The near and mid-infrared photometric properties of known redshift <i>z</i> ≥ 5 quasars

Ross, Nicholas P.; Cross, Nicholas

doi:10.1093/mnras/staa544

Cited by 30 publications

(11 citation statements)

References 172 publications

(153 reference statements)

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“…In Fig. 10, we show the observed colours of known 𝑧 > 5 quasars using force-photometered data from Ross & Cross (2020). We remove all photometric measurements which have uncertainties greater than 0.3 mag.…”

Section: High Redshift Quasarsmentioning

confidence: 99%

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Modelling type 1 quasar colours in the era of Rubin and Euclid

Temple

Hewett

Banerji

2021

Monthly Notices of the Royal Astronomical Society

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We construct a parametric SED model which is able to reproduce the average observed SDSS-UKIDSS-WISE quasar colours to within one tenth of a magnitude across a wide range of redshift (0 < z < 5) and luminosity (−22 > Mi > −29). This model is shown to provide accurate predictions for the colours of known quasars which are less luminous than those used to calibrate the model parameters, and also those at higher redshifts z > 5. Using a single parameter, the model encapsulates an up-to-date understanding of the intra-population variance in the rest-frame ultraviolet and optical emission lines of luminous quasars. At fixed redshift, there are systematic changes in the average quasar colours with apparent i-band magnitude, which we find to be well explained by the contribution from the host galaxy and our parametrization of the emission-line properties. By including redshift as an additional free parameter, the model could be used to provide photometric redshifts for individual objects. For the population as a whole we find that the average emission line and host galaxy contributions can be well described by simple functions of luminosity which account for the observed changes in the average quasar colours across 18.1 < iAB < 21.5. We use these trends to provide predictions for quasar colours at the luminosities and redshifts which will be probed by the Rubin Observatory LSST and ESA-Euclid wide survey. The model code is applicable to a wide range of upcoming photometric and spectroscopic surveys, and is made publicly available.

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Section: High Redshift Quasarsmentioning

confidence: 99%

“…Figure 10. Black points: the observed colours of individual 𝑧 > 5 quasars fromRoss & Cross (2020). Any colours for a quasar involving a magnitude uncertainty >0.3 mag are excluded.…”

mentioning

confidence: 99%

Modelling type 1 quasar colours in the era of Rubin and Euclid

Temple

Hewett

Banerji

2021

Monthly Notices of the Royal Astronomical Society

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“…Our new list-driven catalogue is produced by performing aperture photometry in each band at the position of every object that is detected in the VIKING J band, and applying an aperture correction appropriate for a point source. Further details of the creation of the list-driven catalogue will be provided in a forthcoming paper (Cross et al, in prep.; see also Ross & Cross 2020).…”

Section: Viking Surveymentioning

confidence: 95%

A complete search for redshift z>6.5 quasars in the VIKING survey

Barnett,

Warren,

Cross

et al. 2020

Preprint

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We present the results of a new, deeper, and complete search for high-redshift z > 6.5 quasars over 977 deg 2 of the VISTA Kilo-Degree Infrared Galaxy Survey (VIKING) survey, that is sensitive out to z ∼ 9.3. This exploits a new list-driven dataset providing aperture fluxes and uncertainties in all bands ZY JHK s , for all sources detected by VIKING in J. We used the Bayesian model comparison (BMC) selection method of Mortlock et al., producing a ranked list of just 21 candidates. The sources ranked 1, 2, 3 and 5 are the four known z > 6.5 quasars in this field. Additional observations of the other 17 candidates, primarily DESI Legacy Survey photometry and ESO FORS2 spectroscopy, confirm that none is a quasar. This is the first complete sample (i.e., all candidates followed up) from the VIKING survey, and we provide the computed selection function. We also compute selection functions for samples produced by two other methods: colour cuts and minimum-χ 2 SED fitting. Comparison of the efficiency (fraction of candidates that are quasars) and the depth of the three methods leads to the following conclusions: i) BMC produces eight times fewer false positives than colour cuts, while also reaching 0.3 mag. deeper, ii) the minimum-χ 2 SED fitting method is extremely efficient but reaches 0.7 mag less deep than the BMC method, picking out only one of the four known quasars. By additionally following up BMC candidates rejected because their photometric SEDs have high χ 2 values, we identify a population of galaxies where very strong [OIII]λλ4959,5007 emission in the Y band can mimic the colours of quasars, i.e., from Lyα and a blue continuum. This is a potential additional contaminant population in future searches for faint high-redshift quasars (such as in Euclid), not previously identified as such, and that requires better characterisation.

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“…These expectations collide with the most recent compilations (see, for instance, Refs. [11,12]), which show that only ∼300 sources have been confirmed to exist at z > 6 over most of the sky. Environmental (CMB) and intrinsic (QSO versus radio mode accretion) conditions might be responsible for the lower rate of radio powerful sources at z > 5 but, selection criteria, might also be playing a role [13].…”

Section: Introductionmentioning

confidence: 98%

Exploring New Redshift Indicators for Radio-Powerful AGN

et al. 2021

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Active Galactic Nuclei (AGN) are relevant sources of radiation that might have helped reionising the Universe during its early epochs. The super-massive black holes (SMBHs) they host helped accreting material and emitting large amounts of energy into the medium. Recent studies have shown that, for epochs earlier than z∼5, the number density of SMBHs is on the order of few hundreds per square degree. Latest observations place this value below 300 SMBHs at z≳6 for the full sky. To overcome this gap, it is necessary to detect large numbers of sources at the earliest epochs. Given the large areas needed to detect such quantities, using traditional redshift determination techniques—spectroscopic and photometric redshift—is no longer an efficient task. Machine Learning (ML) might help obtaining precise redshift for large samples in a fraction of the time used by other methods. We have developed and implemented an ML model which can predict redshift values for WISE-detected AGN in the HETDEX Spring Field. We obtained a median prediction error of σzN=1.48×(zPredicted−zTrue)/(1+zTrue)=0.1162 and an outlier fraction of η=11.58% at (zPredicted−zTrue)/(1+zTrue)>0.15, in line with previous applications of ML to AGN. We also applied the model to data from the Stripe 82 area obtaining a prediction error of σzN=0.2501.

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The near and mid-infrared photometric properties of known redshift z ≥ 5 quasars

Cited by 30 publications

References 172 publications

Modelling type 1 quasar colours in the era of Rubin and Euclid

Modelling type 1 quasar colours in the era of Rubin and Euclid

A complete search for redshift z>6.5 quasars in the VIKING survey

Exploring New Redshift Indicators for Radio-Powerful AGN

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