Benchmarking pre-main sequence stellar evolutionary tracks using disk-based dynamical stellar masses

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 12 CO ( J = 3 − 2) line transition emitted by the disks orbiting 20 sources in the old (4 − 14 Myr) 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 − 1.3 M ⊙ . 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 ±1 σ ). 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 models 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.

Institutions

Publication Details

Journal
Astronomy and Astrophysics
Published
2026-03-12
DOI
https://doi.org/10.1051/0004-6361/202558147
Primary Topic
Stellar, planetary, and galactic studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Benchmarking pre-main sequence stellar evolutionary tracks using disk-based dynamical stellar masses

Astronomy and Astrophysics
Stellar, planetary, and galactic studies
article

Benchmarking pre-main sequence stellar evolutionary tracks using disk-based dynamical stellar masses

article en

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 12 CO ( J = 3 − 2) line transition emitted by the disks orbiting 20 sources in the old (4 − 14 Myr) 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 − 1.3 M ⊙ . 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 ±1 σ ). 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 models 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.

Astronomy and AstrophysicsVol. 708
University College Dublin (IE), Centre National de la Recherche Scientifique (FR), Institute of Astronomy and Astrophysics, Academia Sinica (TW), University of Arizona (US), University of Milan (IT), University of Cambridge (GB), University of Michigan (US), Atacama Large Millimeter Submillimeter Array (CL), Max Planck Institute for Extraterrestrial Physics (DE), Max Planck Institute for Astronomy (DE), Institute of Astronomy (RU), Center for Astrophysics Harvard & Smithsonian (US), University of Virginia (US), Lunar and Planetary Institute (US), Massachusetts Institute of Technology (US), Université Grenoble Alpes (FR)
Openalex Percentile: Top 28%
Stellar, planetary, and galactic studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.