Based on results by recent surveys, the number of bright quasars at redshifts z > 3 is being constantly revised upward. The current consensus is that at bright magnitudes (M 1450 ≤ −27) the number densities of such sources could have been underestimated by a factor of 30%–40%. In the framework of the QUBRICS survey, we identified 58 bright QSOs at 3.6 ≤ z ≤ 4.2, with magnitudes i psf ≤ 18, in an area of 12400 deg2. The uniqueness of our survey is underlined by the fact that it allows us, for the first time, to extend the sampled absolute magnitude range up to M 1450 = −29.5. We derived a bright-end slope of β = −4.025 and a space density at 〈M 1450〉 = −28.75 of 2.61 × 10−10 Mpc−3 comoving, after taking into account the estimated incompleteness of our observations. Taking into account the results of fainter surveys, active galactic nuclei (AGNs) brighter than M 1450 = −23 could produce at least half of the ionizing emissivity at z ∼ 4. Considering a mean escape fraction of 0.7 for the QSO and AGN population, combined with a mean free path of 41.3 proper Mpc at z = 3.9, we derive a photoionization rate of , produced by AGNs at M 1450 < −18, that is, ∼100% of the measured ionizing background at z ∼ 4.
We present the results of the spectroscopic follow-up of the QUasars as BRIght beacons for Cosmology in the Southern Hemisphere (QUBRICS; Calderone et al. 2019) survey. The selection method is based on a machine-learning approach applied to photometric catalogs, covering an area of ∼12,400 deg2 in the Southern Hemisphere. The spectroscopic observations started in 2018 and identified 55 new, high-redshift (z ≥ 2.5), bright (i ≤ 18) quasi-stellar objects (QSOs), with the catalog published in late 2019. Here we report the current status of the survey, bringing the total number of bright QSOs at z ≥ 2.5 identified by QUBRICS to 224. The success rate of the QUBRICS selection method, in its most recent training, is estimated to be 68%. The predominant contaminant turns out to be lower-z QSOs at z < 2.5. This survey provides a unique sample of bright QSOs at high z available for a number of cosmological investigations. In particular, carrying out the redshift drift measurements (Sandage Test) in the Southern Hemisphere, using the High Resolution Spectrograph at the 39 m Extremely Large Telescope appears to be possible with less than 2500 hr of observations spread over 30 targets in 25 yr.
Motivated by evidences favoring a rapid and late hydrogen reionization process completing at z ∼ 5.2–5.5 and mainly driven by rare and luminous sources, we have reassessed the estimate of the space density of ultra-luminous QSOs at z ∼ 5 in the framework of the QUBRICS survey. A ∼ 90% complete sample of 14 spectroscopically confirmed QSOs at M 1450 ≤ −28.3 and 4.5 ≤ z ≤ 5.0 has been derived in an area of 12,400 deg2, thanks to multiwavelength selection and Gaia astrometry. The space density of z ∼ 5 QSOs within −29.3 ≤ M 1450 ≤ −28.3 is three times higher than previous determinations. Our results suggest a steep bright-end slope for the QSO luminosity function at z ∼ 5 and a mild redshift evolution of the space density of ultrabright QSOs (M 1450 ∼ −28.5) at 3 < z < 5.5, in agreement with the redshift evolution of the much fainter active galactic nucleus (AGN) population at M 1450 ∼ −23. These findings are consistent with a pure density evolution for the AGN population at z > 3. Adopting our z ∼ 4 QSO luminosity function and applying a mild density evolution in redshift, a photoionization rate of Γ HI = 0.46 − 0.09 + 0.17 × 10 − 12 s − 1 has been obtained at z = 4.75, assuming an escape fraction of ∼70% and a steep faint-end slope of the AGN luminosity function. The derived photoionization rate is ∼50–100% of the ionizing background measured at the end of the reionization epoch, suggesting that AGNs could play an important role in the cosmological reionization process.
The number of known, bright (i < 18), high-redshift (z > 2.5) QSOs in the Southern Hemisphere is considerably lower than the corresponding number in the Northern Hemisphere due to the lack of multi-wavelength surveys at δ < 0. Recent works, such as the QUBRICS survey, successfully identified new, high-redshift QSOs in the South by means of a machine learning approach applied on a large photometric dataset. Building on the success of QUBRICS, we present a new QSO selection method based on the Probabilistic Random Forest (PRF), an improvement of the classic Random Forest algorithm. The PRF takes into account measurement errors, treating input data as probability distribution functions: this allows us to obtain better accuracy and a robust predictive model. We applied the PRF to the same photometric dataset used in QUBRICS, based on the SkyMapper DR1, Gaia DR2, 2MASS, WISE and GALEX databases. The resulting candidate list includes 626 sources with i < 18. We estimate for our proposed algorithm a completeness of ∼84 per cent and a purity of $\sim 78{{\ \rm per\ cent}}$ on the test datasets. Preliminary spectroscopic campaigns allowed us to observe 41 candidates, of which 29 turned out to be z > 2.5 QSOs. The performances of the PRF, currently comparable to those of the CCA, are expected to improve as the number of high-z QSOs available for the training sample grows: results are however already promising, despite this being one of the first applications of this method to an astrophysical context.
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