Herschel Multitiered Extragalactic Survey: clusters of dusty galaxies uncovered by Herschel★ and Planck†
Bibliographic record
Abstract
The potential for Planck to detect clusters of dusty, star-forming galaxies at z > 1 is tested by examining the Herschel-SPIRE images of Planck Early Release Compact Source Catalog sources lying in fields observed by the Herschel Multitiered Extragalactic Survey. Of the 16 Planck sources that lie in the ∼90 sq. deg. examined, we find that 12 are associated with single bright Herschel sources. The remaining four are associated with overdensities of Herschel sources, making them candidate clusters of dusty, star-forming galaxies. We use complementary optical/near-IR data for these ‘clumps’ to test this idea, and find evidence for the presence of galaxy clusters in all four cases. We use photometric redshifts and red sequence galaxies to estimate the redshifts of these clusters, finding that they range from 0.8 to 2.3. These redshifts imply that the Herschel sources in these clusters, which contribute to the detected Planck flux, are forming stars very rapidly, with typical total cluster star formation rates >1000 M⊙ yr−1. The high-redshift clusters discovered in these observations are used to constrain the epoch of cluster galaxy formation, finding that the galaxies in our clusters are 1–1.5 Gyr old at z ∼ 1–2. Prospects for the discovery of further clusters of dusty galaxies are discussed, using not only all sky Planck surveys, but also deeper, smaller area, Herschel surveys.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".