First Discoveries of z > 6 Quasars with the DECam Legacy Survey and UKIRT Hemisphere Survey
Bibliographic record
Abstract
Abstract We present the first discoveries from a survey of z ≳ 6 quasars using imaging data from the DECam Legacy Survey (DECaLS) in the optical, the UKIRT Deep Infrared Sky Survey (UKIDSS) and a preliminary version of the UKIRT Hemisphere Survey (UHS) in the near-IR, and ALLWISE in the mid-IR. DECaLS will image 9000 deg2 of sky down to z AB ∼ 23.0, and UKIDSS and UHS will map the northern sky at 0 < decl. < +60°, reaching J VEGA ∼ 19.6 (5-σ). The combination of these data sets allows us to discover quasars at redshift z ≳ 7 and to conduct a complete census of the faint quasar population at z ≳ 6. In this paper, we report on the selection method of our search, and on the initial discoveries of two new, faint z ≳ 6 quasars and one new z = 6.63 quasar in our pilot spectroscopic observations. The two new z ∼ 6 quasars are at z = 6.07 and z = 6.17 with absolute magnitudes at rest-frame wavelength 1450 Å being M 1450 = −25.83 and M 1450 = −25.76, respectively. These discoveries suggest that we can find quasars close to or fainter than the break magnitude of the Quasar Luminosity Function (QLF) at z ≳ 6. The new z = 6.63 quasar has an absolute magnitude of M 1450 = −25.95. This demonstrates the potential of using the combined DECaLS and UKIDSS/UHS data sets to find z ≳ 7 quasars. Extrapolating from previous QLF measurements, we predict that these combined data sets will yield ∼200 z ∼ 6 quasars to z AB < 21.5, ∼1000 z ∼ 6 quasars to z AB < 23, and ∼30 quasars at z > 6.5 to J VEGA < 19.5.
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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 | 0.000 |
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".