J/A+A/708/A120 AGB Carbon rich stars SED fitting results (Liberatori+, 2026)
A homogeneous view of asymptotic giant branch carbon stars as seen by Gaia.
Liberatori A., Hatzidimitriou D., Antoniadis K., Pastorelli G.,
Trabucchi M., Groenewegen M.A.T., Bossini D., Girardi L., Marigo P.,
Bressan A., Kallimanis I.N., Costa G., Katsis V., Vasilopoulos G.,
Chatzipetros S.
<Astron. Astrophys. 708, A120 (2026)>
=2026A&A...708A.120L 2026A&A...708A.120L (SIMBAD/NED BibCode)
ADC_Keywords: Stars, carbon ; Stars, late-type ; Mass loss ;
Models, evolutionary ; Optical
Keywords: stars: AGB and post-AGB - stars: mass loss
Abstract:
Carbon stars on the asymptotic giant branch are major contributors to
the dust enrichment of galaxies, with gas mass-loss rate values up to
dM/dt=10-4M[sun/yr. They represent the final evolutionary stage
of low- and intermediate-mass stars, during which recurrent dredge-up
episodes enrich their atmospheres with carbon and trigger the
formation of dust. Through their intense winds, they inject large
amounts of newly formed carbonaceous dust into the interstellar
medium, playing a central role in the chemical evolution of galaxies.
Their stellar and dust properties have been studied for decades, with
a particular focus on the carbon stars in the Magellanic Clouds (MCs).
Our aim is to homogeneously analyse the Gaia DR3 Golden Sample of
Carbon Stars through the spectral energy distribution (SED) fitting.
Our focus is on sources belonging to the Milky Way (MW) and the MCs.
Our dataset consists of 14747 stars with complete multi-band
photometry from Gaia, 2MASS, and WISE, combined with recent distance
and extinction estimates. For a subsample of Mira variables made of
2494 stars, we also modelled multi-band light curves to obtain
accurate mean magnitudes. Stellar and circumstellar properties were
derived by fitting the observations with a large grid of synthetic
models computed with the DUSTY radiative transfer code, using COMARCS
model atmospheres as input. For each target, we determined stellar and
dust parameters such as the effective temperature, optical depth, and
gas mass-loss rate.
The resulting distributions reveal typical effective temperatures of
around 3150K. Mass-loss rates range from 10-11 to 10-4M☉/yr.
The average dust temperature at the inner bound of the dust shell is
about Td=1000K. We also observe a correlation between photometric
variability amplitude and mass-loss rate.
This homogeneous framework provides a unified view of carbon stars
across environments spanning a wide range of metallicities, supported
by strong statistical coverage. Our results show that some of the
physical properties of carbon stars exhibit a dependence on the
galactic environment. However, these dependences do not necessarily
reflect intrinsic metallicity effects, but are influenced by
differences in luminosity distributions and by the selection biases
affecting the available samples. The use of Gaia and WISE introduces
combined selection effects that are significant, limiting the
detection of both the most dust-enshrouded objects and the less
luminous sources in the Magellanic Clouds. While this limits the
completeness of the comparison, the observed trends remain
statistically robust within the selected samples.
Description:
We present a homogeneous analysis of the Gaia DR3 Golden Sample of
Carbon Stars, focusing on sources belonging to the Milky Way (MW) and
the Magellanic Clouds (MCs). Our dataset consists of 14747 stars with
complete multi-band photometry from Gaia, 2MASS, and WISE, combined
with recent distance and extinction estimates. For a subsample of Mira
variables (2494 stars), we modelled multi-band light curves to obtain
accurate mean magnitudes. Stellar and circumstellar properties were
derived by fitting the observations with a large grid of synthetic
models computed with the DUSTY radiative transfer code, using COMARCS
model atmospheres as input. We determined stellar and dust parameters
such as effective temperature, optical depth, and gas mass-loss rate.
The resulting distributions reveal typical effective temperatures
around 3150K and mass-loss rates ranging from 10-11 to
10-4M☉/yr. The average dust temperature at the inner bound of
the dust shell is about 1000K. We also observe a correlation between
photometric variability amplitude and mass-loss rate.
