J/A+A/648/A44 Large-amplitude variables in Gaia DR2 (Mowlavi+, 2021)
Large-amplitude variables in Gaia Data Release 2.
Multi-band variability characterization.
Mowlavi N., Rimoldini L., Evans D.W., Riello M., De Angeli F., Palaversa L.,
Audard M., Eyer L., Garcia-Lario P., Gavras P., Holl B.,
Jevardat de Fombelle G., Lecoeur-Taibi I., Nienartowicz K.
<Astron. Astrophys. 648, A44 (2021)>
=2021A&A...648A..44M 2021A&A...648A..44M (SIMBAD/NED BibCode)
ADC_Keywords: Surveys ; Stars, variable ; Photometry
Keywords: stars: variables: general - stars: general - surveys -
methods: data analysis
Abstract:
Photometric variability is an essential feature that sheds light on
the intrinsic properties of celestial variable sources, the more so
when photometry is available in various bands. In this respect, the
all-sky Gaia mission is particularly attractive as it collects, among
other quantities, epoch photometry measured quasi-simultaneously in
three optical bands for sources ranging from a few magnitudes to
fainter than magnitude twenty.
The second data release (DR2) of the mission provides mean G, GBP and
GRP photometry for 1.4 billion sources, but light curves and
variability properties are available for only 0.5 million of them.
Here, we provide a census of large-amplitude variables (LAVs) with
amplitudes larger than 0.2mag in the G band for objects with mean
brightnesses between 5.5 and 19mag.
To achieve this, we rely on variability amplitude proxies in G, GBP
and GRP computed from the uncertainties on the magnitudes published in
DR2. We then apply successive filters to identify two subsets
containing respectively sources with reliable mean GBP and GRP (for
studies using colours) and sources having compatible amplitude proxies
in G, GBP and GRP (for multi-band variability studies).
The full catalogue gathers 23315874 LAV candidates, and the two
subsets with increased levels of purity contain respectively 1148861
and 618966 sources. A multi-band variability analysis of the
catalogue shows that different types of variable stars can be
categorized according to their colour and blue-to-red amplitude ratios
as determined from the G, GBP and GRP amplitude proxies. More
specifically, four groups are globally identified. They mostly include
long-period variables in a first group with amplitudes more than twice
larger in the blue than in the red, hot compact variables in a second
group with amplitudes smaller in the blue than in the red, classical
instability strip pulsators in a third group with amplitudes larger in
the blue than in the red by 50% to 80%, and other non-pulsating
variables in a fourth group, mainly achromatic, but with still 10% of
them having 20% to 50% larger amplitudes in the blue than in the red.
The catalogue constitutes the first census of Gaia large amplitude
variable (LAV) candidates, extracted from the public DR2 archive. The
overview presented here illustrates the added-value of the mission for
multi-band variability studies even at this stage when epoch
photometry is not yet available for all sources.
Description:
We present a catalogue of 23315874 large amplitude variables (LAV)
from Gaia DR2 having peak-to-peak G amplitudes larger than about
0.2mag, selected from their amplitude proxy AproxyG>0.06 (Sect. 3).
The full catalogue of sources is called Dataset A.
