EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 669 (January 2023) A&A, 669 (2023) A134 Full HTML
Open Access
Issue
A&A
Volume 669, January 2023
Article Number A134
Number of page(s) 10
Section Extragalactic astronomy
DOI https://doi.org/10.1051/0004-6361/202243855
Published online 24 January 2023

© The Authors 2023

Licence Creative CommonsOpen Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

This article is published in open access under the Subscribe-to-Open model. Subscribe to A&A to support open access publication.

1. Introduction

Radio-loud (RL) active galactic nuclei (AGN) are those supermassive black holes (SMBHs) that are able to expel part of the accreting matter into two relativistic bipolar jets (e.g., see Blandford et al. 2019 for a recent review). They are therefore usually referred to as jetted AGN (e.g., Padovani et al. 2017) and represent up to 10% of the total AGN population (e.g., Liu et al. 2021). Understanding the mechanisms responsible for the launch and the emission of these jets is of crucial importance for studying their role in SMBH accretion and evolution (e.g., Volonteri et al. 2015), and for investigating their feedback on the intergalactic medium (e.g., Fabian 2012).

High-redshift RL quasars (QSOs) are indispensable tools for studying the early evolutionary stage of the first jetted SMBHs, their feedback on the host galaxy and the environment, and their contribution to the re-ionization epoch (e.g., Blandford et al. 2019). Among the more than 500 QSOs discovered to date at z > 5, approximately 30 are classified as RL (e.g., Romani et al. 2004; McGreer et al. 2006; Zeimann et al. 2011; Sbarrato et al. 2012; Bañados et al. 2018), that is, with a radio loudness R > 10, with R defined as the ratio of the 5 GHz and 4400 Å rest-frame flux densities: R = S5 GHz/S4400 Å (Kellermann et al. 1989). Therefore, a systematic search for these objects and their subsequent study is necessary to better constrain the properties of jetted SMBHs in the first gigayears following the Big Bang.

In an effort to enlarge the current sample of high-z RL QSOs, we are conducting a project that combines optical, infrared (IR), and radio datasets to identify distant radio sources all over the sky (Caccianiga et al. 2019; Belladitta et al. 2019, 2020; Ighina et al. 2023). In this paper, we present the discovery and first observations of PSO J191.05696+86.43172 (hereafter PSO J191+86), a powerful jetted QSO at z  =  5.32, which was selected from the cross-correlation of the NRAO VLA Sky Survey (NVSS, Condon et al. 1998) in the radio, the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS PS1, Chambers et al. 2016) in the optical, and the AllWISE Source Catalog (Wright et al. 2010; Mainzer et al. 2011) in the mid-infrared (MIR).

The paper is organized as follows: in Sect. 2 we outline our selection method; in Sect. 3 we present new optical and near-infrared (NIR) spectroscopic observations of PSO J191+86; in Sects. 4 and 5 we report archival radio data and a new X-ray follow-up observation, respectively; in Sects. 6 and 7 we describe our results on the multi-wavelength properties of the source; and finally, in Sect. 8 we provide a brief discussion and conclusions.

The magnitudes used in this work are all in the AB system unless otherwise specified. We use a flat Λ cold dark matter (ΛCDM) cosmology with H0 = 70 km s−1 Mpc−1, Ωm = 0.3, and ΩΛ = 0.7. Spectral indices are given assuming Sν ∝ ν−α and all errors are reported at 1σ, unless otherwise specified. Throughout the paper, the flux densities are the observed ones, while luminosities are given in the rest-frame of the source unless otherwise specified.

2. Source selection

From the entire NVSS catalog, we selected bright (S1.4 GHz ≥ 30 mJy) and compact objects to provide an accurate (< 2″) radio position. With this criteria we found approximately 45 000 sources. We then cross-matched these with the Pan-STARRS PS1 catalog using a maximum separation equal to 2″. This impact parameter guarantees the recovery of more than 90% of the real optical counterparts (Condon et al. 1998). We selected only relatively bright optical sources (iPS1 < 21.5) outside the Galactic plane (|b|≥20°) in order to minimize contamination from stars, and at Dec > −25° to exclude optical objects at the declination limit of the Pan-STARRS survey. All the sources that satisfied the following photometric criteria were then selected: (i) no detection in gPS1-band; (ii) drop-out: rPS1 − iPS1 ≥ 1.2; (iii) blue continuum: iPS1 − zPS1 ≤ 0.5; (iv) point-like sources: iPS1 − iKron < 0.05; and (v) no detection in WISE (W2) or iPS1 – W2(Vega) < 5. This last constraint has been placed to minimize the contamination by dust-reddened AGN at z = 1 − 2 (e.g., Carnall et al. 2015; Caccianiga et al. 2019).

Following the application of these filters, 14 candidates remained; 4 of them are known radio QSOs in the literature. PSO J191+86 stands out among the other 10 targets for its very high drop-out value (r − i > 1.7), its photometric redshift (z > 5), and its very high radio flux density (S1.4 GHz > 70 mJy). We therefore considered only this source for spectroscopic follow up. Table 1 reports the Pan-STARRS PS1 and WISE magnitudes of PSO J191+86 (corrected for Galactic extinction using the extinction law provided by Fitzpatrick (1999), with RV = 3.1). Figure 1 shows the optical images of the source in the different g, r, i, z, y PS1 bands. The optical coordinates of PSO J191+86 are: RA = 191.05696 deg (12h44m13.902s), Dec = +86.43172 deg (+86d25′54.07″).

thumbnail Fig. 1.

0.2′×0.2′ Pan-STARRS PS1 g, r, i, z, y cutout images of PSO J191+86. Its optical position is marked with a red circle of 1.5″ of diameter. The radio NVSS position is marked with a blue dashed circle, as large as the radio positional error reported in the catalog (1.7″). All images are oriented with north up and east to the left.

Table 1.

Optical and MIR magnitudes of PSO J191+86.

3. Optical and NIR observations, and data reduction

3.1. TNG/DOLORES observation

We performed a dedicated spectroscopic follow-up of PSO J191+86 with DOLORES (Device Optimized for the LOw RESolution) installed at the Telescopio Nazionale Galileo (TNG). We confirmed PSO J191+86 as a high-z RL QSO on the night of 21 June 2018, with a single 30min observation with the LR − R grism and a long-slit of 1″ width. The mean air mass during the observation was 1.7. Table 2 reports the details of this observation.

Table 2.

Summary of the optical and NIR follow-up spectroscopic observations of PSO J191+86.

An exposure of an Ar+Ne+Hg+Kr lamp was carried out to ensure the wavelength calibration, and the flux calibration was obtained by observing the G191-B2B (RA = 05h05m30.62s, Dec = +52d49′54.0″) spectro-photometric standard star of the catalogs of Oke (1990).

Data reduction was performed using standard Image Reduction and Analysis Facility (IRAF) procedures (Tody 1993). The DOLORES discovery spectrum is shown in Fig. 2; it has been corrected for Galactic extinction as explained in Sect. 2.

thumbnail Fig. 2.

