2. Candidate selection

Finding bright quasars has been greatly simplified in modern times, first with the all-sky survey of the Wide-field Infrared Survey Explorer (WISE; Wright et al. Reference Wright2010 ; Mainzer et al. 2014 ), and more recently with the accurate parallax and proper motion information from the all-sky survey of Gaia. Several authors have proposed very effective methods for selecting quasar candidates exploiting these data sets using hard selection cuts, Bayesian probabilities, or machine-learning approaches (e.g., Calderone et al. Reference Calderone2019; Shu et al. Reference Shu2019; Wolf et al. Reference Wolf2020). Here, we choose a very simple approach, given that we focus our interest at bright magnitudes, where the stars, galaxies, and quasars can be easily separated, as demonstrated below.

We avoid the vicinity of the Galactic Plane, where quasars are dimmed by dust extinction and are harder to identify reliably due to source crowding biasing the photometry, especially in the WISE catalogue, where the large point spread function in the infrared passbands leads to blending. Effective searches in the Galactic Plane include the work of Fu et al. (Reference Fu2022), who have recently discovered 191 new quasars, five of which are brighter than $i=16$ ABmag. In contrast, we restrict our search to a Galactic latitude of $|b|>10^\circ$ and avoid the most difficult parts of the plane.

Previous work has shown that known quasars have Gaia parallaxes and proper motions (PPM) that are statistically consistent with zero within their errors (e.g., Liao et al. Reference Liao2021; Onken et al. Reference Onken2022b; Souchay et al. Reference Souchay2022, but for interesting counter-examples, see Wu et al. Reference Wu2022) and hence we restrict the search to a target list with parallaxes and proper motions of low $({<}4\sigma$ ) significance. We also restrict the search to objects with a Gaia $B_{P}/R_{P}$ excess factor (phot_bp_rp_excess_factor; see Riello et al. Reference Riello2021) ${<}1.5$ , which rejects clearly extended or blended sources. Among the known broad-line quasars in the Milliquas catalogue having Gaia $B_{P}<17$ mag, $z>0.3$ , and $|b|>10^{\circ}$ , the selection rules above reject less than 4% of the quasars (43 out of 1227); some of the rejected objects have no PPM measurements at all, however, the vast majority of the objects are simply consistent with being drawn from the tails of a zero-PPM population.

We investigated several colour properties, and found that the mid-infrared $W1-W2$ colour provides a highly effective distinction between the known quasars and the bulk of the candidate sample, which are primarily distant (hence, small PPM) stars. In the left panel of Figure 1, we show the $W1-W2$ colour vs Gaia $B_{P}$ magnitude for the known quasars from Milliquas and the sample passing the Gaia criteria above. At $B_{P}<17$ mag, the quasar and non-quasar population appear clearly separated, while they start to blend into each other at fainter magnitudes. As the known quasars have been compiled from a variety of selection methods (X-ray, UV, optical, radio), the mid-infrared quasar colours should not be subject to any particular biases beyond the scatter arising from the photometric errors, and just reflect the typical spectral energy distribution (SED) associated with accretion onto a BH. Thus, we select quasar candidates using the simple rule of $W1-W2>0.2$ mag. While there is likely to be increasing contamination towards that $W1-W2$ boundary, the moderate number of candidates to follow-up allows us to pursue a strategy that emphasises completeness (and the threshold may be relaxed further in future expansions of the observing campaign). Based on the PPM statistics above, expect the completeness to be $\approx$ 96% for $|b|>10^{\circ}$ .

Figure 1. Left panel: WISE $W1-W2$ colour versus Gaia $B_{P}$ magnitude of objects with low parallax and proper motion (yellow); known quasars are shown in black or, if they violate our selection criterion, in grey. Centre panel: $W1-W2$ colour versus redshift for known quasars satisfying (black) or violating (grey) our selection criteria. Right panel: $W1-W2$ colour versus $B_{P}$ magnitude for objects with low PPM in yellow, the new AllBRICQS quasars in black, contaminating stars in cyan, unclassified spectra in blue, and unobserved candidates in red.

