First Results from the Canada‐France High‐<i>z</i>Quasar Survey: Constraints on the<i>z</i>= 6 Quasar Luminosity Function and the Quasar Contribution to Reionization
Bibliographic record
Abstract
We present preliminary results of a new quasar survey being undertaken with multicolor optical imaging from the Canada-France-Hawaii Telescope. The current data consist of 3.83 deg 2 of imaging in the i ' and z ' filters to a 10 σ limit of z ' < 23.35. Near-infrared photometry of 24 candidate 5.7 < z < 6.4 quasars confirms them all to be low-mass stars, including two T dwarfs and four or five L dwarfs. Photometric estimates of the spectral type of the two T dwarfs are T3 and T6. We use the lack of high-redshift quasars in this survey volume to constrain the z = 6 quasar luminosity function. For reasonable values of the break absolute magnitude M and faint-end slope α, we determine that the bright-end slope β > -3.2 at 95% confidence. We find that the comoving space density of quasars brighter than M 1450 = -23.5 declines by a factor of >25 from z = 2 to 6, mirroring the decline observed for high-luminosity quasars. We consider the contribution of the quasar population to the ionizing photon density at z = 6 and the implications for reionization. We show that the current constraints on the quasar population give an ionizing photon density ≪30% that of the star-forming galaxy population. We conclude that active galactic nuclei make a negligible contribution to the reionization of hydrogen at z ~ 6.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".