UV and U-band luminosity functions from CLAUDS and HSC-SSP – I. Using four million galaxies to simultaneously constrain the very faint and bright regimes to z ∼ 3
Bibliographic record
Abstract
ABSTRACT We constrain the rest-frame FUV (1546 Å), NUV (2345 Å), and U-band (3690 Å) luminosity functions (LFs) and luminosity densities (LDs) with unprecedented precision from z ∼ 0.2 to z ∼ 3 (FUV, NUV) and z ∼ 2 (U band). Our sample of over 4.3 million galaxies, selected from the CFHT Large Area U-band Deep Survey (CLAUDS) and HyperSuprime-Cam Subaru Strategic Program (HSC-SSP) data lets us probe the very faint regime (down to MFUV, MNUV, MU ≃ −15 at low redshift), while simultaneously detecting very rare galaxies at the bright end down to comoving densities <10−5 Mpc−3. Our FUV and NUV LFs are well fitted by single-Schechter functions, with faint-end slopes that are very stable up to z ∼ 2. We confirm, but self-consistently and with much better precision than previous studies, that the LDs at all three wavelengths increase rapidly with lookback time to z ∼ 1, and then much more slowly at 1 < z < 2–3. Evolution of the FUV and NUV LFs and LDs at z < 1 is driven almost entirely by the fading of the characteristic magnitude, $M^\star _{\rm UV}$, while at z > 1 it is due to the evolution of both $M^\star _{\rm UV}$ and the characteristic number density $\phi ^\star _{\rm UV}$. In contrast, the U-band LF has an excess of faint galaxies and is fitted with a double-Schechter form; $M^\star _{U}$, both $\phi ^\star _{U}$ components, and the bright-end slope evolve throughout 0.2 < z < 2, while the faint-end slope is constant over at least the measurable 0.05 < z < 0.6. We present tables of our Schechter parameters and LD measurements that can be used for testing theoretical galaxy evolution models and forecasting future observations.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".