The catalogue contains the results of the SED fitting procedure for
13777 carbon stars. It includes positional data, distances,
extinctions, derived stellar parameters (Teff, Mass, Luminosity), and
dust parameters (optical depth, mass-loss rate, dust temperature). It
also provides the photometric data used (Gaia, 2MASS, WISE) and, for
Miras, the parameters derived from light curve fitting.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
catalog.dat 1088 13777 Catalogue of stellar and dust parameters (table 3)
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See also:
I/355 : Gaia DR3 Part 1. Main source (Gaia Collaboration, 2022)
II/246 : 2MASS All-Sky Catalog of Point Sources (Cutri+, 2003)
II/328 : AllWISE Data Release (Cutri+, 2013)
I/352 : Distances to 1.47 billion stars in Gaia EDR3 (Bailer-Jones+, 2021)
J/A+A/661/A147 : Galactic interstellar dust Gaia-2MASS 3D maps
(Lallement+, 2022)
Byte-by-byte Description of file: catalog.dat
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Bytes Format Units Label Explanations
--------------------------------------------------------------------------------
1- 19 I19 --- GaiaDR3 Gaia DR3 unique source identifier
(GaiaDR3_ID)
21- 36 A16 --- 2MASS 2MASS ID (2MASS_id)
38- 56 A19 --- AllWISE AllWISE ID (AllWISE_id)
58- 76 A19 --- OGLE OGLE ID (if available) (OGLE_ID)
78- 97 F20.16 deg RAdeg Right ascension (ICRS) at Ep=2016) (ra)
99- 110 F12.10 deg e_RAdeg Uncertainty in right ascension
(ra_error)
112- 131 F20.16 deg DEdeg Declination (ICRS) at Ep=2016) (dec)
133- 144 F12.10 deg e_DEdeg Uncertainty in declination (dec_error)
146- 169 E24.16 mas plx Gaia parallax (parallax)
171- 182 F12.10 mas e_plx Uncertainty in Gaia parallax
(parallax_error)
184- 195 F12.9 mas/yr PM Total proper motion from Gaia (pm)
197- 219 E23.15 mas/yr pmRA Proper motion in right ascension from
Gaia (pmra)
221- 232 F12.10 mas/yr e_pmRA Uncertainty in pmra from Gaia
(pmra_error)
234- 253 F20.16 mas/yr pmDE Proper motion in declination from Gaia
(pmdec)
255- 266 F12.10 mas/yr e_pmDE Uncertainty in pmdec from Gaia
(pmdec_error)
268- 279 F12.6 pc Distpc Distance from parallax or adopted value
from Bailer-Jones et al.
(2021AJ....161..147B 2021AJ....161..147B, Cat. I/352)
(distance_pc)
281- 287 F7.5 mag Ext Line-of-sight extinction from Lallement
et al. (2022A&A...661A.147L 2022A&A...661A.147L,
Cat. J/A+A/661/A147) 3D maps (ext)
289- 295 F7.5 mag e_Ext Uncertainty in extinction (exterr)
297- 316 F20.15 --- minchi2r Minimum chi2 value from SED fit
(MinChisquared)
318- 323 F6.1 K Teff Effective temperature (Teff)
325- 330 F6.1 K Tdust Inner dust shell temperature (Tdust)
332- 334 F3.1 Msun Mass Stellar mass (Mass)
336- 338 F3.1 --- AmC Fraction of amorphous carbon dust
(always 1.0) (AmC)
340- 362 F23.16 Lsun Lbol Bolometric luminosity (Lbol)
364- 382 F19.16 --- tau Optical depth (tau at 0.55um) (Tau)
384- 401 F18.16 --- C/O Carbon-to-oxygen ratio (C/O)
403- 421 F19.16 --- logtau Logarithmic optical depth
(tau at 0.55um) (Tau_log)
423- 444 E22.16 Msun/yr dM/dt Gas mass-loss rate (MassLossRate)
446- 465 F20.16 [Msun/yr] log(dM/dt) Logarithmic gas mass-loss rate
