A Steep Decline in the Galaxy Space Density beyond Redshift 9 in the CANUCS UV Luminosity Function
Bibliographic record
Abstract
Abstract We present a new sample of 158 galaxies at redshift z > 7.5 selected from deep James Webb Space Telescope (JWST) NIRCam imaging of five widely separated sight lines in the CANUCS survey. Two-thirds of the pointings and 80% of the galaxies are covered by 12–14 NIRCam filters, including seven to nine medium bands, providing accurate photometric redshifts and robustness against low-redshift interlopers. A sample of 28 galaxies at z > 7.5 with spectroscopic redshifts shows a low systematic offset and scatter in the difference between photometric and spectroscopic redshifts. We derive the galaxy UV luminosity function at redshifts 8–12, finding a slightly higher normalization than previously seen with the Hubble Space Telescope at redshifts 8–10. We observe a steeper decline in the galaxy space density from z = 8 to 12 than found by most JWST Cycle 1 studies. In particular, we find only eight galaxies at z > 10 and none at z > 12.5, with no z > 10 galaxies brighter than F277W AB = 28 or M UV = −20 in our unmasked, delensed survey area of 53.4 arcmin2. We attribute the lack of bright z > 10 galaxies in CANUCS compared to GLASS and CEERS to intrinsic variance in the galaxy density along different sight lines. The evolution in the CANUCS luminosity function between z = 8 and 12 is comparable to that predicted by simulations that assume a standard star formation efficiency without invoking any special adjustments.
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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 | 0.001 |
| 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".