As shown in the middle panel of Figure 1, the quasars that approach our $W1-W2$ threshold at faint $B_{P}$ magnitudes are strongly biased towards high redshift, but some sources at $z\sim 4$ can still be found within our selected region.

We limit the present sample to have either $B_{P}<16.5$ or $R_{P}<16$ mag and find 290 candidates^{Footnote b} (see right panel of Figure 1). Approximately 500 broad-line quasars are known at $z>0.3$ within these magnitude limits. If $\sim$ 85% of our candidates were similar objects, then one third of bright quasars would be missing from current catalogues and be revealed by AllBRICQS.

In Figure 2 we characterise our candidate list further in relation to known quasars of similar brightness. We can see that our new candidates are more numerous at Southern declinations and especially at Southern Galactic latitudes. The reason is, of course, that the Sloan Digital Sky Survey (SDSS, York et al. Reference York2000; Richards et al. Reference Richards2002; Abdurro’uf & et al. 2022), which has revealed a huge sample of quasars, was focused on the Northern Galactic Cap.

Figure 2. Number counts of AllBRICQS candidates (dark grey) as a function of Gaia $B_{P}$ magnitude (left), declination (centre), and Galactic latitude (right). The blue histograms are known quasars for the same magnitude range as the candidates: Gaia $B_{P}<16.5$ or $R_{P}<16$ mag. Light grey are all known quasars.

3. Observations and data processing

Optical spectroscopy was obtained with the Australian National University (ANU) 2.3-m telescope at Siding Spring Observatory (SSO) using the Wide Field Spectrograph (WiFeS; Dopita et al. Reference Dopita2007, Reference Dopita2010). WiFeS is an integral field spectrograph and, with a spatial binning of 2 pixels, provides $1\times 1^{\prime\prime}$ sampling over a $25\times38^{\prime\prime}$ field-of-view.

WiFeS spectra were obtained between UT 2022 March 11 and 2022 November 24 for the AllBRICQS sample presented here. We note that observations on one of those nights (UT 2022 June 14) were conducted as part of the Science Verification activities for the fully robotic operations of the ANU 2.3 m telescope. The targets were selected from the candidate list based purely on considerations of observability (Right Ascension and airmass), aiming for complete coverage of the list (between RA=10 h and 5 h, only five candidates still needed observing).

With the resolving power $R\sim3000$ gratings and the RT560 beamsplitter, we used exposure times between 180 and 1500 s, covering the wavelength range 3250–9550 Å across the two cameras of the spectrograph. Various spectrophotometric standard stars were observed alongside the AllBRICQS candidates and were used for calibrating the overall spectral shape. However, because the standards were not necessarily observed under the same observing conditions, we do not utilise them for absolute flux calibration.

The raw data were processed with the Python-based pipeline, PyWiFeS (Childress et al. Reference Childress, Vogt, Nielsen and Sharp2014). We then extracted the spectra from the 3D data cubes (separate cubes for each arm of the spectrograph) using QFitsView,^{Footnote c} utilising nearby regions for sky subtraction. The signal-to-noise values in the final spectra were typically between 10 and 50 per pixel.

The spectra were classified and redshifted by eye, aided by the Marz online application^{Footnote d} (Hinton et al. Reference Hinton, Davis, Lidman, Glazebrook and Lewis2016; Hinton Reference Hinton2016). The typical redshift uncertainty is 0.01, but can be either better or worse depending on the details of the available emission lines and their shapes.

4. AllBRICQS sample

The observations reported here encompass 166 of the 290 AllBRICQS candidates. We present a list of the 156 confirmed AllBRICQS quasars in Appendix A, arranged in order of ascending RA. A gallery of the quasar spectra, arranged in order of ascending redshift, is provided in Appendix B. Four unclassified sources are presented in Appendix C. Finally, the six stars we observed are presented in Appendix D.

