Subaru High-z Exploration of Low-luminosity Quasars (SHELLQs). V. Quasar Luminosity Function and Contribution to Cosmic Reionization at z = 6
Bibliographic record
Abstract
Abstract We present new measurements of the quasar luminosity function (LF) at z ∼ 6 over an unprecedentedly wide range of the rest-frame ultraviolet luminosity M 1450 from −30 to −22 mag. This is the fifth in a series of publications from the Subaru High- z Exploration of Low-Luminosity Quasars (SHELLQs) project, which exploits the deep multiband imaging data produced by the Hyper Suprime-Cam Subaru Strategic Program survey. The LF was calculated with a complete sample of 110 quasars at 5.7 ≤ z ≤ 6.5, which includes 48 SHELLQs quasars discovered over 650 deg 2 and 63 brighter quasars discovered by the Sloan Digital Sky Survey and the Canada–France–Hawaii Quasar Survey (including one overlapping object). This is the largest sample of z ∼ 6 quasars with a well-defined selection function constructed to date, which has allowed us to detect significant flattening of the LF at its faint end. A double power-law function fit to the sample yields a faint-end slope , a bright-end slope , a break magnitude , and a characteristic space density Gpc −3 mag −1 . Integrating this best-fit model over the range −18 < M 1450 < −30 mag, quasars emit ionizing photons at the rate of s −1 Mpc −3 at z = 6.0. This is less than 10% of the critical rate necessary to keep the intergalactic medium ionized, which indicates that quasars are not a major contributor to cosmic reionization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".