Faint Quasars Live in the Same Number Density Environments as Lyman Break Galaxies at z ∼ 4
Bibliographic record
Abstract
Abstract Characterizing high-z quasar environments is key to understanding the coevolution of quasars and the surrounding galaxies. To restrict their global picture, we statistically examine the g-dropout galaxy overdensity distribution around 570 faint quasar candidates at z ∼ 4, based on the Hyper Suprime-Cam Subaru Strategic Program survey. We compare the overdensity significances of g-dropout galaxies around the quasars with those around g-dropout galaxies, and find no significant difference between their distributions. A total of 4 (22) out of the 570 faint quasars, , are found to be associated with the >4σ overdense regions within an angular separation of 1.8 (3.0) arcmin, which is the typical size of protoclusters at this epoch. This is similar to the fraction of g-dropout galaxies associated with the >4σ overdense regions. This result is consistent with our previous work in which and of luminous quasars detected in the Sloan Digital Sky Survey exist in the >4σ overdense regions within 1.′8 and 3.′0 separations, respectively. Therefore, we suggest that the galaxy number densities around quasars are independent of their luminosity, and most quasars do not preferentially appear in the richest protocluster regions at z ∼ 4. The lack of an apparent positive correlation between the quasars and the protoclusters implies that (i) the gas-rich major merger rate is relatively low in the protocluster regions, (ii) most high-z quasars may appear through secular processes, or (iii) some dust-obscured quasars exist in the protocluster regions.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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".