As noted in Appendix A, 140 of our 156 quasars represent new discoveries, while the remaining 16 are composed of quasars identified from the Edinburgh-Cape Blue Object Survey (13 quasars without published redshifts, and so intentionally retained in the candidate list; Stobie et al. Reference Stobie1997; Kilkenny et al. Reference Kilkenny2016); two quasars of known redshift, but lacking published optical spectroscopy; and one quasar announced since the beginning of the AllBRICQS observing campaign. In contrast, just six candidates have proven to be stars. Excluding the four quasars beyond our Gaia magnitude limits and the four unclassified sources, this gives a preliminary estimate of the AllBRICQS selection purity of 152/158 = 96%.

The right panel of Figure 1 suggests that the purity is declining at the blue end of the $W1-W2$ range, but we do find quasars near the boundary and will wait for the completed sample before making a more comprehensive statistical analysis.

4.1. Luminosities

We flux-calibrate the WiFeS spectra for the AllBRICQS quasars with the Gaia DR3 $B_{P}$ and $R_{P}$ photometry and then correct for Galactic extinction using the Fitzpatrick et al. (Reference Fitzpatrick, Massa, Gordon, Bohlin and Clayton2019) extinction curve implemented in the dust_extinction Python package (Gordon Reference Gordon2021). We assume $R_V=3.1$ , and apply a $\times0.86$ correction factor to the values drawn from the Schlegel, Finkbeiner, & Davis (Reference Schlegel, Finkbeiner and Davis1998) $E(B-V)$ map (Schlafly & Finkbeiner Reference Schlafly and Finkbeiner2011). We derive continuum luminosities from the observed redshifts and the median extinction-corrected emission in 20 Å windows centred around the rest-frame wavelengths of 1450, 3000, and 5100 Å (as the redshifts permit, and excluding the 1450 Å continuum for broad absorption line quasars). We also estimate the bolometric luminosity for each quasar by applying the bolometric corrections (BCs) from Runnoe, Brotherton, & Shang (Reference Runnoe, Brotherton and Shang2012b,Reference Runnoe, Brotherton and Shanga) and adopting the mean when multiple values are available. The continuum and bolometric luminosities are provided in Appendix E. Based on the typical RMS fluxes within the spectroscopic continuum windows, we expect the luminosity estimates to be reliable at the level of 0.1 dex, but plan to make more precise measurements when performing detailed spectral fitting in future work.

The bolometric luminosities across redshift are shown in comparison to the quasars from the 14th data release of SDSS (DR14Q; Rakshit, Stalin, & Kotilainen Reference Rakshit, Stalin and Kotilainen2020) in Figure 3. To adopt a consistent bolometric correction as above, we apply the Runnoe et al. (Reference Runnoe, Brotherton and Shang2012b,Reference Runnoe, Brotherton and Shanga) BCs to the tabulated DR14Q continuum luminosities and again take the mean value when multiple estimates are available. We also show in Figure 3 a number of bright quasars for comparison with the AllBRICQS sample: the long-studied 3C 273; the most luminous known quasar in the Universe, SMSS J215728.21-360215.1 (hereafter, J2157-3602; Wolf et al. Reference Wolf2018a; Onken et al. Reference Onken2020); and the bright quasar which inspired the AllBRICQS project, J1144-4308 (Onken et al. Reference Onken2022a). The AllBRICQS quasars fill a niche not well populated by the DR14Q sample, despite substantial overlap between the SDSS bright-end limit of $i_{\rm SDSS}=15$ ABmag and the AllBRICQS faint-end limit of $R_{P}=16$ mag ( $i_{\rm SDSS}\approx 16.35$ ABmag).