We identified two subsamples, summarized in Table 1. Dataset B (5% of
Dataset A) is suitable for studies requiring GBP and GRP magnitudes,
such as studying colour-magnitude diagrams. Dataset C (about half of
Dataset B) is suited for multiband variability studies involving the
amplitude proxies AproxyBP and AproxyRP in GBP and GRP,
respectively.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
tabled1.dat 268 23315874 Catalog of large amplitude variables from Gaia DR2
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See also:
I/345 : Gaia DR2 (Gaia Collaboration, 2018)
Byte-by-byte Description of file: tabled1.dat
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Bytes Format Units Label Explanations
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1- 19 I19 --- GaiaDR2 GaiaDR2 source ID (source_id)
21 I1 --- datasetB [0/1] In in dataset B? (dataset_B) (1)
23 I1 --- datasetC [0/1] In in dataset C? (dataset_C) (1)
25- 38 F14.10 deg GLON GaiaDR2 Galactic longitude (l_deg)
40- 53 F14.10 deg GLAT GaiaDR2 Galactic latitude (b_deg)
55- 64 F10.4 mas Plx ?=- GaiaDR2 absolute stellar parallax
(parallax_mas)
66- 71 F6.4 mas e_Plx ?=- GaiaDR2 Standard error of parallax
(parallaxerrormas)
73- 76 I4 --- o_Gmag ? GaiaDR2 number of observations contributing
to G photometry (photgn_obs)
78- 88 E11.5 e-/s FG GaiaDR2 G-band mean flux (photgmean_flux)
90-100 E11.5 e-/s e_FG GaiaDR2 Error on G-band mean flux
(photgmeanfluxerror)
102-110 F9.6 mag Gmag GaiaDR2 G-band mean magnitude (Vega)
(photgmean_mag)
112-114 I3 --- o_BPmag ? GaiaDR2 Number of observations contributing
to BP photometry (photbpn_obs)
116-126 E11.5 e-/s FBP ?=- GaiaDR2 mean flux in the integrated
BP band (photbpmean_flux)
128-138 E11.5 e-/s e_FBP ?=- GaiaDR2 error on the integrated BP mean
flux (photbpmeanfluxerror)
140-148 F9.6 mag BPmag ?=- GaiaDR2 integrated BP mean magnitude
(Vega) (photbpmean_mag)
150-152 I3 --- o_RPmag ? GaiaDR2 number of observations contributing
to RP photometry (photrpn_obs)
154-164 E11.5 e-/s FRP ?=- GaiaDR2 mean flux in the integrated RP
band (photrpmean_flux)
166-176 E11.5 e-/s e_FRP ?=- GaiaDR2 error on the integrated RP mean
flux (photrpmeanfluxerror)
178-186 F9.6 mag RPmag ?=- GaiaDR2 integrated RP mean magnitude
(Vega) (photrpmean_mag)
188-192 F5.3 --- E(BR/RP) ?=- GaiaDR2 BP/RP excess factor
(photbprpexcessfactor)
194-198 F5.3 --- NE(BR/RP) ?=- Normalized GaiaDR2 BP/RP excess factor
(photbprpexcessfactor_normalized)
200 I1 --- f_NE(BR/RP) [0/1] Is BP/RP flux excess reliable ?
(isGoodBpRpExcessFactorNormalized)
202 I1 --- LPV [0/1] Is LPV candidate in GaiaDR2? (DR2_LPV)
204 I1 --- RRL-SOS [0/1] Is RR Lyrae candidate in GaiaDR2
(sos table)? (DR2RRLSOS)
206 I1 --- RRL-Cl [0/1] Is RR Lyrae candidate in GaiaDR2
(classif table)? (DR2RRLClassif)
208 I1 --- Cep-SOS [0/1] Is Cepheid candidate in GaiaDR2
(sos table)? (DR2CepSOS)
210 I1 --- Cep-Cl [0/1] Is Cepheid candidate in GaiaDR2
(classif table)? (DR2CepClassif)
212 I1 --- dSctSXPhe [0/1] Is delta Scuti & SXPHE candidate
in GaiaDR2? (DR2dSctSXPhe)
214 I1 --- RotMod [0/1] Is rotation modulation candidate
in GaiaDR2? (DR2_RotMod)
216 I1 --- STS [0/1] Is short time-scale candidate
in GaiaDR2? (DR2_STS)
218-225 F8.6 --- AmpG Amplitude proxy in G (amplProxyG)
227-236 F10.6 --- AmpBP ?=- Amplitude proxy in BP (amplProxyBP)
238-247 F10.6 --- AmpRP ?=- Amplitude proxy in RP (amplProxyRP)
249-258 F10.6 --- AmpBP+RP ?=- Amplitude proxy in BP+RP, Eq. (C10)
(amplProxyBPplusRPwithoutCov)