(MassLossRate_log)
467- 486 F20.15 --- e_minchi2r Uncertainty on minimum chi2
(MinChisquared_sigma)
488- 509 F22.17 K e_Teff Uncertainty in effective temperature
(Teff_sigma)
511- 529 F19.15 K e_Tdust Uncertainty in inner dust shell
temperature (Tdust_sigma)
531- 549 F19.17 Msun e_Mass Uncertainty in stellar mass
(Mass_sigma)
551- 574 E24.16 --- e_logtau Uncertainty in log optical depth
(Tausigmalog)
576- 599 E24.16 [Msun/yr] e_log(dM/dt) Uncertainty in log(Mass-Loss Rate)
(MassLossRatesigmalog)
601- 618 F18.16 --- meanFluxR Mean observed/model flux ratio for all
filters used in the fit
(offsetobservover_bestmodel)
620- 624 A5 --- MW [0/1] True = Milky Way member (mw)
626- 630 A5 --- SMC [0/1] True = Small Magellanic Cloud
member (smc)
632- 636 A5 --- LMC [0/1] True = Large Magellanic Cloud
member (lmc)
638- 656 F19.16 mag Windex Gaia-2MASS Wesenheit index
(Wesenheit_function)
658- 675 F18.14 d Period ? Pulsation period from multiband
light curve fit (Period)
677- 695 F19.16 mag Gmaglc ? Mean G magnitude from light curve
fit (Gmag_lcurve)
697- 714 F18.15 mag BPmaglc ? Mean BP magnitude from light curve
fit (BPmag_lcurve)
716- 734 F19.16 mag RPmaglc ? Mean RP magnitude from light curve
fit (RPmag_lcurve)
736- 753 F18.16 mag AmpBP ? Gaia BP-band amplitude from light
curve fit (BP_Amplitude)
755- 772 F18.16 mag AmpRP ? Gaia RP-band amplitude from light
curve fit (RP_Amplitude)
774- 791 F18.16 mag AmpG ? Gaia G-band amplitude from light
curve fit (G_Amplitude)
797 I1 --- Mira [0/1]? 1 = identified Mira variable
(Mira)
799- 821 F23.20 mag BPMAG Absolute BP magnitude (M_BP)
823- 844 F22.19 mag RPMAG Absolute RP magnitude (M_RP)
846- 868 F23.20 mag GMAG Absolute G magnitude (M_G)
870- 890 F21.18 mag JMAG Absolute J magnitude (M_J)
892- 913 F22.18 mag HMAG Absolute J magnitude (M_H)
915- 934 F20.16 mag W1MAG Absolute W1 magnitude (M_W1)
936- 956 F21.17 mag W2MAG Absolute W2 magnitude (M_W2)
958- 977 F20.16 mag W3MAG Absolute W3 magnitude (M_W3)
979- 998 F20.16 mag W4MAG Absolute W4 magnitude (M_W4)
1000-1019 F20.16 mag KMAG Absolute K magnitude (M_K)
1021-1028 F8.6 mag e_Gmag Uncertainty in G magnitude (e_Gmag)
1030-1037 F8.6 mag e_BPmag Uncertainty in BP magnitude (e_BPmag)
1039-1046 F8.6 mag e_RPmag Uncertainty in RP magnitude (e_RPmag)
1048-1052 F5.3 mag e_Jmag ? Uncertainty in J magnitude (e_Jmag)
1054-1058 F5.3 mag e_Hmag ? Uncertainty in H magnitude (e_Hmag)
1060-1064 F5.3 mag e_Kmag ? Uncertainty in K magnitude (e_Kmag)
1066-1070 F5.3 mag e_W1mag ? Uncertainty in W1 magnitude (e_W1mag)
1072-1076 F5.3 mag e_W2mag ? Uncertainty in W2 magnitude (e_W2mag)
1078-1082 F5.3 mag e_W3mag ? Uncertainty in W3 magnitude (e_W3mag)
1084-1088 F5.3 mag e_W4mag ? Uncertainty in W4 magnitude (e_W4mag)
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Acknowledgements:
From Alessio Liberatori, aliberatori(at)phys.uoa.gr
This project has received funding from the European Union's Horizon
2020 research and innovation programme under the Marie
Sklodowska-Curie grant agreement No 101072454 (Milky Way-Gaia Doctoral
Network).
(End) Patricia Vannier [CDS] 18-Feb-2026