J/A+A/708/L1 Pre-main sequence stars masses (Zallio+, 2026)
Benchmarking pre-main sequence stellar evolutionary tracks using disk-based
dynamical stellar masses.
Zallio L., Vioque M., Andrews S.M., Empey A., Rosotti G.P., Miotello A.,
Manara C.F., Carpenter J.M., Deng D., Kurtovic N.T., Law C.J., Longarini C.,
Paneque-Carreno T., Teague R., Villenave M., Yen H.S., Zagaria F.
<Astron. Astrophys. 708, L1 (2026)>
=2026A&A...708L...1Z 2026A&A...708L...1Z (SIMBAD/NED BibCode)
ADC_Keywords: Stars, pre-main sequence ; Stars, masses ; Carbon monoxide ;
Models
Keywords: stars: general - Hertzsprung-Russell and C-M diagrams -
planetary disks - stars: pre-main sequence - stars: protostars -
starspots
Abstract:
Stellar masses are a fundamental property to understand models of
pre-main sequence evolution, but their values derived from
Hertzsprung-Russell (HR) diagrams are strongly model dependent. We
benchmark pre-main sequence stellar evolutionary tracks using stellar
masses dynamically estimated by fitting a parametric model to ALMA
observations of the 12CO (J=3-2) line transition emitted by
the disks orbiting 20 sources in the old (4-14Myr) Upper Scorpius
star forming region. We derive stellar masses from HR diagram fitting
for ten different stellar evolutionary models, which we then compare
with their stellar dynamical masses for comparison in the stellar mass
range 0.1-1.3M☉. Models with a moderate-to-low fraction of
cold stellar spots (f=17%) most accurately reproduce the dynamical
stellar masses (100% of the targets agree within ±1σ). While a
higher spot coverage (f=34%) provides similar stellar mass predictions
similar to magnetic equipartition models, larger fractions (f≥51%)
significantly disagree with dynamical masses. Magnetic equipartition
models overestimate stellar masses up to a factor ∼20%, whereas
non-magnetic mod- els underestimate them up to ∼12%. For some models,
there is evidence that the stellar mass discrepancies are
anticorrelated with dynamical stellar masses. When stellar dynamical
mass priors are considered in HR diagram fitting, the median age of a
single source can change up to ∼25%, while the median ages inferred
across different tracks become consistent, with the age scatter
decreasing by ∼77%. These results provide strong empirical constraints
for testing and developing evolutionary models of pre-main sequence
stars.
Description:
Table containing the stellar masses considered in this work. The
disk-based dynamical masses were taken from Zallio et al.
(2026A&A...705A..49Z 2026A&A...705A..49Z, Cat. J/A+A/705/A49)
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
tabled1.dat 480 25 stellar masses considered in this work
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See also:
J/A+A/705/A49 : 12CO gas structures of protoplanetary disks (Zallio+, 2026)
Byte-by-byte Description of file: tabled1.dat
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Bytes Format Units Label Explanations
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1- 17 A17 --- 2MASS 2MASS source identifier, JHHMMMSSss+DDMMSSs
(Source_2MASS)
19- 37 A19 --- GaiaDR3 Gaia DR3 source identifier (Gaia_DR3)
39- 50 E12.6 deg RAdeg Right ascension (ICRS) at Ep=2016.0
(Gaia DR3) (RA_GaiaDR3)
52- 64 E13.6 deg DEdeg Declination (ICRS) at Ep=2016.0 (Gaia DR3)
(DEC_GaiaDR3)
66- 77 E12.6 Msun Mcsalt Stellar mass from csalt (M_csalt)
79- 90 E12.6 Msun e_Mcsalt Uncertainty on M_csalt (err_csalt)
92-103 E12.6 Msun B15Mass ?=- Mass from Baraffe et al.
(2015A&A...577A..42B 2015A&A...577A..42B) tracks
(Baraffe15_mass)
105-116 E12.6 Msun e_B15Mass ?=- Lower uncertainty on B15Mass
(16th percentile) (Baraffe15errlow)
118-129 E12.6 Msun E_B15Mass ?=- Upper uncertainty on B15Mass
(84th percentile) (Baraffe15errup)
131-142 E12.6 Msun F16noBMass ?=- Mass from Feiden et al.
