In this work we spectroscopically select narrowline AGN NLAGN among the sim 300 publicly available mediumresolution spectra of the CEERS Survey. Using both traditional and newly identified emission line NLAGN diagnostics diagrams we identified 52 NLAGN at 2lesssim zlesssim 9 on which we performed a detailed multiwavelength analysis. We also identified 4 new zlesssim 2 broadline AGN BLAGN in addition to the 8 previously reported highz BLAGN. We found that the traditional BPT diagnostic diagrams are not suited to identify highz AGN while most of the highz NLAGN are selected using the recently proposed AGN diagnostic diagrams based on the OIIIlambda4363 auroral line or highionization emission lines. We compared the emission line velocity dispersion and the obscuration of the sample of NLAGN with those of the parent sample without finding significant differences between the two distributions suggesting a population of AGN heavily buried and not significantly impacting the host galaxies physical properties as further confirmed by SEDfitting. The bolometric luminosities of the highz NLAGNs selected in this work are well below those sampled by surveys before JWST potentially explaining the weak impact of these AGN. Finally we investigate the Xray properties of the selected NLAGN and of the sample of highz BLAGN. We find that all but 4 NLAGN are undetected in the deep Xray image of the field as well as all the highz BLAGN. We do not obtain a detection even by stacking the undetected sources resulting in an Xray weakness of sim 12 dex from what is expected based on their bolometric luminosities. To discriminate between a heavily obscured AGN scenario or an intrinsic Xray weakness of these sources we performed a radio stacking analysis which did not reveal any detection leaving open the questions about the origin of the Xray weakness.
['Astrophysics - Astrophysics of Galaxies', 'Astrophysics - Cosmology and Nongalactic Astrophysics']
Narrow line AGN selection in CEERS spectroscopic selection physical properties Xray and radio analysis
{'Narrow line AGN selection in CEERS: spectroscopic selection, physical properties, X-ray and radio analysis': "Giovanni Mazzolari 1 , 2 , 3, ⋆ , Jan Scholtz 3 , 4 , Roberto Maiolino 3 , 4 , 5 , Roberto Gilli 2 , Alberto Traina 2 , Iván E. López 2 , Hannah Übler 3 , 4 , Bartolomeo Trefoloni 6 , 7 , Francesco D'Eugenio 3 , 4 , Xihan Ji 3 , 4 , Marco Mignoli 2 , Fabio Vito 2 , and 1  \nMarcella Brusa  \n- 1 Dipartimento di Fisica e Astronomia, Università di Bologna, Via Gobetti 93 / 2, I-40129 Bologna, Italy\n- 2 INAF - Osservatorio di Astrofisica e Scienza dello Spazio di Bologna, Via Gobetti 93 / 3, I-40129 Bologna, Italy\n- 3 Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge, CB3 0HA, UK\n- 4 Cavendish Laboratory, University of Cambridge, 19 JJ Thomson Avenue, Cambridge, CB3 0HE, UK\n- 5 Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, UK\n- 6 Dipartimento di Fisica e Astronomia, Università di Firenze, Via G. Sansone 1, 50019 Sesto Fiorentino, Firenze, Italy\n- 7 INAF - Osservatorio Astrofisico di Arcetri, Largo Enrico Fermi 5, 50125 Firenze, Italy", 'ABSTRACT': "The transformative era opened by JWST on the highz Universe allows us to investigate the early stages of the Supermassive Black Holes (SMBH) evolution, with the first results showing a greater than expected number of active galactic nuclei (AGN) at very early times. In this work, we spectroscopically select narrow-line AGN (NLAGN) among the ∼ 300 publicly available medium-resolution spectra of the Cosmic Evolution Early Release Science Survey (CEERS). Using both traditional and newly identified emission line NLAGN diagnostics diagrams, we identified 52 NLAGN at 2 ≲ z ≲ 9 on which we performed a detailed multiwavelength analysis. We also identified 4 new z ≲ 2 broad-line AGN (BLAGN), in addition to the 8 previously reported high-redshift BLAGN. We found that the traditional BPT diagnostic diagrams are not suited to identify highz AGN, while most of the highz NLAGN are selected using the recently proposed AGN diagnostic diagrams based on the [O iii ] λ 4363 auroral line or high-ionization emission lines.We compared the emission line velocity dispersion and the obscuration levels of the sample of NLAGN with those of the parent sample without finding significant di ff erences between