Optical and NIR de-reddened observed spectra of PSO J191+86 taken at TNG and LBT, respectively. The most important visible emission lines are marked. We masked the part of the MgII line that suffers from a strong absorption feature, in which the peak of the MgII line falls (shown here in gray). The top x-axis reports the rest-frame wavelengths while the right axis shows the monochromatic luminosity.

3.2. LBT/LUCI follow-up

We performed a spectroscopic follow-up with the Large Binocular Telescope (LBT) utility camera in the infrared (LUCI, Seifert et al. 2003) at the LBT in order to extend the wavelength range in the NIR band and detect the CIVλ1549 (hereafter CIV) and the MgIIλ2798 (hereafter MgII) broad emission lines (BELs), which can be used to estimate the central black hole mass of PSO J191+86 thanks to the so-called single epoch (SE) or virial method (e.g., Vestergaard & Peterson 2006, hereafter VP06, see Sect. 6.1). The observation was carried out on the night of 3 May 2019 (P.I. Moretti A., program ID: LBT2018AC123500-1) and consisted of 12 exposures of 270 s each in nodding mode in the sequence ABBA, with a total integration time of 1.8 h. The medium seeing along the night was 0.9″ and the mean air mass was 1.7. The details of this observation are reported in Table 2. We decided to use the grism 200 with the zJ and HK filters on LUCI1 and LUCI2, respectively, in order to cover the whole spectral range and detect the CIV (LUCI1) and the MgII (LUCI2) simultaneously. The G200-zJ configuration allowed us to observe the wavelength range from 0.9 to 1.2 μm, where the CIV line is expected (λobs = 9805 Å at z = 5.3); instead the G200-HK configuration covers the range from 1.5 to 2.4 μm in which the MgII line falls (expected λobs = 17 700 Å). Data reduction was performed at the Italian LBT Spectroscopic Reduction Center with the software developed for LBT spectroscopic data reduction (Gargiulo et al. 2022). Each spectral image was independently dark subtracted and flat-field corrected. Sky subtraction was done on 2D extracted, wavelength-calibrated spectra. Wavelength calibration was obtained by using several sky lines, reaching an rms of 0.25 Å on LUCI1 and 0.5 Å on LUCI2.

Figure 2 shows the LBT/LUCI1 and the LBT/LUCI2 spectra in which the CIV and the MgII BELs are detected, together with the CIII]λ1909+AlIIIλ1860+SiIII]λ1892 complex. Also, in this case, the two spectra have been corrected for Galactic extinction as in the TNG/DOLORES spectrum. We note that the MgII line suffers from the presence of an absorption feature (a residual of background subtraction; see gray line in Fig. 2 and the zoom in Fig. 6). When masking the absorption feature, the wide range of absorption results in a gap close to the line center.

4. Archival continuum radio data

In addition to the NVSS observation at 1.4 GHz (S1.4 GHz = 74.2±2.3 mJy, see also Fig. 3), PSO J191+86 has an archival detection in the Westerbork Northern Sky Survey (WENSS, Rengelink et al. 1997, see Fig. 3) at 325 MHz of 19.0±3.3 mJy. Due to the availability of these two flux densities, Massaro et al. (2014) included PSO J191+86 in the LOw frequency Radio CATalog of flat spectrum sources (LORCAT). Moreover the source was observed by Healey et al. (2009) at 4.85 GHz with the Effelsberg 100 m telescope. These authors measured a flux density of 33.7±1.3 mJy. The detections with WENSS, NVSS, and Effelsberg enabled Healey et al. (2009) to classify PSO J191+86 as a Gigahertz-Peaked Spectrum (GPS) source, meaning a young (< 103 − 4 yr) and compact (< 1 kpc) radio source. These objects are usually considered to be the early stages of evolution of powerful large-scale radio galaxies of the local Universe (see O’Dea & Saikia 2021 for a recent review).

thumbnail Fig. 3.

3′×3′ cutout of the iPS1 image around PSO J191+86 overlaid with the radio contours from NVSS (1.4 GHz, cyan), WENSS (325 MHz, blue), and VLASS (3 GHz, yellow). In all cases, contours are spaced by starting from three times the survey rms (NVSS = 0.42 mJy beam−1; VLASS = 160 μJy beam−1; WENSS = 2.7 mJy beam−1). A zoom onto the VLASS emission is shown in Fig. 4. The red cross indicates the optical position of the source.

PSO J191+86 is also clearly detected at 3 GHz in the Very Large Array Sky Survey (VLASS, Lacy et al. 2020, see Figs. 3 and 4). The source was observed during both the first campaign of the first epoch (VLASS 1.1) in 2017 and the first campaign of the second epoch (VLASS 2.1) in 2020. As the data of the 1.1 epoch suffer from phase errors, that is, artifacts that alter the true size and morphology of a source, we carried out the analysis on only the 2.1 image. We performed a single Gaussian fit using the task IMFIT of the Common Astronomy Software Applications package (CASA, McMullin et al. 2007) to quantify the flux density and the size of PSO J191+86 (see Fig. 4). The measurements of total and peak flux density and the size obtained from the best fit are listed in Table 3. The position of the source estimated by the fit is: RA = 12h44m13.57949s ± 0.01239s, Dec = +86d25′54.04861″ ± 0.00021s, which is at 0.3″ from the optical PS1 position, confirming the radio–optical association of PSO J191+86. By comparing the dimensions of the source – as estimated by the single Gaussian fit – with the beam size (major axis = 4.372″, minor axis = 2.241″, PA = 80.75 deg, east of north), we concluded that the source is partially resolved.

thumbnail Fig. 4.

VLASS 2.1 image of PSO J191+86. The contours are drawn at −3, −2, 2, 3, 6, 9, 18, 36, 72, and 144 times the off-source rms (160 μJy). In the bottom left corner, the beam size (4.372″ × 2.241″) is shown. North is up, east is left.

Table 3.

Properties of the quick-look VLASS 2.1 image of PSO J191+86.

Finally, PSO J191+86 is not detected in the TIFR GMRT Sky Survey (TGSS, Intema et al. 2017) at 150 MHz. From the TGSS image, we computed only an upper limit (at 2σ) of ∼4 mJy.

In Table 4, all the available radio flux densities of PSO J191+86 are reported. The VLASS integrated flux density has been corrected for 3% systematic uncertainty1.

Table 4.

Summary of the archival radio observations of PSO J191+86.

