MAMMOTH-Subaru. II. Diverse Populations of Circumgalactic Lyα Nebulae at Cosmic Noon
Bibliographic record
Abstract
Abstract Circumgalactic Lyα nebulae are gaseous halos around galaxies exhibiting luminous extended Lyα emission. This work investigates Lyα nebulae from deep imaging of ∼12 deg2 sky, targeted by the MAMMOTH-Subaru survey. Utilizing the wide-field capability of Hyper Suprime-Cam, we present one of the largest blind Lyα nebula selections, including QSO nebulae, Lyα blobs, and radio galaxy nebulae down to the typical 2σ Lyα surface brightness of ( 5 - 10 ) × 10 − 18 erg s − 1 cm − 2 arcsec − 2 . The sample contains 117 nebulae with Lyα sizes of 40–400 kpc, and the most gigantic one spans about 365 kpc, and is referred to as the Ivory Nebula. Combining multiwavelength data, we investigate diverse nebula populations and associated galaxies. We find a small fraction of Lyα nebulae have QSOs (∼7%), luminous infrared galaxies (LIRGs; ∼1%), and radio galaxies (∼2%). Remarkably, among the 28 enormous Lyα nebulae (ELANe) exceeding 100 kpc, about 80% are associated with UV-faint galaxies (M UV > −22), and are categorized as Type II ELANe. We underscore that Type II ELANe constitute the majority but remain largely hidden in current galaxy and QSO surveys. Dusty starburst and obscured AGN activity are proposed to explain the nature of Type II ELANe. The spectral energy distribution of stacking all Lyα nebulae also reveals signs of massive dusty star-forming galaxies with obscured AGNs. We propose a model to explain the dusty nature where the diverse populations of Lyα nebulae capture massive galaxies at different evolutionary stages undergoing violent assembly. Lyα nebulae provide critical insights into the formation and evolution of today’s massive cluster galaxies at cosmic noon.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".