Let the Great World Spin: Revealing the Stormy, Turbulent Nature of Young Giant Exoplanet Analogs with the Spitzer Space Telescope
Bibliographic record
Abstract
Abstract We present a survey for photometric variability in young, low-mass brown dwarfs with the Spitzer Space Telescope. The 23 objects in our sample show robust signatures of youth and share properties with directly imaged exoplanets. We present three new young objects: 2MASS J03492367+0635078, 2MASS J09512690−8023553, and 2MASS J07180871−6415310. We detect variability in 13 young objects, and find that young brown dwarfs are highly likely to display variability across the L2–T4 spectral type range. In contrast, the field dwarf variability occurrence rate drops for spectral types >L9. We examine the variability amplitudes of young objects and find an enhancement in maximum amplitudes compared to field dwarfs. We speculate that the observed range of amplitudes within a spectral type may be influenced by secondary effects such as viewing inclination and/or rotation period. We combine our new rotation periods with the literature to investigate the effects of mass on angular momentum evolution. While high-mass brown dwarfs (>30 M Jup ) spin up over time, the same trend is not apparent for lower-mass objects (<30 M Jup ), likely due to the small number of measured periods for old, low-mass objects. The rotation periods of companion brown dwarfs and planetary-mass objects are consistent with those of isolated objects with similar ages and masses, suggesting similar angular momentum histories. Within the AB Doradus group, we find a high-variability occurrence rate and evidence for common angular momentum evolution. The results are encouraging for future variability searches in directly imaged exoplanets with facilities such as the James Webb Space Telescope and 30 m telescopes.
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 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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".