5. Swift-XRT follow up

PSO J191+86 was observed in X-rays by the Swift-XRT telescope (target ID: 3110833; P.I. Belladitta S.). Observations were carried out between September, October, and November 2020 and consisted of 44 segments for a total exposure time of 47.81 ks. Data have been reduced through the standard data-analysis pipeline (Evans et al. 2009), running on the UK Swift Science Data Centre web page2 using HEASOFT v6.26.1. The source is clearly detected with a total of 55 counts and with an expected background of 7 counts in the [0.5–10] keV energy band. The standard (PSF-fitted) Swift-XRT position of the source calculated by the detected and centroid algorithm is RA = 12h44m12.97s, Dec = +86d25′57″, with an uncertainty of 3.5″ (90% confidence). This is at 3.0″ from the optical PS1 position. A standard spectral analysis was performed using XSPEC (v.12.10.1) by fitting the observed spectrum (Fig. 5) with a single power law with the absorption factor fixed to the Galactic value (6.46×1020 cm−2) as measured by the HI Galaxy map of Kalberla et al. (2005). We measured a photon index (ΓX) of 1.32 ± 0.2, which implies an X-ray spectral index (αX = ΓX − 1) of 0.32, and a flux of 8.11 erg s−1 cm−2 in the observed [0.5–10] keV energy band.

thumbnail Fig. 5.

Swift-XRT observed spectrum of PSO J191+86 modeled with a single power law with only Galactic absorption (solid red line).

6. Analysis of MgII and CIV broad emission lines

Among all the emission lines detected in the TNG and LBT spectra, we focused on the CIV and MgII BELs; the latter allowed us to measure the redshift of the source and together with the CIV provides an estimation of the mass of the black hole hosted by PSO J191+86. To derive the properties of the two BELs (e.g., redshift, line width, line luminosity) we followed an approach used in several studies in the literature that is based on the analysis of high-z QSO spectra (e.g., Mazzucchelli et al. 2017; Schindler et al. 2020; Bañados et al. 2021; Vito et al. 2022; Farina et al. 2022).

First, we subtracted the continuum emission – which is described by a power law (fpl ∝ λ/2500 ), an iron pseudo-continuum template, and a Balmer pseudo-continuum – from the spectra. We modeled the Fe II contribution with the empirical template of Vestergaard & Wilkes (2001), which is used in the derivation of the scaling relation that we later consider for estimating the black hole mass of the QSO (see Sect. 6.1). To be consistent with studies in the literature (e.g., Vito et al. 2022 and reference therein), we used an iterative process to convolve the iron pseudo-continuum model with a Gaussian function of equal width to that of the MgII emission line, as it is assumed that FeII emission arises from a region close to that responsible for the MgII emission. To perform the continuum fit, we chose a region of the quasar continuum free of broad emission lines and of strong spikes from residual atmospheric emission: [10 520–11 110] Å in the LUCI1 spectrum and [15 979–17 200] Å in the LUCI2 spectrum (see Fig. 6). We then subtracted the entire pseudo-continuum model from the observed spectra, and modeled the two BELs with Gaussian functions.

thumbnail Fig. 6.

Zoom into the CIV and MgII line fit and into the Lyα+NV region. Left and central panel: total spectral fit (red line), and the different components, i.e., power law + Balmer pseudo-continuum (blue line), Fe II template (orange line, from Vestergaard & Wilkes 2001), and emission lines (purple). For the MgII, we represent the two lines of the doublet (solid Gaussians and dashed Gaussians, respectively). Spectral regions used for the continuum fits are shown as horizontal light blue shaded areas. In the right panel, the absorption feature in the middle of the MgII line is masked (gray dotted line). Right panel: Lyα and NV spectral region. The blue vertical lines represent the positions of the two BELs based on the MgII line redshift. The cyan shaded region is the uncertainty on this redshift estimate. The top x-axis reports the rest-frame wavelengths while the right axis shows the monochromatic luminosity.

BELs are usually well described by a multiple-Gaussian profile (e.g., Marziani et al. 2010; Shen et al. 2011, 2019; Tang et al. 2012; Karouzos et al. 2015; Rakshit et al. 2020). In particular, we considered a model where each line is described by a broad plus a narrow component to account for a possible contribution from the narrow line region. Each broad line is modeled with 1 or 2 Gaussians, while the narrow component is modeled with a Gaussian that has a FWHM of lower than 1000 km s−1 and higher than the spectral resolution (FWHM > ∼200 km s−1). In the case of MgII, we also considered that the line is a doublet (λ2796/2803) with an intensity ratio set equal to 1:1 (e.g., Marziani et al. 2013). For the MgII, we found that the narrow component is not statistically required and has no impact on the width of the broad component. The broad component of each line of the doublet is modeled with two Gaussian functions (i.e., four Gaussians in total for describing the entire line profile; see Fig. 6). Similarly, for the CIV we did not find clear evidence of a narrow component. This is in agreement with several works in the literature, which report that the existence of a strong narrow component for the CIV line is controversial (e.g., Wills et al. 1993; Corbin & Boroson 1996; Vestergaard 2002; Shen & Liu 2012). Instead, the broad component is well fitted with a single Gaussian (Fig. 6). On the right side of the CIV, we also fitted with a single Gaussian profile the Heλ1640 emission line (see Fig. 6).

The uncertainties on broad emission line properties were evaluated through a Monte Carlo method (e.g., Raiteri et al. 2020; Zuo et al. 2020; Diana et al. 2022). Each wavelength of the best-fit model was randomly perturbed 1000 times according to a Gaussian distribution of the mean rms of the spectra computed underneath the emission lines on the pseudo-continuum-subtracted spectrum. In this way, we obtained 1000 different mock spectra of the line profiles, from which we measured the line properties with the same procedure as that used on the real data. We computed the distributions of all the line properties for these 1000 simulated spectra, and the interval that contains 68% of the data in these distributions was taken as the statistical uncertainty on the best-fit values.

From the multi-Gaussian modeling, we measured the following line parameters: redshift, line width (parameterized as the FWHM), rest-frame equivalent width (REW), line flux, and luminosity (see Table 5). As the systemic redshift of PSO J191+86, we adopted the one derived from the MgII line, which is usually taken as the best redshift estimator for high-z objects when submillimeter and millimeter data are not available (e.g., De Rosa et al. 2014; Mazzucchelli et al. 2017; Schindler et al. 2020). We note that, despite the absorption feature in the middle, the redshift estimated from the MgII line is consistent with the expected positions of the Lyα and NV lines (see right panel of Fig. 6).

Table 5.

Properties of CIV and MgII BELs.

6.1. Estimates of the black hole mass

The most common method used to compute the mass of the central BH of Type I AGN is the SE method (e.g., Mazzucchelli et al. 2017; Shen et al. 2011, 2019; Diana et al. 2022). The underlying assumption of this technique is that the dynamics of the gas clouds is dominated by the central black hole gravitational potential. CIV and MgII BELs are the lines most frequently used to compute the mass of the central SMBH hosted by high-z QSOs. However, several works have questioned the reliability of CIV as a good virial mass indicator (e.g., Sulentic et al. 2007; Trakhtenbrot & Netzer 2012; Bisogni et al. 2017; Marziani et al. 2019) due to its observed blueward asymmetry and the velocity shifts of the line profile with respect to low-ionization lines, which are independent of the source orientation (e.g., Gaskell 1982; Coatman et al. 2017; Runnoe et al. 2014; Zuo et al. 2020). These characteristics suggest that the CIV clouds are affected by nongravitational effects, such as outflows, which have a significant effect on the observed emission velocity profile. The so-called weak emission line quasar (WELQ, Diamond-Stanic et al. 2009, REW < 10 Å) population exhibits the largest blueshift (> 3000 km s−1, see e.g., Vietri et al. 2018). With a REW of ∼150 Å, it is clear that PSO J191+86 does not belong to this QSO population, and therefore we do not expect to find a high value of blueshift for our source. Moreover, several works in the literature (e.g., Marziani et al. 1996; Sulentic et al. 2007; Richards et al. 2011) have claimed that RL sources usually show a lower value of blueshfit with respect to radio-quiet (RQ, or non-jetted) objects.