260 I1 --- Group1 [0/1] Is in Group 1 (for Dataset C only)?
(Group_1) (2)
262 I1 --- Group2 [0/1] Is in Group 2 (for Dataset C only)?
(Group_2) (2)
264 I1 --- Group3 [0/1] Is in Group 3 (for Dataset C only)?
(Group_3) (2)
266 I1 --- Group4 [0/1] Is in Group 4 (for Dataset C only)?
(Group_4) (2)
268 I1 --- Group4a [0/1] Is in Group 4a (for Dataset C only)?
(Group_4a) (2)
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Note (1): Datasets as follows:
Dataset A: All LAVs satisfying Eq. 6 and cleaned from sources whose light
curves appear to be affected by instrumental artifacts at specific times of
the mission (filter a1 in Table 1, see Sect. A.2 in Appendix A for more
info). Sources that may potentially contain G epoch magnitudes fainter than
20.5mag are also excluded (filter a2 in Table 1, see Appendix A.3).
The procedure used to import the data from the Gaia DR2 archive and details
on the filtering criteria are given in Appendix A.
Dataset B: Subset of Dataset A to be preferentially used if reliable GBP and
GRP magnitudes are needed (such as for colour-magnitude diagrams). The
selection relies on the fact that IBP+IRP must be close to IG as a
result of the wavelength transmission bands of G, GBP and GRP
(Evans et al., 2018A&A...616A...4E 2018A&A...616A...4E). A source with a larger-than-expected
summed flux IBP+IRP relative to IG is therefore suspected to have
inconsistent G, GBP and GRP measurements. While unreliable BP/RP flux
excesses are, in DR2, due in many cases to BP/RP integrated fluxes of
poorer quality, similar problems can also affect G-band measurements. We
refer to Appendix B for a discussion on this (see in particular Sect. B.3).
The BP/RP flux excess (IBP+IRP)=IG depends on the spectral type,
and thus on GBP-GRP colour. We derive in Appendix B a normalized BP/RP
flux excess, notated C0 (Eq. B.3 in the Appendix), which should be close
to one at all GBP-GRP colours for typical stars, and apply the filtering
criteria b2 and b3 listed in Table 1 to derive Dataset B. This can be done
only if the source has IBP and IRP values in Gaia DR2, which imposes the
additional selection criterion b1 listed in Table 1.
Dataset C: Subset of Dataset B to be preferentially used if reliable
AproxyBP and AproxyRP are needed (such as for multi-band variability
studies in G, GBP and GRP). The selection relies on the fact that the
variability in BP+RP must be consistent with the variability in G given the
wavelength transmission bands. A variability in G that is not present in
BP+RP is suspicious (note, however, that this could happen in the case of
an anti-correlated variability in the blue and in the red4). Likewise, a
variability observed in BP+RP but not in G may indicate additional noise
in GBP and/or GRP that would make AproxyBP and/or AproxyRP unreliable
(note, however, that, in such a case, AproxyG may still be reliable).
Note (2): Subgroups in group C as follows:
Group 1 = sources with GBP-GRP>1.8mag (2033 LAVs)
Group 2 = sources with GBP-GRP<0.2mag (59 LAVs)
Group 3 = predominantly contain pulsating stars(3531 LAVs)
Group 4 = predominantly contain non-pulsating LAVs. (79 074 LAVs)
Group 4a = additional insight on Group 4 LAVs that display chromatic
variability (6154 LAVs)
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Acknowledgements:
Nami Mowlavi, Nami.Mowlavi(at)unige.ch
(End) N. Mowlavi [Geneva Univ., Switzerland], P. Vannier [CDS] 07-Jan-2021