Hotspots and a clumpy disc: variability of brown dwarfs and stars in the young σ Ori cluster
Bibliographic record
Abstract
The properties of accretion discs around stars and brown dwarfs in the σ Ori cluster (age 3 Myr) are studied based on near-infrared (IR) time series photometry supported by mid-IR spectral energy distributions (SEDs). We monitor ∼30 young low-mass sources over eight nights in the J and K band using the duPont telescope at Las Campanas. We find three objects showing variability with J-band amplitudes ≥0.5 mag; five additional objects exhibit low-level variations. All three highly variable sources have been previously identified as highly variable; thus, we establish the long-term nature of their flux changes. The light curves contain periodic components with time-scales of ∼0.5–8 d, but have additional irregular variations superimposed – the characteristic behaviour for classical T Tauri stars. Based on the colour variability, we conclude that hotspots are the dominant cause of variations in two objects (#19 and #33), including one likely brown dwarf, with spot temperatures in the range of 6000–7000 K. For the third one (#2), a brown dwarf or very low-mass star, inhomogeneities at the inner edge of the disc are the likely origin of variability. Based on mid-IR data from Spitzer, we confirm that the three highly variable sources are surrounded by circum-(sub)-stellar discs. They show typical SEDs for T Tauri-like objects. Using SED models, we infer an enhanced scaleheight in the disc for the object #2, which favours the detection of disc inhomogeneities in light curves and is thus consistent with the information from variability. In the σ Ori cluster, about every fifth accreting low-mass object shows persistent high-level photometric variability. We demonstrate that estimates for fundamental parameters in such objects can be significantly improved by determining the extent and origin of the variations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".