Other authors, have instead demonstrated that there is a consistency between the SE MBH computed from CIV and Balmer lines (e.g., VP06; Greene et al. 2010; Assef et al. 2011; Dalla Bontà et al. 2020). Finally, Shen et al. (2019) report that CIV can still be used because on average it provides black hole masses that are with those obtained from low-ionization lines, albeit with a large intrinsic scatter. Therefore, we decided to compute the black hole mass using the CIV, even if we considered our best estimate of mass to be those based on MgII.

For the MgII, we used the SE scaling relation presented by Vestergaard & Osmer (2009), for a direct comparison with other estimates in the literature:

(1)

where λLλ(3000 Å) is the monochromatic luminosity at 3000 Å derived from the power-law model3: λLλ (3000 Å) = 6.57±0.62×1046 erg s−1. We obtained a black hole mass of 1.67. With respect to the uncertainty reported in Table 5, here the error on MBH already takes into account the intrinsic scatter of the scaling relation (0.55 dex), which is the dominant uncertainty of the black hole mass estimate. Consistent black hole mass estimates are obtained using different scaling relations reported in the literature, both based on the continuum luminosity (e.g., McLure & Dunlop 2004; Shen & Liu 2012) and on the MgII line luminosity (e.g., Shen & Liu 2012).

For the CIV, we used the scaling relation of VP06, which is the most frequently used in the literature:

(2)

We estimated the continuum luminosity (λLλ) at 1350 Å directly from the TNG rest frame spectrum: 6.78±0.97×1046 erg s−1. Before applying this scaling relation, we corrected the FWHM (CIV) value for blueshift effect by following the prescription of Coatman et al. (2017):

(3)

where α = 0.41 ± 0.02, β = 0.62 ± 0.04 and ΔV is the line blueshift defined as

(4)

where c is the speed of light, 1549.48 Å is the rest frame wavelength for the CIV, and λhalf is the line centroid4. We found a ΔV of 741 km s−1, which is small, as expected, and allowed us to infer that the virial black hole mass of PSO J191+86 based on CIV line should not be strongly affected by blueshift effects. A similar value of ΔV is found using λpeak (i.e., the peak of the CIV line obtained by the Gaussian model in Fig. 6) with respect to λhalf: 759±522 km s−1.

The corrected FWHM (C IV) is 4072 km s−1 and therefore the MBH is equal to 2.40. The reported error already takes into consideration the intrinsic scatter of the used scaling relation (0.36 dex; VP06). By taking into account only the statistical uncertainty (see Table 5), the black hole mass derived from CIV is consistent within 1σ with that estimated from the MgII line.

6.2. Bolometric luminosity and Eddington ratio

The value of MBH allowed us to derived the Eddington ratio for the source, which quantifies the speed with which the black hole is accreting with respect to the Eddington limit: , where LEdd is the Eddington luminosity, the maximum luminosity beyond which radiation pressure will overcome gravity5, and Lbol is the bolometric luminosity, which is the total energy produced by the AGN per unit of time integrated over all wavelengths. To estimate Lbol, we used the continuum luminosity at 3000 Å computed in the previous subsection and the following bolometric correction: Lbol = K × L3000 Å, where K = 5.15 ± 1.26 (Shen et al. 2008). We obtain Lbol = 3.38 ± 1.14 × 1047 erg s−1. The corresponding value of λEdd is: = 1.55. The uncertainty in parenthesis takes into account both the statistical error on the virial mass and the intrinsic scatter of the SE relation.

The SE MBH and λEdd of PSO J191+86 are similar to those derived for RL and RQ QSOs discovered in the same range of redshift (z = 4.5 − 5.5; e.g., Shen et al. 2011; Yi et al. 2014; Trakhtenbrot et al. 2021; Diana et al. 2022). This similarity in terms of mass and Eddington ratio could be a consequence of a selection bias, as all these high-z sources have been selected from similar optical/IR surveys.

7. Analysis of the radio and X-ray properties

7.1. Radio spectrum

From the radio flux densities listed in Table 4, we computed the radio spectral index of PSO J191+86. We find that the radio spectrum shows a peak around ∼1 GHz (observed frame, Fig. 7, ∼6.3 GHz in the rest frame of the source). By assuming that the 1.4 GHz detection glimpses the turnover, we estimated the radio spectral indices below and above this potential peak and assuming a single power-law for the continuum emission (Sν ∝ ν−α). The spectral index between 325 MHz and 1.4 GHz () is −0.93±0.28 and (the spectral index between 1.4 and 4.85 GHz) is 0.65±0.12. Therefore, PSO J191+86 can be classified as a GPS source according to Healey et al. (2009).

thumbnail Fig. 7.

Radio flux densities as a function of the observed (bottom x-axis) and rest-frame (top x-axis) frequency of PSO J191+86 from 0.150 to 4.85 GHz. The spectrum shows a peak around ∼1 GHz, and therefore the source can be classified as a GPS. The corresponding indices of the low- and high-frequency parts of the spectrum are reported together with the reference surveys. The red dashed line represents the possible spectral index according to the TGSS upper limit.

As the radio data in hand are not simultaneous (spanning over ∼25 years), variability may be affecting the observed spectrum, making it appear flat (e.g., Dallacasa et al. 2000; Orienti & Dallacasa 2020). To date, we have no information about possible flux density variability of the source. A nearly simultaneous sampling of the radio spectrum (in particular below the possible turnover) is necessary.

