The HerMES SPIRE submillimeter local luminosity function
Bibliographic record
Abstract
Local luminosity functions are fundamental benchmarks for high-redshift galaxy formation and evolution studies as well as for models describing these processes. Determining the local luminosity function in the submillimeter range can help to better constrain in particular the bolometric luminosity density in the local Universe, and Herschel offers the first opportunity to do so in an unbiased way by imaging large sky areas at several submillimeter wavelengths. We present the first Herschel measurement of the submillimeter 0 < z < 0.2 local luminosity function and infrared bolometric (8–1000 μm) local luminosity density based on SPIRE data from the HerMES Herschel key program over 14.7 deg2. Flux measurements in the three SPIRE channels at 250, 350 and 500 μm are combined with Spitzer photometry and archival data. We fit the observed optical-to-submillimeter spectral energy distribution of SPIRE sources and use the 1/Vmax estimator to provide the first constraints on the monochromatic 250, 350 and 500 μm as well as on the infrared bolometric (8–1000 μm) local luminosity function based on Herschel data. We compare our results with modeling predictions and find a slightly more abundant local submillimeter population than predicted by a number of models. Our measurement of the infrared bolometric (8–1000 μm) local luminosity function suggests a flat slope at low luminosity, and the inferred local luminosity density, 1.31-0.21+0.24 × 108 Mpc-3, is consistent with the range of values reported in recent literature.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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".