Figure 3. Bolometric luminosity versus redshift for the first AllBRICQS quasars (red circles), with the highest-redshift source (J0529-4351; see Section 5) indicated as a red star. The AllBRICQS discoveries that are fainter than $B_{P}=16.5$ and $R_{P}=16$ mag are indicated with open orange diamonds. For comparison, we also show 3C 273 (blue square); the recently discovered J1144-4308 (green star; Onken et al. Reference Onken2022a); the most luminous known quasar, J2157-3602 (magenta star; Wolf et al. Reference Wolf2018a; Onken et al. Reference Onken2020); and the numerous quasars observed by SDSS grey points; (grey points; Rakshit et al. Reference Rakshit, Stalin and Kotilainen2020). The AllBRICQS quasars improve our knowledge of the luminous end of the quasar distribution across a wide redshift range.

For the extended AllBRICQS sample (having Gaia magnitudes just fainter than our main sample’s criteria of $B_{P}<16.5$ mag or $R_{P}<16$ mag), we find one quasar, J1501-1053 at $z=0.72$ , with a luminosity that places it amongst the bulk of the AllBRICQS population ( $5.5\times10^{46}$ erg s $^{-1}$ ). This quasar is relatively blue ( $B_{P}-R_{P}$ =0.59 mag), yet is in the 74th percentile of reddening amongst our confirmed quasars, with an $E(B-V)_{\rm SFD}$ =0.12 mag. The extinction-corrected continuum luminosities at both 3000 and 5100 Å provide a consistent estimate of the bolometric luminosity, indicating that it was the foreground dust that caused the source to be marginally outside our selection criteria.

5. The case of J0529-4351

In this section, we focus on the properties of the $z=3.93$ quasar, J0529-4351. As indicated in Figure 3, the continuum flux at rest-frame 1450 Å suggests an intrinsic bolometric luminosity of $1.5\times10^{48}$ erg s $^{-1}$ , on par with the most luminous known quasar, J2157-3602 (Wolf et al. Reference Wolf2018a; Onken et al. Reference Onken2020). In the observed frame, aside from two gravitationally lensed systems (APM 08279+5255 and B 1422+231), J0529-4351 has the brightest Gaia $R_{P}$ magnitude of any quasar more distant than HS 1946+7658 at $z=3.051$ . Hence, we examine in detail the available imaging data to constrain the possibility of gravitational lensing boosting the observed flux.

As discussed in Section 4.2, the relative flux measured by Gaia through its narrow (G-band) and wide ( $B_{P}$ and $R_{P}$ ) apertures can be used as a measure of extended emission on sub-arcsecond spatial scales. For J0529-4351, the colour-corrected phot_bp_rp_excess_factor, $C^{*}$ , is found to be -0.037. With the 1 $\sigma$ scatter expected to be 0.02 at $G=16.34$ mag (Riello et al. Reference Riello2021), the Gaia data do not indicate any additional flux at radii larger than 0.175 $^{\prime\prime}$ from the quasar (half the 0.35 $^{\prime\prime}$ aperture of the G-band).

In addition, the Dark Energy Survey (DES) DR2 (Abbott et al. Reference Abbott2021) photometry for J0529-4351 is found to be consistent with a point source in all five optical/infrared bands (grizY): the SPREAD_MODEL and WAVG_SPREAD_MODEL are below 0.001 (where values below 0.003 have been found to robustly isolate stellar sources in griz imaging of similar depth; Desai et al. Reference Desai2012), and the CLASS_STAR estimates are ${>}0.98$ .

To assess possible microlensing of J0529-4351 from stars in a putative foreground galaxy, we examined the photometry from several surveys of the past decade. SMSS DR3 optical photometry^{Footnote i} indicates a dimming of $\sim$ $0.2$ mag between 2014 November and 2019 October in griz (the source is undetected in the u and v filters because of the Ly $\alpha$ absorption). Similarly, the photometry from the NEOWISE 2022 Data Release^{Footnote j} (Mainzer et al. 2014) in W1 and W2, obtained between 2014 March and 2021 September, indicates no more than 0.05 mag of dimming over that time span.