7.2. Radio loudness

From the observed radio and optical flux densities we computed the radio loudness (R) of PSO J191+86, which quantifies the level of power of the nonthermal synchrotron radio emission with respect to that of the thermal emission originating from the accretion disk. It is defined as the ratio between the rest-frame radio (5 GHz) and optical (blue band B at 4400 Å) fluxes (Kellermann et al. 1989): . We estimated the flux density at 5 GHz by extrapolating the 1.4 GHz value adopting the spectral index of the optically thick part of the spectrum (). We highlight that 5 GHz in the rest-frame corresponds to 0.789 GHz in the observed frame. The value of the flux density at 4400 Å rest frame was derived from the LUCI2 rest-frame spectrum and assuming the optical spectral index of Vanden Berk et al. (2001, αν = 0.44). We obtained R = 337 ± 10 (Log(R) = 2.52). This value is in agreement with that of other peaked radio sources at z ≥ 4.5, but also with the R of the high-z blazars (e.g., Belladitta et al. 2019), i.e., RL AGN with the relativistic jets closely oriented to our line of sight (e.g., Urry & Padovani 1995). This may suggest that the nonthermal synchrotron emission of PSO J191+86 is Doppler boosted. Figure 8 shows the comparison between the radio luminosity at 8 GHz and the optical luminosity at 4400 Å of PSO J191+86 and of all the RL QSOs discovered in the literature at similar redshift (z = 4.5 − 5.5). For these RL QSOs, the luminosity at 8 GHz was computed starting from the observed flux at 1.4 GHz, and by assuming a radio spectral index of 0.75±0.25, as already done in other works (e.g., Bañados et al. 2015), as only a few sources have a tabulated spectral index in the literature. However, the observed 1.4 GHz frequency corresponds to a rest-frame frequency of 7.7–9 GHz for z = 4.5 − 5.5 sources, which is very close to 8 GHz. Therefore, the lack of a measured spectral index has only a marginal impact on the computed radio luminosities. Instead the luminosity at 4400 Å was computed from the de-reddened zPS1 band magnitude (the one available for all these sources) and assuming the optical spectral index of Vanden Berk et al. (2001, αν = 0.44). From Fig. 8, it is clear that PSO J191+86 is one of the most luminous RL QSOs at this redshift, confirming that the radio emission is produced in a powerful jet. Further investigation is necessary to properly interpret the radio emission from PSO J191+86.

thumbnail Fig. 8.

Rest-frame radio luminosity at 8 GHz vs. the rest-frame optical luminosity at 4400 Å for PSO J191+86 (red star) compared with z = 4.5 − 5.5 radio-loud QSOs (gray points) discovered in the literature. Squares represent all the sources defined as blazars in the literature on the basis of their radio and/or X-ray properties. Yellow circles represent all the sources identified as peaked spectrum objects in the literature (Coppejans et al. 2017; Shao et al. 2020, 2022). PSO J191+86 is one of the most luminous RL QSOs at these redshifts, confirming the power of its radio emission.

7.3. X-ray emission

From the X-ray properties reported in Sect. 5, we computed an X-ray luminosity of 5.33 erg s−1 in the [2–10] keV energy band6. This value clearly tells us that the X-ray emission of PSO J191+86 largely overwhelms that expected from a typical hot X-ray corona and therefore originates in a powerful jet. This is particular evident when plotting the SED of PSO J191+86 (Fig. 9): the X-ray emission is flatter and stronger with respect to that of RQ AGN with the same optical luminosity, according to the LX–LUV relation of Just et al. (2007).

thumbnail Fig. 9.

Rest-frame SED of PSO J191+86 from radio to X-ray frequencies. In the X-ray, we show the best-fit emission in the observed [0.5–10] keV energy band (green dotted line) with its uncertainty. We also report the TNG and LUCI spectra (in black) and a quasar template (SWIRE template library; light-green) as a guide line. The red dashed line represents the coronal emission expected from a RQ AGN with the same L2500 Å as PSO J191+86 according to the relation of Just et al. (2007), and the orange shaded area is the 1σ uncertainty on this estimate.

The value of the photon index (ΓX) computed from the Swift-XRT observation (Sect. 5) is flat (< 1.5), in line with that of peaked radio sources (e.g., Snios et al. 2020) and blazars (e.g., Ighina et al. 2019) at high redshift. Therefore, we cannot exclude that the X-ray emission of PSO J191+86 is dominated by a relativistic jet oriented toward the Earth, as the high value of R suggests as well. This is also indicated by the value of the of PSO J191+86, the ratio that quantifies the relative strength of the X-ray emission with respect to the optical/UV component. The is the two-point spectral index of a fictitious power law connecting 2500 Å and 10 keV in the rest frame of the source (Ighina et al. 2019): . The value of the monochromatic luminosity at 10 keV rest frame was computed from the observed flux density at [0.5–10] keV and using the αX value7: erg s−1 Hz−1. The luminosity at 2500 Å was instead measured from the flux density at 2500 Å directly obtained from the LUCI 2 rest-frame spectrum: L2500 Å = 5.56 ± 0.40 × 1031 erg s−1 Hz−1. We found an equal to 1.329, which is similar to that of high-z blazars (e.g., Ighina et al. 2019).

8. Discussion and conclusions

In this work, we present the discovery and multi-wavelength properties of PSO J191+86, a powerful radio QSO in the early Universe (z = 5.32). In the radio band, PSO J191+86 shows a possible peaked radio spectrum around ∼1 GHz in the observed frame, corresponding to ∼6.3 GHz in the rest frame. If this turnover is confirmed, PSO J191+86 will be one of the most powerful (L1.4 GHz = 1.17 × 1028 W Hz−1) GPS source at z > 5 ever discovered.

Assuming that the radio spectrum is peaked, we can compute the kinetic age of PSO J191+86 radio jets from the well-known correlation between peak frequency (νt in GHz) and projected angular size (l in kpc) derived by O’Dea & Baum (1997):

(5)

Assuming that the peak of the spectrum is between 1 and 2 GHz (observed frame, i.e., ∼6 and ∼13 GHz in the rest-frame), we obtain l in the range ∼10–30 pc (without taking into account the large scatter of the νt − l relation; e.g., Nyland et al. 2020). The corresponding kinetic age of the radio jets of PSO J191+86 would be in the range of ∼150–460 yr, assuming a typical hot spot expansion velocity of 0.2c (e.g., Giroletti & Polatidis 2009; An & Baan 2012). This would make PSO J191+86 one of the youngest GPS source at z ∼ 5 ever discovered. Therefore, a detailed study of its radio emission could shed light on the triggering of radio activity in this distant QSO, on the formation and early stage evolution of its radio jets, on their interaction with the ambient medium, and on their feedback on the host galaxy (e.g., Hardcastle & Croston 2020). However, the nonsimultaneity of the radio data at hand prevents us from assessing the real nature of the radio spectrum because of possible variability. Simultaneous observations over a wide range of frequencies are necessary to confirm the possible turnover.

The radio loudness of the source is very high (> 300), making PSO J191+86 similar to the bulk population of blazars in the early Universe. Moreover, the flat (ΓX = 1.32) and strong X-ray emission with respect to the optical emission () is similar to that of blazars. Therefore, PSO J191+86 could be a GPS object with the young relativistic jets oriented toward our line of sight. This is not uncommon at high-z, because the blazar Q0906+6930 (Romani et al. 2004) at z = 5.47 shows a clearly peaked radio spectrum (e.g., Coppejans et al. 2017; Mufakharov et al. 2021) with a turnover frequency of 6.4 GHz (observed frame), but, at the same time, Very Long Baseline Interferometry (VLBI) data found evidence of Doppler boosting (e.g., An et al. 2020). These results suggest that J0906+6930 is a GPS source likely oriented toward the observer. Similarly a multifrequency VLBI follow up for PSO J191+86 is in progress (Belladitta et al., in prep.) that is designed to spatially resolve the parsec-scale radio emission of the source and to find evidence of Doppler boosting.

