Clustering of intermediate redshift quasars using the final SDSS III-BOSS sample
Bibliographic record
Abstract
We measure the two-point clustering of spectroscopically confirmed quasars from the final sample of the Baryon Oscillation Spectroscopic Survey (BOSS) on comoving scales of 4 ≲ s ≲ 22 h−1 Mpc. The sample covers 6950 deg2 [ ∼ 19 (h− 1Gpc)3] and, over the redshift range 2.2 ≤ z ≤ 2.8, contains 55 826 homogeneously selected quasars, which is twice as many as in any similar work. We deduce bQ = 3.54 ± 0.10; the most precise measurement of quasar bias to date at these redshifts. This corresponds to a host halo mass of ∼2 × 1012 h−1 M⊙ with an implied quasar duty cycle of ∼1 per cent. The real-space projected correlation function is well fitted by a power law of index 2 and correlation length r0 = (8.12 ± 0.22) h− 1 Mpc over scales of 4 ≲ rp ≲ 25 h−1 Mpc. To better study the evolution of quasar clustering at moderate redshift, we extend the redshift range of our study to z ∼ 3.4 and measure the bias and correlation length of three subsamples over 2.2 ≤ z ≤ 3.4. We find no significant evolution of r0 or bias over this range, implying that the host halo mass of quasars decreases somewhat with increasing redshift. We find quasar clustering remains similar over a decade in luminosity, contradicting a scenario in which quasar luminosity is monotonically related to halo mass at z ≈ 2.5. Our results are broadly consistent with previous BOSS measurements, but they yield more precise constraints based upon a larger and more uniform data set.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".