In terms of large-separation lensed images, the only other Gaia DR3 source in a 30 $^{\prime}$ search radius having similar colours, low PPM, and an $R_{P}$ within 2 mag of J0529-4351 is shown by DES imaging to be the centre of a foreground spiral galaxy.

We find that the existing data for J0529-4351 provides no evidence that the quasar is gravitationally lensed, and thus, we conclude that its extraordinary luminosity is likely to be an indication of an extremely high accretion rate onto its BH.

In terms of its multi-wavelength properties, we find no radio detections within 2 $^{\prime}$ in DR1 of the Rapid ASKAP Continuum Survey (RACS; McConnell et al. Reference McConnell2020; Hale et al. Reference Hale2021), and no X-ray counterparts catalogued within 25 $^{\prime}$ in the Second ROSAT all-sky X-ray Survey (2RXS; Boller et al. Reference Boller2016).

Given the unusual nature of J0529-4351, we have already begun to collect additional data to further investigate this remarkable quasar.

6. Comparison with $Gaia$ -selected quasars

We compare our confirmed quasars with the quasar catalogues derived from the Gaia variability analysis (Carnerero et al. Reference Carnerero2022), or from other Gaia source classification methods (Gaia Collaboration Reference Gaia Collaboration2022; Delchambre et al. Reference Delchambre2022), including those utilising the $B_{P}/R_{P}$ low-resolution spectra (De Angeli et al. Reference De Angeli2022; Montegriffo et al. Reference Montegriffo2022).

First, we consider the Gaia DR3 variabLE AgN sample (GLEAN; Carnerero et al. Reference Carnerero2022). The GLEAN coverage excludes the Galactic Plane and regions around the Magellanic Clouds because of its constraint on the number density of sources within 100 arcsec being less than 0.004 arcsec $^{-2}$ . This irregular exclusion zone covers $|b|\lesssim25^{\circ}$ at the Galactic Centre, but allows sparse sampling of the Plane in the direction of the Anti-centre. The GLEAN sample^{Footnote k} totals over 872000 sources, including more than 21000 potentially new quasars. The latter are predominantly at $G_{P}>20$ mag, significantly fainter than the AllBRICQS regime ( $G_{P}\lesssim17$ mag).

We indicate in Table A.1 whether each AllBRICQS quasar was included in the GLEAN sample, or in another Gaia DR3 variability table,^{Footnote l} or neither. The completeness of the GLEAN sample is estimated (cf. Figure 24 of Carnerero et al. Reference Carnerero2022) to be ${>}$ 80% for $G_{P}<17$ mag, with a purity of ${>}$ 95%. Having 123 of our 156 quasars selected by GLEAN, and one GLEAN-selected star compared to the 123 quasars, the first AllBRICQS sample is consistent with the Carnerero et al. (Reference Carnerero2022) estimates.

We further compare the AllBRICQS quasars to the classifications produced by Gaia’s Discrete Source Classifier (DSC; Gaia Collaboration Reference Gaia Collaboration2022; Delchambre et al. Reference Delchambre2022), a probabilistic classification algorithm that was trained on 300000 SDSS quasars. The DSC assigned a quasar label (via the Combmod classifier, recorded in the classlabel_dsc parameter) to 116 of our 156 quasars, or 74% completeness within the present sample. This appears to be significantly lower than the expected^{Footnote m} quasar completeness for $G_{P}<17$ mag of nearly 100%. We find that 37 of the AllBRICQS quasars were labelled as stars (including one as a ‘physicalbinary’), as was just 1 of the 6 stars we observed. Of particular note, J0529-4351, the luminous quasar at $z=3.93$ , was labelled as a star by the DSC with 99.98% probability.