3

As the LUCI2 spectrum does not cover the wavelengths up to 3000 Å, we used the continuum near the MgII line, between 2720 Å and 2750 Å, and extrapolated it to 3000 Å using the power-law index estimated from our data (αλ = −1.51).

4

The line centroid is defined as the wavelength that bisects the line, splitting it in two equal parts. We used the definition of Dalla Bontà et al. (2020): , where P(λ) is the line profile.

5

erg s−1.

6

, where z is the redshift estimated from the MgII line (see Table 5) and DL is the corresponding luminosity distance computed on https://www.astro.ucla.edu/~wright//CosmoCalc.html.

7

.

Acknowledgments

We thank the anonymous referee for the useful comments and suggestions. This work is based on observations made with the Large Binocular Telescope (LBT, program LBT2018AC123500-1). We are grateful to the LBT staff for providing the observations for this object. LBT is an international collaboration among institutions in the United States of America, Italy, and Germany. This work is based on observations made with the Italian Telescopio Nazionale Galileo (TNG) operated on the island of La Palma by the Fundación Galileo Galilei of the INAF (Istituto Nazionale di Astrofisica) at the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias. The observations were executed by M. Pedani on a night with a short slot of DDT time available. This work also used data from observations with the Neil Gehrels Swift Observatory (program ID: 3110833). This work made use of data supplied by the UK Swift Science Data Centre at the University of Leicester. SB, AC and AM acknowledge financial contribution from the agreement ASI-INAF n. I/037/12/0 and n.2017-14-H.0 and from INAF under PRIN SKA/CTA FORECaST. CS acknowledges financial support from the Italian Ministry of University and Research – Project Proposal CIR01_00010. This project used public archival data from the first data release of the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS PS1). Pan-STARRS1 PS1 have been made possible through contributions of the institutes listed in https://panstarrs.stsci.edu. The NVSS data was taken by the NRAO Very Large Array. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc. GMRT is run by the National Centre for Radio Astrophysics of the Tata Institute of Fundamental Research. WENSS is a joint project of the Netherlands Foundation for Research in Astronomy (NFRA) and Leiden Observatory. VLASS data have been obtained from the Canadian Astronomy Data Centre operated by the National Research Council of Canada with the support of the Canadian Space Agency. The Canadian Initiative for Radio Astronomy Data Analysis (CIRADA) is funded by a grant from the Canada Foundation for Innovation 2017 Innovation Fund (Project 35999) and by the Provinces of Ontario, British Columbia, Alberta, Manitoba and Quebec, in collaboration with the National Research Council of Canada, the US National Radio Astronomy Observatory and Australia’s Commonwealth Scientific and Industrial Research Organisation. This research made use of Astropy, a community-developed core Python package for Astronomy (Astropy Collaboration 2018).

