Very Low-mass Stars and Brown Dwarfs in Upper Scorpius Using Gaia DR1: Mass Function, Disks, and Kinematics
Bibliographic record
Abstract
Abstract Our understanding of the brown dwarf population in star-forming regions is dependent on knowing distances and proper motions and therefore will be improved through the Gaia space mission. In this paper, we select new samples of very low-mass objects (VLMOs) in Upper Scorpius using UKIDSS colors and optimized proper motions calculated using Gaia DR1. The scatter in proper motions from VLMOs in Upper Scorpius is now (for the first time) dominated by the kinematic spread of the region itself, not by the positional uncertainties. With age and mass estimates updated using Gaia parallaxes for early-type stars in the same region, we determine masses for all VLMOs. Our final most complete sample includes 453 VLMOs of which ∼125 are expected to be brown dwarfs. The cleanest sample is comprised of 131 VLMOs, with ∼105 brown dwarfs. We also compile a joint sample from the literature that includes 415 VLMOs, out of which 152 are likely brown dwarfs. The disk fraction among low-mass brown dwarfs ( <?CDATA $M\lt 0.05\,{M}_{\odot }$?> ) is substantially higher than in more massive objects, indicating that disks around low-mass brown dwarfs survive longer than in low-mass stars overall. The mass function for <?CDATA $0.01\lt M\lt 0.1\,{M}_{\odot }$?> is consistent with the Kroupa Initial Mass Function. We investigate the possibility that some “proper motion outliers” have undergone a dynamical ejection early in their evolution. Our analysis shows that the color–magnitude cuts used when selecting samples introduce strong bias into the population statistics due to varying levels of contamination and completeness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".