(2016A&A...593A..99F 2016A&A...593A..99F) tracks (no B)
(Feiden16noBmass)
144-155 E12.6 Msun e_F16noBMass ?=- Lower uncertainty of F16noBMass
(Feiden16noBerr_low)
157-168 E12.6 Msun E_F16noBMass ?=- Upper uncertainty of F16noBMass
(Feiden16noBerr_up)
170-181 E12.6 Msun F16BMass ?=- Mass from Feidenet al.
(2016A&A...593A..99F 2016A&A...593A..99F) tracks (with B)
(Feiden16Bmass)
183-194 E12.6 Msun e_F16BMass ?=- Lower uncertainty of F16BMass
(Feiden16Berr_low)
196-207 E12.6 Msun E_F16BMass ?=- Upper uncertainty of F16BMass
(Feiden16Berr_up)
209-220 E12.6 Msun PMass ?=- Mass from PARSEC v2.0 tracks
(PARSEC_mass)
222-233 E12.6 Msun e_PMass ?=- Lower uncertainty on PMass
(PARSECerrlow)
235-246 E12.6 Msun E_PMass ?=- Upper uncertainty on PMass
(PARSECerrup)
248-259 E12.6 Msun S20Mass ?=- Mass from Siess et al.
(2000A&A...358..593S 2000A&A...358..593S) tracks
(Siess2000_mass)
261-272 E12.6 Msun e_S20Mass ?=- Lower uncertainty on S20Mass
(Siess2000errlow)
274-285 E12.6 Msun E_S20Mass ?=- Upper uncertainty on S20Mass
(Siess2000errup)
287-298 E12.6 Msun Sf0Mass ?=- Mass from SPOTS models (f=0%)
(SPOTSf0mass)
300-311 E12.6 Msun e_Sf0Mass ?=- Lower uncertainty on Sf0Mass
(SPOTSf0err_low)
313-324 E12.6 Msun E_Sf0Mass ?=- Upper uncertainty on Sf0Mass
(SPOTSf0err_up)
326-337 E12.6 Msun Sf17Mass ?=- Mass from SPOTS models (f=17%)
(SPOTSf17mass)
339-350 E12.6 Msun e_Sf17Mass ?=- Lower uncertainty on Sf17Mass
(SPOTSf17err_low)
352-363 E12.6 Msun E_Sf17Mass ?=- Upper uncertainty on Sf17Mass
(SPOTSf17err_up)
365-376 E12.6 Msun Sf34Mass ?=- Mass from SPOTS models (f=34%)
(SPOTSf34mass)
378-389 E12.6 Msun e_Sf34Mass ?=- Lower uncertainty on Sf34Mass
(SPOTSf34err_low)
391-402 E12.6 Msun E_Sf34Mass ?=- Upper uncertainty on Sf34Mass
(SPOTSf34err_up)
404-415 E12.6 Msun Sf51Mass ?=- Mass from SPOTS models
(f=51%) (SPOTSf51mass)
417-428 E12.6 Msun e_Sf51Mass ?=- Lower uncertainty on Sf51Mass
(SPOTSf51err_low)
430-441 E12.6 Msun E_Sf51Mass ?=- Upper uncertainty on Sf51Mass
(SPOTSf51err_up)
443-454 E12.6 Msun Sf85Mass ?=- Mass from SPOTS models (f=85%)
(SPOTSf85mass)
456-467 E12.6 Msun e_Sf85Mass ?=- Lower uncertainty on Sf85Mass
(SPOTSf85err_low)
469-480 E12.6 Msun E_Sf85Mass ?=- Upper uncertainty on Sf85Mass
(SPOTSf85err_up)
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Acknowledgements:
Luigi Zallio, luigi.zallio(at)unimi.it
License: CC-BY-4.0 [see https://spdx.org/licenses/]
(End) Patricia Vannier [CDS] 19-Mar-2026