HerMES: unveiling obscured star formation – the far-infrared luminosity function of ultraviolet-selected galaxies at z ∼ 1.5
Bibliographic record
Abstract
We study the far-infrared and sub-millimetre properties of a sample of ultraviolet (UV) selected galaxies at z ∼ 1.5. Using stacking at 250, 350 and 500 μm from Herschel Space Observatory Spectral and Photometric Imaging Receiver (SPIRE) imaging of the Cosmological Evolution Survey (COSMOS) field obtained within the Herschel Multi-tiered Extragalactic Survey (HERMES) key programme, we derive the mean infrared (IR) luminosity as a function of both UV luminosity and slope of the UV continuum β. The IR to UV luminosity ratio is roughly constant over most of the UV luminosity range we explore. We also find that the IR to UV luminosity ratio is correlated with β. We observe a correlation that underestimates the correlation derived from low-redshift starburst galaxies, but is in good agreement with the correlation derived from local normal star-forming galaxies. Using these results we reconstruct the IR luminosity function of our UV-selected sample. This luminosity function recovers the IR luminosity functions measured from IR-selected samples at the faintest luminosities (LIR ∼ 1011 L⊙), but might underestimate them at the bright-end (LIR ≳ 5 × 1011 L⊙). For galaxies with 1011 < LIR/L⊙ < 1013, the IR luminosity function of an UV selection recovers (given the differences in IR-based estimates) 52–65 to 89–112 per cent of the star formation rate density derived from an IR selection. The cosmic star formation rate density derived from this IR luminosity function is 61–76 to 100–133 per cent of the density derived from IR selections at the same epoch. Assuming the latest Herschel results and conservative stacking measurements, we use a toy model to fully reproduce the far-IR luminosity function from our UV selection at z ∼ 1.5. This suggests that a sample around 4 mag deeper (i.e. reaching u* ∼ 30 mag) and a large dispersion of the IR to UV luminosity ratio are required.
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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 | 0.001 |
| 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) | 0.002 | 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".