References

  1. An, T., & Baan, W. A. 2012, ApJ, 760, 77 [Google Scholar]
  2. An, T., Mohan, P., Zhang, Y., et al. 2020, Nat. Commun., 11, 143 [Google Scholar]
  3. Assef, R. J., Denney, K. D., Kochanek, C. S., et al. 2011, ApJ, 742, 93 [Google Scholar]
  4. Astropy Collaboration (Price-Whelan, A. M., et al.) 2018, AJ, 156, 123 [Google Scholar]
  5. Bañados, E., Venemans, B. P., Morganson, E., et al. 2015, ApJ, 804, 118 [Google Scholar]
  6. Bañados, E., Carilli, C., Walter, F., et al. 2018, ApJ, 861, L14 [Google Scholar]
  7. Bañados, E., Mazzucchelli, C., Momjian, E., et al. 2021, ApJ, 909, 80 [CrossRef] [Google Scholar]
  8. Belladitta, S., Moretti, A., Caccianiga, A., et al. 2019, A&A, 629, A68 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  9. Belladitta, S., Moretti, A., Caccianiga, A., et al. 2020, A&A, 635, L7 [EDP Sciences] [Google Scholar]
  10. Bisogni, S., di Serego Alighieri, S., Goldoni, P., et al. 2017, A&A, 603, A1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  11. Blandford, R., Meier, D., & Readhead, A. 2019, ARA&A, 57, 467 [NASA ADS] [CrossRef] [Google Scholar]
  12. Caccianiga, A., Moretti, A., Belladitta, S., et al. 2019, MNRAS, 484, 204 [NASA ADS] [CrossRef] [Google Scholar]
  13. Carnall, A. C., Shanks, T., Chehade, B., et al. 2015, MNRAS, 451, L16 [Google Scholar]
  14. Chambers, K. C., Magnier, E. A., Metcalfe, N., et al. 2016, ArXiv e-prints [arXiv:1612.05560] [Google Scholar]
  15. Coatman, L., Hewett, P. C., Banerji, M., et al. 2017, MNRAS, 465, 2120 [Google Scholar]
  16. Condon, J. J., Cotton, W. D., Greisen, E. W., et al. 1998, AJ, 115, 1693 [Google Scholar]
  17. Coppejans, R., van Velzen, S., Intema, H. T., et al. 2017, MNRAS, 467, 2039 [NASA ADS] [Google Scholar]
  18. Corbin, M. R., & Boroson, T. A. 1996, ApJS, 107, 69 [NASA ADS] [CrossRef] [Google Scholar]
  19. Cutri, R. M., Wright, E. L., Conrow, T., et al. 2012, Explanatory Supplement to the WISE All-Sky Data Release Products [Google Scholar]
  20. Dalla Bontà, E., Peterson, B. M., Bentz, M. C., et al. 2020, ApJ, 903, 112 [CrossRef] [Google Scholar]
  21. Dallacasa, D., Stanghellini, C., Centonza, M., & Fanti, R. 2000, A&A, 363, 887 [NASA ADS] [Google Scholar]
  22. De Rosa, G., Venemans, B. P., Decarli, R., et al. 2014, ApJ, 790, 145 [Google Scholar]
  23. Diamond-Stanic, A. M., Fan, X., Brandt, W. N., et al. 2009, ApJ, 699, 782 [NASA ADS] [CrossRef] [Google Scholar]
  24. Diana, A., Caccianiga, A., Ighina, L., et al. 2022, MNRAS, 511, 5436 [NASA ADS] [CrossRef] [Google Scholar]
  25. Evans, P. A., Beardmore, A. P., Page, K. L., et al. 2009, MNRAS, 397, 1177 [Google Scholar]
  26. Fabian, A. C. 2012, ARA&A, 50, 455 [Google Scholar]
  27. Farina, E. P., Schindler, J. T., Walter, F., et al. 2022, ApJ, 941, 106 [NASA ADS] [CrossRef] [Google Scholar]
  28. Fitzpatrick, E. L. 1999, PASP, 111, 63 [Google Scholar]
  29. Gargiulo, A., Fumana, M., Bisogni, S., et al. 2022, MNRAS, 514, 2902 [NASA ADS] [CrossRef] [Google Scholar]
  30. Gaskell, C. M. 1982, ApJ, 263, 79 [NASA ADS] [CrossRef] [Google Scholar]
  31. Giroletti, M., & Polatidis, A. 2009, Astron. Nachr., 330, 193 [Google Scholar]
  32. Greene, J. E., Peng, C. Y., & Ludwig, R. R. 2010, ApJ, 709, 937 [Google Scholar]
  33. Hardcastle, M. J., & Croston, J. H. 2020, New Astron. Rev., 88, 101539 [Google Scholar]
  34. Healey, S. E., Fuhrmann, L., Taylor, G. B., Romani, R. W., & Readhead, A. C. S. 2009, AJ, 138, 1032 [NASA ADS] [CrossRef] [Google Scholar]
  35. Ighina, L., Caccianiga, A., Moretti, A., et al. 2019, MNRAS, 489, 2732 [NASA ADS] [CrossRef] [Google Scholar]
  36. Ighina, L., Caccianiga, A., Moretti, A., et al. 2023, MNRAS, 519, 2060 [Google Scholar]
  37. Intema, H. T., Jagannathan, P., Mooley, K. P., & Frail, D. A. 2017, A&A, 598, A78 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  38. Just, D. W., Brandt, W. N., Shemmer, O., et al. 2007, ApJ, 665, 1004 [Google Scholar]
  39. Kalberla, P. M. W., Burton, W. B., Hartmann, D., et al. 2005, A&A, 440, 775 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  40. Karouzos, M., Woo, J.-H., Matsuoka, K., et al. 2015, ApJ, 815, 128 [NASA ADS] [CrossRef] [Google Scholar]
  41. Kellermann, K. I., Sramek, R., Schmidt, M., Shaffer, D. B., & Green, R. 1989, AJ, 98, 1195 [Google Scholar]
  42. Lacy, M., Baum, S. A., Chandler, C. J., et al. 2020, PASP, 132 [Google Scholar]
  43. Liu, Y., Wang, R., Momjian, E., et al. 2021, ApJ, 908, 124 [Google Scholar]
  44. Mainzer, A., Bauer, J., Grav, T., et al. 2011, ApJ, 731, 53 [Google Scholar]
  45. Marziani, P., Sulentic, J. W., Dultzin-Hacyan, D., Calvani, M., & Moles, M. 1996, ApJS, 104, 37 [Google Scholar]
  46. Marziani, P., Sulentic, J. W., Negrete, C. A., et al. 2010, MNRAS, 409, 1033 [Google Scholar]
  47. Marziani, P., Sulentic, J. W., Plauchu-Frayn, I., & del Olmo, A. 2013, A&A, 555, A89 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  48. Marziani, P., del Olmo, A., Martínez-Carballo, M. A., et al. 2019, A&A, 627, A88 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  49. Massaro, F., Giroletti, M., D’Abrusco, R., et al. 2014, ApJS, 213, 3 [NASA ADS] [CrossRef] [Google Scholar]
  50. Mazzucchelli, C., Bañados, E., Venemans, B. P., et al. 2017, ApJ, 849, 91 [Google Scholar]
  51. McGreer, I. D., Becker, R. H., Helfand, D. J., & White, R. L. 2006, ApJ, 652, 157 [Google Scholar]
  52. McLure, R. J., & Dunlop, J. S. 2004, MNRAS, 352, 1390 [NASA ADS] [CrossRef] [Google Scholar]
  53. McMullin, J. P., Waters, B., Schiebel, D., Young, W., & Golap, K. 2007, ASP Conf. Ser., 376, 127 [Google Scholar]
  54. Mufakharov, T., Mikhailov, A., Sotnikova, Y., et al. 2021, MNRAS, 503, 4662 [NASA ADS] [CrossRef] [Google Scholar]
  55. Nyland, K., Dong, D. Z., Patil, P., et al. 2020, ApJ, 905, 74 [NASA ADS] [CrossRef] [Google Scholar]
  56. O’Dea, C. P., & Baum, S. A. 1997, AJ, 113, 148 [CrossRef] [Google Scholar]
  57. O’Dea, C. P., & Saikia, D. J. 2021, A&ARv, 29, 3 [Google Scholar]
  58. Oke, J. B. 1990, AJ, 99, 1621 [Google Scholar]
  59. Orienti, M., & Dallacasa, D. 2020, MNRAS, 499, 1340 [NASA ADS] [CrossRef] [Google Scholar]
  60. Padovani, P., Alexander, D. M., Assef, R. J., et al. 2017, A&ARv, 25, 2 [Google Scholar]
  61. Raiteri, C. M., Acosta Pulido, J. A., Villata, M., et al. 2020, MNRAS, 493, 2793 [NASA ADS] [CrossRef] [Google Scholar]
  62. Rakshit, S., Stalin, C. S., & Kotilainen, J. 2020, ApJS, 249, 17 [Google Scholar]
  63. Rengelink, R. B., Tang, Y., de Bruyn, A. G., et al. 1997, A&AS, 124, 259 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  64. Romani, R. W., Sowards-Emmerd, D., Greenhill, L., & Michelson, P. 2004, ApJ, 610, L9 [Google Scholar]
  65. Richards, G. T., Kruczek, N. E., Gallagher, S. C., et al. 2011, AJ, 141, 167 [Google Scholar]
  66. Runnoe, J. C., Brotherton, M. S., DiPompeo, M. A., & Shang, Z. 2014, MNRAS, 438, 3263 [NASA ADS] [CrossRef] [Google Scholar]
  67. Sbarrato, T., Ghisellini, G., Nardini, M., et al. 2012, MNRAS, 426, L91 [Google Scholar]
  68. Schindler, J.-T., Farina, E. P., Bañados, E., et al. 2020, ApJ, 905, 51 [Google Scholar]
  69. Seifert, W., Appenzeller, I., Baumeister, H., et al. 2003, SPIE Conf. Ser., 4841, 962 [Google Scholar]
  70. Shao, Y., Wagg, J., Wang, R., et al. 2020, A&A, 641, A85 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  71. Shao, Y., Wagg, J., Wang, R., et al. 2022, A&A, 659, A159 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  72. Shen, Y., & Liu, X. 2012, ApJ, 753, 125 [NASA ADS] [CrossRef] [Google Scholar]
  73. Shen, Y., Greene, J. E., Strauss, M. A., Richards, G. T., & Schneider, D. P. 2008, ApJ, 680, 169 [Google Scholar]
  74. Shen, Y., Richards, G. T., Strauss, M. A., et al. 2011, ApJS, 194, 45 [Google Scholar]
  75. Shen, Y., Wu, J., Jiang, L., et al. 2019, ApJ, 873, 35 [Google Scholar]
  76. Snios, B., Siemiginowska, A., Sobolewska, M., et al. 2020, ApJ, 899, 127 [NASA ADS] [CrossRef] [Google Scholar]
  77. Sulentic, J. W., Bachev, R., Marziani, P., Negrete, C. A., & Dultzin, D. 2007, ApJ, 666, 757 [NASA ADS] [CrossRef] [Google Scholar]
  78. Tang, B., Shang, Z., Gu, Q., Brotherton, M. S., & Runnoe, J. C. 2012, ApJS, 201, 38 [NASA ADS] [CrossRef] [Google Scholar]
  79. Tody, D. 1993, ASP Conf. Ser., 52, 173 [NASA ADS] [Google Scholar]
  80. Trakhtenbrot, B. 2021, IAU Proc. 356, 261 [NASA ADS] [Google Scholar]
  81. Trakhtenbrot, B., & Netzer, H. 2012, MNRAS, 427, 3081 [NASA ADS] [CrossRef] [Google Scholar]
  82. Urry, C. M., & Padovani, P. 1995, PASP, 107, 803 [NASA ADS] [CrossRef] [Google Scholar]
  83. Vanden Berk, D. E., Richards, G. T., Bauer, A., et al. 2001, AJ, 122, 549 [Google Scholar]
  84. Vestergaard, M. 2002, ApJ, 571, 733 [NASA ADS] [CrossRef] [Google Scholar]
  85. Vestergaard, M., & Osmer, P. S. 2009, ApJ, 699, 800 [Google Scholar]
  86. Vestergaard, M., & Peterson, B. M. 2006, ApJ, 641, 689 [Google Scholar]
  87. Vestergaard, M., & Wilkes, B. J. 2001, ApJS, 134, 1 [Google Scholar]
  88. Vietri, G., Piconcelli, E., Bischetti, M., et al. 2018, A&A, 617, A81 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  89. Vito, F., Mignoli, M., Gilli, R., et al. 2022, A&A, 663, A159 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  90. Volonteri, M., Silk, J., & Dubus, G. 2015, ApJ, 804, 148 [Google Scholar]
  91. Wills, B. J., Brotherton, M. S., Fang, D., Steidel, C. C., & Sargent, W. L. W. 1993, ApJ, 415, 563 [NASA ADS] [CrossRef] [Google Scholar]
  92. Wright, E. L., Eisenhardt, P. R. M., Mainzer, A. K., et al. 2010, AJ, 140, 1868 [Google Scholar]
  93. Yi, W.-M., Wang, F., Wu, X.-B., et al. 2014, ApJ, 795, L29 [Google Scholar]
  94. Zeimann, G. R., White, R. L., Becker, R. H., et al. 2011, ApJ, 736, 57 [Google Scholar]
  95. Zuo, W., Wu, X.-B., Fan, X., et al. 2020, ApJ, 896, 40 [NASA ADS] [CrossRef] [Google Scholar]

