Keck Deep Fields. III. Luminosity‐dependent Evolution of the Ultraviolet Luminosity and Star Formation Rate Densities at<i>z</i>∼4, 3, and 2
Bibliographic record
Abstract
We use our very deep U n G I catalog of z ~ 4, 3, and 2 UV-selected star-forming galaxies to study the cosmological evolution of the rest-frame 1700 Å luminosity density. The ability to reliably constrain the contribution of faint galaxies is critical here, and our data do so by reaching deep into the galaxy population, to M + 2 at z ~ 4 and deeper still at lower redshifts ( M = -21.0 and L is the corresponding luminosity). We find that the luminosity density at z ≳ 2 is dominated by the hitherto poorly studied galaxies fainter than L , and, indeed, the bulk of the UV light at these epochs comes from galaxies in the rather narrow luminosity range L = (0.1-1) L . Overall, there is a gradual rise in total luminosity density starting at ≳4 (we find twice as much UV light at z ~ 3 as at z ~ 4), followed by a shallow peak or plateau within z ~ 3-1, finally followed by the well-known plunge to z ~ 0. Within this total picture, luminosity density in sub- L galaxies at z ≳ 2 evolves more rapidly than that in more luminous objects; this trend is reversed at lower redshifts, z ≲ 1—a reversal that is reminiscent of galaxy downsizing. We find that within the context of commonly used models there seemingly are not enough faint or bright LBGs to maintain ionization of intergalactic gas even as recently as z ~ 4, and the problem becomes worse at higher redshifts: apparently the universe must be easier to reionize than some recent studies have assumed. Nevertheless, sub- L galaxies do dominate the total UV luminosity density at z ≳ 2, and this dominance highlights the need for follow-up studies that will teach us more about these very numerous but thus far largely unexplored systems.
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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 | 0.002 | 0.001 |
| 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) | 0.003 | 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".