um lambdamin ? Maximum wavelength available
for alphair calculation
270-287 F18.15 um lambdamax ? Maximum wavelength available
for alphair calculation
289-296 A8 --- Disc IR Disc Class (4)
298-299 A2 --- SpType Spectral Type
301-310 A10 --- f_SpType Method for Spectral type estimation (5)
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Note (1): Following App. C.1.
0 : H-alpha observation exists, but does not indicate ongoing
accretion (WTTS)
>0 : at least one observation reports ongoing accretion (CTTS).
blank : no available information. See App. C.1
Note (2): Timescale derivation method (Sect. 4.2) as follows:
GLS = generalised Lomb-Scargle periodogram was used to derive timescale
(Sect. 4.2.1).
SF = structure function was used to derive timescale (Sect. 4.2.2).
Note (3): Variability morphology class (Sect. 4.3) as follows:
EB = eclipsing Binary Q<0.11 and M>0.25
P = strictly Periodic Symmetric Q<0.11 and M≤0.25
QPS = quasi-periodic symmetric 0.11≤Q≤0.61 and |M|≤0.25
QPD = quasi-periodic Dipper: 0.11≤Q≤0.61 and M>0.25
APD = aperiodic Dipper: Q>0.61 and M>0.25
B = burst: Q>0.11 and M←0.25
S = stochastic: Q>0.61 and |M|≤0.25
L = long-trend: timescale > 0.5 * (total observed time)
Note (4): Disc classification based on the SED IR alpha_IR index (App.C.2)
as follows:
Discless = alphaIR < -2.5
Thin = -1.6 < alphaIR ≤ -2.5
Thick = -0.3 < alphaIR ≤ -1.6
Envelope = alphaIR > -0.3
Note (5): Spectral type estimation method (App. C.3) as follows:
Bp-Rp->SpT = converted from de-reddened GBP-GRP colours
Teff->SpT = converted from Teff using Pecaut & Mamajek
(2013ApJS..208....9P 2013ApJS..208....9P, Cat. J/ApJS/208/9)
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Acknowledgements:
Julia Roquette, julia.roquette(at)unige.ch
References:
Andrae et al., 2023A&A...674A..27A 2023A&A...674A..27A
Cody et al., 2014AJ....147...82C 2014AJ....147...82C, Cat. J/AJ/147/82
Eyer et al., 2023A&A...674A..13E 2023A&A...674A..13E
Marton et al., 2023A&A...674A..21M 2023A&A...674A..21M, Cat. J/A+A/674/A21
Pecaut & Mamajek, 2013ApJS..208....9P 2013ApJS..208....9P, Cat. J/ApJS/208/9
Roquette et al., 2025A&A...702A..63R 2025A&A...702A..63R, Cat. J/A+A/702/A63
(End) Patricia Vannier [CDS] 03-Dec-2025