In addition to the 116 quasars identified by the DSC, another 10 were flagged as quasars by the Outlier Analysis (OA) module, which uses self-organising maps (Kohonen Reference Kohonen1982) to label sources with low DSC classification probability.

The challenges inherent in classifying quasars from Gaia’s low-resolution $B_{P}/R_{P}$ spectroscopy are evident when comparing against our $R\sim3000$ spectra from WiFeS (Figure 4). The blending of nearby emission lines, which can exhibit an intrinsic dispersion in relative fluxes, shifts the peak of the line emission, and the ‘ringing’ in the spectra reconstructed from the DR3 basis functions, both at the blue end and in regions around strong emission lines, often makes an assessment of the true underlying spectrum difficult. In terms of further analysis of the spectra, studies of absorption features (both broad and narrow) and emission line widths (e.g., for BH mass estimation) are only possible with higher resolving power than provided by the $B_{P}/R_{P}$ spectra.

Figure 4. Flux versus wavelength for the $R\sim3000$ spectrum of AllBRICQS (black line) and the Gaia low-resolution $B_{P}/R_{P}$ spectral reconstruction (blue points with errorbars) for four example quasars. Top labels indicate the AllBRICQS redshift as well as the Gaia classifications (contained in GLEAN or other variability samples, and/or a DSC-labelled quasar). Vertical lines indicate the positions of various quasar emissions lines: H $\alpha$ (red, dashed), H $\beta$ (orange, dot-dashed), Mg ii (green, dotted), C iii] (blue, solid), C iv (purple, dashed). The thin, black vertical line at 5575 Å indicates where the blue and red arms of the WiFeS spectrograph are spliced together. The Gaia spectra broaden and blend spectral features, which complicates the efforts to classify the sources and determine redshifts, let alone any more detailed analysis.

7. Discussion

The sources discovered in AllBRICQS are those which have eluded detection in the first 50+ yr of quasar searches, but many had already come under suspicion from other selection methods. In Section 6, we described the high degree of completeness for the Gaia quasar classification, which is remarkable given their exclusive reliance on Gaia’s optical dataset (astrometric, photometric, and low-resolution spectroscopic). Yet the existence of AllBRICQS quasars that escaped the Gaia criteria confirms the value of multi-wavelength approaches.

In addition to the Gaia variability and spectroscopic classifications, Table A.1 indicates the objects which were flagged as Primary or Secondary quasar candidates from the Ultraviolet Quasar Survey (UVQS; Monroe et al. Reference Monroe2016), which combined photometry from the Galaxy Evolution Explorer (GALEX; Martin et al. Reference Martin2005) and WISE satellites. Apart from Galactic extinction, these UV/optical probes should provide the most complete samples of unobscured quasars at low to moderate redshift.

At higher energies, we anticipate the majority of the real quasars amongst the AllBRICQS candidates to be detected by SRG/eROSITA (the Spectrum-Roentgen-Gamma satellite’s extended ROentgen Survey with an Imaging Telescope Array; Predehl et al. Reference Predehl2021). In addition, a small number of AllBRICQS quasars are also known to be associated with quasar-like radio emission, but did not have a spectroscopically confirmed redshift.

Outliers from the AllBRICQS selection criteria (in either Gaia astrometry or WISE colours) could still be identified at other wavelengths, and many of those bright quasars may be observed as part of the Black Hole Mapper^{Footnote n} (BHM) within SDSS-V (Kollmeier et al. Reference Kollmeier2017). Moreover, the BHM programme will greatly expand the samples at fainter optical magnitudes, particularly as SDSS extends its optical spectroscopy footprint to the Southern hemisphere.

