Herschel-Astrophysical Terahertz Large Area Survey: detection of a far-infrared population around galaxy clusters★
Bibliographic record
Abstract
We report the detection of a significant excess in the surface density of far-infrared sources from the Herschel-Astrophysical Terahertz Large Area Survey within ∼1 Mpc of the centres of 66 optically selected clusters of galaxies in the Sloan Digital Sky Survey with 〈z〉∼ 0.25. From the analysis of the multiwavelength properties of their counterparts we conclude that the far-infrared emission is associated with dust-obscured star formation and/or active galactic nuclei (AGN) within galaxies in the clusters themselves. The excess reaches a maximum at a radius of ∼0.8 Mpc, where we find 1.0 ± 0.3 S250 > 34 mJy sources on average per cluster above what would be expected for random field locations. If the far-infrared emission is dominated by star formation (as opposed to AGN) then this corresponds to an average star formation rate of ∼7 M⊙ yr−1 per cluster in sources with LIR > 5 × 1010 L⊙. Although lensed sources make a negligible contribution to the excess signal, a fraction of the sources around the clusters could be gravitationally lensed, and we have identified a sample of potential cases of cluster-lensed Herschel sources that could be targeted in follow-up studies.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".