YSO Variability in the W51 Star-Forming Region
Bibliographic record
Abstract
Time-domain studies of mid-infrared and submillimeter variability have shown that at least half of protostars are variable. We present a statistical analysis of mid-infrared variability among young stellar objects (YSOs) in the distant, massive star-forming region W51 using NEOWISE data. From a catalog of 81 protostars, 527 disk objects, and 37,687 other sources including diskless pre-main sequence and evolved contaminants, we identified significant variability in the 3.4 um (W1) and 4.6 um (W2) bands. Because of W51's distance (~5.4 kpc) and extinction, the sample mainly includes intermediate- to high-mass YSOs (>2 Msun), unlike nearby regions dominated by low-mass stars. This mass bias may affect the observed variability. In W2, 11.1% of protostars, 7.6% of disk objects, and 0.6% of PMS+E sources showed secular variability, while 8.6%, 2.3%, and 0.5% showed stochastic variability; similar fractions were found in W1. The variability fraction and amplitude increase toward earlier stages. Protostars exhibit high-amplitude stochastic changes likely driven by dynamic accretion and extinction, whereas disk objects show more secular patterns-linear, curved, or periodic-possibly due to moderate accretion variations or disk geometry. Color-magnitude analysis shows that protostars generally redden as they brighten, consistent with enhanced dust emission or variable extinction, while disk objects show mixed trends: roughly balanced in W1 but more often bluer in W2, suggesting reduced extinction or hotspot modulation. These results highlight distinct mechanisms of variability across evolutionary stages and demonstrate that mid-infrared monitoring offers key insight into accretion and disk evolution in young stars.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".