The WiggleZ Dark Energy Survey: star formation in UV-luminous galaxies from their luminosity functions
Bibliographic record
Abstract
We present the ultraviolet (UV) luminosity function of galaxies from the GALEX Medium Imaging Survey with measured spectroscopic redshifts from the first data release of the WiggleZ Dark Energy Survey.Our sample consists of 39 996 NUV < 22.8 emission line galaxies in the redshift range 0.1 < z < 0.9.This sample selects galaxies with high star formation rates: at 0.6 < z < 0.9 the median star formation rate is at the upper 95th percentile of optically selected (r < 22.5) galaxies and the sample contains about 50 per cent of all NUV < 22.8, 0.6 < z < 0.9 starburst galaxies within the volume sampled.The most luminous galaxies in our sample (-21.0 > M NUV > -22.5) evolve very rapidly with a number density declining as (1 + z) 5±1 from redshift z = 0.9 to 0.6.These starburst galaxies (M NUV < -21 is approximately a star formation rate of 30 M yr -1 ) contribute about 1 per cent of cosmic star formation over the redshift range z = 0.6-0.9.The star formation rate density of these very luminous galaxies evolves rapidly, as (1 + z) 4±1 .Such a rapid evolution implies that the majority of star formation in these large galaxies must have occurred before z = 0.9.We measure the UV luminosity function in z = 0.05 redshift intervals spanning 0.1 < z < 0.9, and provide analytic fits to the results.Our measurements of the luminosity function over this redshift range probe further into the bright end (1-2 mag further) than previous measurements, e.g.Arnouts et al., Budavári et al. and Treyer et al., due to our much larger sample size and sampled volume.At all redshifts z > 0.55 we find that the bright end of the luminosity function is not well described by a pure Schechter function due to an excess of very luminous
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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 | 0.003 | 0.002 |
| 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) | 0.003 | 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".