All Tables

Table 1.

Optical and MIR magnitudes of PSO J191+86.

In the text
Table 2.

Summary of the optical and NIR follow-up spectroscopic observations of PSO J191+86.

In the text
Table 3.

Properties of the quick-look VLASS 2.1 image of PSO J191+86.

In the text
Table 4.

Summary of the archival radio observations of PSO J191+86.

In the text
Table 5.

Properties of CIV and MgII BELs.

In the text

All Figures

thumbnail Fig. 1.

0.2′×0.2′ Pan-STARRS PS1 g, r, i, z, y cutout images of PSO J191+86. Its optical position is marked with a red circle of 1.5″ of diameter. The radio NVSS position is marked with a blue dashed circle, as large as the radio positional error reported in the catalog (1.7″). All images are oriented with north up and east to the left.
In the text
thumbnail Fig. 2.

Optical and NIR de-reddened observed spectra of PSO J191+86 taken at TNG and LBT, respectively. The most important visible emission lines are marked. We masked the part of the MgII line that suffers from a strong absorption feature, in which the peak of the MgII line falls (shown here in gray). The top x-axis reports the rest-frame wavelengths while the right axis shows the monochromatic luminosity.
In the text
thumbnail Fig. 3.

3′×3′ cutout of the iPS1 image around PSO J191+86 overlaid with the radio contours from NVSS (1.4 GHz, cyan), WENSS (325 MHz, blue), and VLASS (3 GHz, yellow). In all cases, contours are spaced by starting from three times the survey rms (NVSS = 0.42 mJy beam−1; VLASS = 160 μJy beam−1; WENSS = 2.7 mJy beam−1). A zoom onto the VLASS emission is shown in Fig. 4. The red cross indicates the optical position of the source.
In the text
thumbnail Fig. 4.

VLASS 2.1 image of PSO J191+86. The contours are drawn at −3, −2, 2, 3, 6, 9, 18, 36, 72, and 144 times the off-source rms (160 μJy). In the bottom left corner, the beam size (4.372″ × 2.241″) is shown. North is up, east is left.
In the text
thumbnail Fig. 5.

Swift-XRT observed spectrum of PSO J191+86 modeled with a single power law with only Galactic absorption (solid red line).
In the text
thumbnail Fig. 6.

Zoom into the CIV and MgII line fit and into the Lyα+NV region. Left and central panel: total spectral fit (red line), and the different components, i.e., power law + Balmer pseudo-continuum (blue line), Fe II template (orange line, from Vestergaard & Wilkes 2001), and emission lines (purple). For the MgII, we represent the two lines of the doublet (solid Gaussians and dashed Gaussians, respectively). Spectral regions used for the continuum fits are shown as horizontal light blue shaded areas. In the right panel, the absorption feature in the middle of the MgII line is masked (gray dotted line). Right panel: Lyα and NV spectral region. The blue vertical lines represent the positions of the two BELs based on the MgII line redshift. The cyan shaded region is the uncertainty on this redshift estimate. The top x-axis reports the rest-frame wavelengths while the right axis shows the monochromatic luminosity.
In the text
thumbnail Fig. 7.

Radio flux densities as a function of the observed (bottom x-axis) and rest-frame (top x-axis) frequency of PSO J191+86 from 0.150 to 4.85 GHz. The spectrum shows a peak around ∼1 GHz, and therefore the source can be classified as a GPS. The corresponding indices of the low- and high-frequency parts of the spectrum are reported together with the reference surveys. The red dashed line represents the possible spectral index according to the TGSS upper limit.
In the text
thumbnail Fig. 8.

Rest-frame radio luminosity at 8 GHz vs. the rest-frame optical luminosity at 4400 Å for PSO J191+86 (red star) compared with z = 4.5 − 5.5 radio-loud QSOs (gray points) discovered in the literature. Squares represent all the sources defined as blazars in the literature on the basis of their radio and/or X-ray properties. Yellow circles represent all the sources identified as peaked spectrum objects in the literature (Coppejans et al. 2017; Shao et al. 2020, 2022). PSO J191+86 is one of the most luminous RL QSOs at these redshifts, confirming the power of its radio emission.
In the text
thumbnail Fig. 9.

Rest-frame SED of PSO J191+86 from radio to X-ray frequencies. In the X-ray, we show the best-fit emission in the observed [0.5–10] keV energy band (green dotted line) with its uncertainty. We also report the TNG and LUCI spectra (in black) and a quasar template (SWIRE template library; light-green) as a guide line. The red dashed line represents the coronal emission expected from a RQ AGN with the same L2500 Å as PSO J191+86 according to the relation of Just et al. (2007), and the orange shaded area is the 1σ uncertainty on this estimate.
In the text

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.