Early large-area surveys for blue objects were limited to high Galactic latitude, with the Calán-Tololo Survey (Maza et al. Reference Maza, Ruiz, Gonzalez, Wischnjewski, Blanco and Phillips1988; Maza,Wischnjewsky, & Antezana Reference Maza, Wischnjewsky and Antezana1996) and Hamburg Quasar Survey (Hagen et al. Reference Hagen, Groote, Engels and Reimers1995; Hagen, Engels, & Reimers Reference Hagen, Engels and Reimers1999) extending closest to the Galactic Plane ( $|b|>20^{\circ}$ ) in the Southern and Northern hemispheres, respectively. Even DR1 of the UVQS, which focused on FUV-detected sources from GALEX, was incomplete in its coverage near the Plane because of the failure of the FUV detector prior to the relaxing of the satellite’s initial safety constraints on overall count rates (see Bianchi Reference Bianchi2014).

AllBRICQS is covering the sky down to $|b|>10^{\circ}$ , but is still constrained from fully exploring behind the Galactic Plane because of source confusion arising from the limited spatial resolution of WISE ( $\sim$ 6 arcsec in W1 and W2). Dedicated quasar searches within the Galactic Plane require alternative selection criteria to mitigate the effects of dust extinction, but have begun yielding significant samples (Im et al. Reference Im2007; Fu et al. Reference Fu2021, Reference Fu2022). Beyond photometric searches, additional low-latitude quasars may be uncovered thanks to the near-IR resolving power of the forthcoming SPHEREx satellite’s all-sky spectrophotometric survey^{Footnote o} (Crill et al. Reference Crill2020).

AllBRICQS will complete observations of the target sample at declination $\delta<+20^\circ$ with the ANU 2.3 m telescope at SSO. The intention for the Northern targets is to collect spectra at the Bohyunsan Optical Astronomy Observatory (BOAO) 1.8-m telescope and the Seoul National University Astronomical Observatory (SAO) 1.0-m telescope in South Korea, and the Yunnan Observatories (YNAO) Lijiang 2.4-m telescope at the Gaomeigu site near Lijiang, China. These observations will confirm classifications and determine redshifts, as well as enabling virial estimates of BH masses (see Cackett, Bentz, & Kara Reference Cackett, Bentz and Kara2021, and references therein). They will also reveal unusual optical spectral properties and foreground absorbers, which may flag specific targets for detailed follow-up at other facilities.

In particular, the two bright quasars at $z>2.5$ —J0431-0838 at $z=2.53$ with SMSS DR3 $i=16.42$ ABmag, and J0529-4351 at $z=3.93$ with $i=16.07$ ABmag—may be appealing targets for the Sandage Test (Sandage Reference Sandage1962). With high-stability wavelength calibration and extremely large telescopes, it should soon be possible to directly detect the expansion of the Universe through the wavelength drift of intervening absorbers over time baselines of decades (Liske et al. Reference Liske2008). These two AllBRICQS quasars, and subsequent discoveries at similar redshifts, would supplement the samples recently compiled by QUBRICS (QUasars as BRIght beacons for Cosmology in the Southern Hemisphere; Calderone et al. Reference Calderone2019; Boutsia et al. Reference Boutsia2020) and ELQS (Extremely Luminous Quasar Survey; Schindler et al. Reference Schindler2017, Reference Schindler2019).

Finally, we note that a few AllBRICQS quasars were catalogued as AGNs by the Edinburgh-Cape (EC) Blue Object Survey, but because of the EC Survey’s focus on hot, evolved stars in the Milky Way, the quasar spectra were not presented and no redshifts were recorded. We expect that many of the AllBRICQS candidates have been observed by groups looking for objects other than quasars, who seemingly had little incentive to publish those spectra—a situation which nearly held true for the case of J1144-4308 (Onken et al. Reference Onken2022a). Yet even if AllBRICQS presents spectra of those objects in future papers, the historical datasets could hold enormous value for studies of variability properties and searches for changing-look AGNs (e.g., LaMassa et al. Reference LaMassa2015), and we encourage readers to dust off their old datasets and publish their quasar spectra.