the two distributions, suggesting a population of AGN heavily buried and not significantly impacting the host galaxies' physical properties, as further confirmed by SED-fitting. The bolometric luminosities of the highz NLAGNs selected in this work are well below those sampled by surveys before JWST, potentially explaining the weak impact of these AGN. Finally, we investigate the X-ray properties of the selected NLAGN and of the sample of highz BLAGN. We find that all but 4 NLAGN are undetected in the deep X-ray image of the field, as well as all the highz BLAGN. We do not obtain a detection even by stacking the undetected sources, resulting in an X-ray weakness of ∼ 1 -2 dex from what is expected based on their bolometric luminosities. To discriminate between a heavily obscured AGN scenario or an intrinsic X-ray weakness of these sources, we performed a radio (1.4GHz) stacking analysis, which did not reveal any detection and left open the questions about the origin of the X-ray weakness.  \nKey words. Galaxies: active, Galaxies: high-redshift, Galaxies: ISM", '1. Introduction': "Thanks to the successful launch of the James Webb Space Telescope (JWST; Gardner et al. 2023; Rigby et al. 2023), we are now able to investigate with high resolution and unprecedented sensitivity both the photometric and spectroscopic properties of galaxies up to z ∼ 14 (Carniani et al. 2024; Curtis-Lake et al. 2022; Robertson et al. 2022). Within this context, recent studies, exploiting both spectroscopic and imaging data from JWST, have revealed a large population of active galactic nuclei (AGN) at high redshift (Kocevski et al. 2023; Übler et al. 2023; Übler et al. 2024; Matthee et al. 2023; Maiolino et al. 2024b, 2023; Greene et al. 2023; Bogdán et al. 2023; Goulding et al. 2023; Kokorev et al. 2023; Furtak et al. 2023; Juodžbalis et al. 2024b; Scholtz et al. 2023a; Chisholm et al. 2024), providing the unique opportunity to study the properties of supermassive black hole (SMBH) and the AGN-galaxy coevolution, since very early times.  \nDi ff erent works, selecting AGN at highz using JWST NIR and MIR photometry, showed that the AGN population at z > 3 is larger than previously expected and that it is probably dominated by obscured, or even heavily obscured sources, as predicted by some coevolutional models Hopkins et al. (2008); Hickox & Alexander (2018). Yang et al. (2023a), taking advantage of the JWST-MIRI photometry of the Cosmic Evolution Early Release Science Survey (CEERS; Finkelstein et al. 2022), investigated the AGN population using spectral energy distribution (SED) modelling, and found a black-hole accretion rate density (BHARD) at z > 3 ∼ 0 . 5 dex higher than what was expected from previous X-ray AGN studies (Vito et al. 2016, 2018). Also Lyu et al. (2024) performing a similar analysis using the JWST / MIRI data of the SMILES survey selected a remarkable fraction of AGN among the MIRI detected sources ( ∼ 7%) and found a statistically significant increase of the obscured AGN fraction with both AGN luminosity and redshift, as previously found in other works (Signorini et al. 2023; Gilli et al. 2022; Buchner et al. 2015; Aird et al. 2015).  \nThe existence of a larger-than-expected AGN population at z > 4 was also shown by spectroscopic studies. For example, Maiolino et al. (2023) and Harikane et al. (2023), by selecting broad-line AGN (BLAGN, or TypeI) among JWST / NIRSpec spectra, found significant AGN excess at z > 4 with respect to the AGN luminosity functions derived using X-ray data (Giallongo et al. 2019).  \nJWST data not only allow the identification of a higher fraction of AGN at highz but also show some new and unexpected features in this early population of SMBHs. Studies have revealed that early SMBHs tend to be overmassive relative to the host galaxy stellar mass, when compared with the local AGN distribution (Maiolino et al. 2023; Bogdán et al. 2023; Furtak et al. 2023; Juodžbalis et al. 2024b), suggesting that the early stages of the coevolution between the SMBH and the host galaxy can be dominated by SMBH growth. This could further suggest that the preferred driving channel for the SMBH formation could be the so-called 'Direct Collapse Black Hole' scenario, together with (or alternatively) episodes of super-Eddington accretion (Scholtz et al. 2023b).  \nAnother remarkable feature of highz newly discovered AGN is that they seem to be X-ray weak compared to the low-redshift AGN population. X-rays have been traditionally used to select AGN because at the typical AGN X-ray luminosities (log LX ≥ 42), the level of contamination by stellar processes is low, allowing a generally pure AGN selection. However, even if X-ray photons are able to penetrate through dense environments, they are almost completely absorbed at Compton-thick (CTK) hydrogen column densities (log( NH / cm -2 ) ≥ 24), making the X-ray identification of heavily obscured AGN challenging (Vignali et al. 2015; Lanzuisi et al. 2018; Goulding et al. 2023; Maiolino et al. 2024a).  \nSpecifically, most of the newly selected AGNs, including BLAGN, lack any X-ray emission (Maiolino et al. 2024a; Yue et al. 2024), even if located in fields covered by some of the deepest extragalactic X-ray observations ever performed. Given the very few exceptions (Goulding et al. 2023; Kovacs et al. 2024; Maiolino et al. 2024a) of X-ray AGN detections in the early Universe, it is possible that the X-ray weakness could be due to intrinsic properties of highz AGN, as it was also suggested for some lowz AGN (Simmonds et al. 2018; Zhang et al. 2023). In this view, AGN can be characterized by a di ff erent accretiondisk / coronal structure that can determine, for example, a larger ratio of the optical to X-ray emission ( α OX ) due to a much lower e ffi ciency of the corona in producing X-ray photons, or simply lack of corona (Proga 2005). Recently, Maiolino et al. (2024a), analysing the lack of X-ray emission in a large sample of highz sources unambiguously identified as AGN, suggested that their X-ray weakness could also be ascribed to the presence, in the inner region of the AGN, of a spherical distribution of clouds with CTK column densities and very low dust content, such as the Broad Line Region (BLR) clouds. In this hypothesis, highz BLAGN do not need to be characterized by any kind of intrinsic X-ray weakness, as their lack of X-ray emission would simply be caused by the inner CTK broad-line region gas.  \nJWST spectroscopy can give us information on the nature of the observed sources, allowing to identify and investigate not only the population of BLAGN, which is probably only the tip of the iceberg of the entire AGN census but also the vast and hidden population of narrow-line AGN (NLAGN, also called TypeII). An additional significant di ff erence between highz and lowz AGN consists in the remarkably di ff erent physical environments constituted by their host galaxies. Indeed, early galaxies are systematically more metal-poor and characterized by younger stel-  \nlar populations (Curti et al. 2023a) that increase their ionization parameters in the ISM (log U; Cameron et al. 2023; Curti et al. 2023a). These two e ff ects have a significant impact on the selection of NLAGN, traditionally based on optical emission-line diagnostic diagrams, because the lower metallicities and the larger log U make star-forming galaxies (SFG) and AGN move towards each other and eventually overlap on the traditional diagnostic diagrams (Übler et al. 2023; Kocevski et al. 2023; Maiolino et al. 2023; Scholtz et al. 2023a; Mazzolari et al. 2024).  \nHowever, the identification of the elusive population of NLAGN is crucial in order to have a complete census of the AGN population, especially at highz , and to build up statistical AGNsamples that can solve the problems on AGN identification and properties at highz .  \nSo far, the systematic search for NLAGN at z > 3 has been attempted only by a few works. In Scholtz et al. (2023a) the authors selected 42 NLAGN among ∼ 200 medium resolution (MR) spectra of the JADES survey (Eisenstein et al. 2023; Bunker et al. 2023). In particular, they used JADES spectra to select NLAGN through a series of rest-frame optical, rest-frame UVdiagnostic diagrams, and by exploiting the detection of highionization emission lines, which usually require AGN as a photoionizing source. The selected sample allowed the authors to investigate the population of AGN up to z ∼ 9, down to bolometric luminosities log Lbol ∼ 42 and host galaxy stellar masses of 10 7 M ⊙ , vastly expanding the region of the parameter space populated by these objects at early times.  \nIn this work, we perform a similar analysis investigating the NLAGN population hidden among the sample of MR spectra collected in the CEERS survey. The paper is organized as follows. In Sec. 2, we present the data and the sample of spectra analyzed throughout this work and the techniques involved in the subsequent analysis: emission line fitting, spectral stacking, SED-fitting, and X-ray and radio stacking. In Sec. 3 we describe the di ff erent emission line diagnostic diagrams involved in the NLAGNselection and the results of the selection. Then in Sec. 4 we discuss the physical properties of the selected NLAGN: the AGN prevalence (Sec. 4.4), the distribution in velocity dispersion and obscuration (Sec. 4.5, Sec. 4.6), the bolometric luminosities (Sec. 4.7), the host galaxies properties (Sec. 4.8), and finally in Sec. 4.9 and Sec. 4.10 the X-ray and radio analysis, respectively.  \nWe assume a flat Λ CDM universe with H 0 = 70 km s -1 Mpc -1 , Ω m = 0 . 3 , ΩΛ = 0 . 7 , Ω k = 0.", '2.1. CEERS Observational Data': 'We use publicly available medium resolution (MR) JWST NIRSpec (Jakobsen et al. 2022) Micro-Shutter Assembly (MSA; Ferruit et al. 2022a) data from the CEERS program (Program ID:1345, Finkelstein et al. 2022). The CEERS NIRSpec observations consist of six pointings in the \'Extended Groth Strip\' field (EGS; Rhodes et al. 2000; Davis et al. 2007), all of which utilized the three grating / filter combination of G140M / F100LP, G235M / F170LP, and G395M / F290LP. This provided a spectral resolution of R ∼ 1000 over the wavelength range of approximately 1-5 µ m (Jakobsen et al. 2022). Each grating / filter combination was observed for a total of 3107s for each pointing. In particular, we considered the 313 spectra reduced and published by the CEERS collaboration in their latest data re-  \nse DR-0.7 1 . The data reduction was performed by the CEERS collaboration using the JWST Calibration Pipeline version 1.8.5 (Bushouse et al. 2022), using the CRDS context "jwst\\_1029.pmap". The spectra were reduced using processing standard pipeline parameters, with some specific deviation in particular regarding the \'jump\' parameters and the socalled "snowball" corrections. Nodded background subtraction was employed. The pipeline was instructed that all targets should be treated as point sources, determining each 1D spectrum to be extracted from the 2D spectral data file over a specified range of pixels in the cross-dispersion direction. Extraction apertures on the 2D spectra were determined for each object by interactive visual inspection and were specified explicitly for pipeline step \'extract\\_1d\'. Most faint galaxies are compact, and the extraction apertures adopted for nearly all objects have heights ranging from 3 to 6 pixels (scale = 0.10 arcsec / pixel), with a median value of 4 pixels. The default pipeline path-loss correction was employed. This calibration is based primarily on pre-flight modelling, assuming the targets are point sources and determining these corrections to be incomplete for significantly extended sources, but this is not the case for the large majority of the targets. Flux calibration uses the default reference files for the adopted CRDS context.  \nFor this work, we used the spectra with the three single grating spectra combined together. The data from the individual MR gratings are resampled to a common wavelength vector in the overlapping regions, adopting the wavelength grating which in the overlap region has the worst spectral resolution. Flux values in the overlap regions are the average of the individual grating values weighted by the flux errors, excluding pixels a ff ected by masked artefacts.  \nAfter a careful visual inspection of the 313 single MR spectra available, we were able to attribute a secure redshift to 217 sources, constituting our parent sample throughout this work.  \nHarikane et al. (2023) already investigated a limited sample of these spectra (i.e. only those at z > 3 . 8) to look for BLAGN, selecting 10 AGNs at z = 4 . 015 -6 . 936 (2 of which are marked only as candidates) whose broad component is only seen in the permitted H α or H β lines and not in the forbidden [O iii ] λ 5007 line. In the rest of the paper we mark the 8 most reliable BLAGN selected in Harikane et al. (2023) as the sample of highz BLAGN.', '2.2. Emission line fitting': "The NLAGN selection performed in this work is based on emission line diagnostics diagrams, where the AGN selection is provided by demarcation lines taken from the literature or by comparing the distribution of the sources with photoionization models, following the procedure done in Scholtz et al. (2023a).  \nWe used a modified version of the publicly available code QubeSpec (Scholtz et al. 2023a; D'Eugenio et al. 2024) to fit the spectra of the sources. We fit the emission lines considering only small wavelength ranges around the single (or group of) emission lines ( ∼ 500Å), with each emission line fitted using a single Gaussian component. The continuum was fit with a power law model, and in most of the spectra it was not detected. This approach for the fit of the continuum is su ffi cient for describing a narrow continuum range around an emission line of interest, and we found no instances of a strong continuum that required more sophisticated (e.g., stellar emission) modelling. QubeSpec uses a Bayesian approach, which requires defining prior probability distributions for each model parameter. In our fit, we as-  \ne log-uniform priors for the peak of the Gaussian describing each line and also for the continuum normalization. The prior on the lines full-width half maximum (FWHMs) is set to a uniform distribution spanning from the minimum resolution of the NIRSpec / MSA ( ∼ 200km / s) up to a maximum of 700 km / s. For the fit of the highz BLAGN identified in Harikane et al. (2023) we also include in the fit a broad component in the H α (with a FWHM uniform prior between 900 -5000km / s) to carefully disentangle the broad H α emission from the narrow one, that is the only component used in the diagnostic diagrams. The prior on the redshift is a normal distribution centred on the redshift obtained from the visual inspection with a standard deviation of 100 km / s.  \nTo estimate the posterior probability distribution of all these parameters, we use a Markov chain Monte Carlo integrator ( emcee ; Foreman-Mackey et al. 2013).  \nTo address the NLAGN selection, we performed a fit of the following rest-frame optical and UV emission line blocks:  \n- -H α + [N ii ] λλ 6548,83 + [S ii ] λλ 6716,31\n- -[O i ] λ 6300\n- -H β + [O iii ] λλ 4959,5008 + He ii λ 4686\n- -H γ + [O iii ] λ 4363\n- -[O ii ] λλ 3726,29 + [Ne iii ] λ 3869\n- -[Ne v ] λ 3426\n- -[Ne iv ] λλ 2422,24\n- -C iii ] λλ 1907,10\n- -[O iii ] λλ 1660,66 + He ii λ 1640 + C iv λλ 1548,51\n- -N iv ] λλ 1483,86\n- -Ly α + N v λ 1240  \nFor the components of the [O iii ] λλ 4959,5008 and [N ii ] λλ 6548,84 doublets, we fixed the ratios between the two components to be 1:3 given by the relative Einstein coe ffi -cients of the two transitions.  \nGiven the resolution of the NIRSpec MR spectra, we fit the [O ii ] λλ 3726,29, [Ne iv ] λλ 2422,24, C iv λλ 1548,51, [O iii ] λλ 1660,66, C iii ] λλ 1907,10, and N iv ] λλ 1483,86 doublets as single Gaussians, centered at the mean wavelength between the two components.  \nThe signal-to-noise ratio (S / N) of each line was evaluated considering the same equations reported in Mignoli et al. (2019) and Lenz & Ayres (1992), and requiring at least S / N > 5 for the detection. Then, we visually inspected all the detected lines to exclude any possible false detection. In case of undetection, we derived the upper limit to the flux of each line as 3 σ the error on the flux returned by QubeSpec .  \nWhile fitting the H α line, we found 4 sources at z ≤ 2 for which the residuals from the narrow-line-only fit were too large, and a broad component was required. These sources were not selected as in Harikane et al. (2023) because in that work the authors investigated only sources at z > 3 . 8. We identify these sources as new BLAGN at lowz ; their spectra are presented in Appendix A. In fitting all the BLAGN, we did not find any significant broad component either in the H β or in the [O iii ] λ 5007 lines.", '2.3. Spectral Stacking': 'Once the final sample of 52 NLAGN has been selected, to get the average emission line properties of the Star-forming galaxies (SFG) and NLAGN samples, we stacked the MR spectra for each of the emission line complexes investigated in this work. The spectral stacking was performed firstly, normalizing all the NLAGN and SFG spectra by the peak flux of the [O iii ] λ 5007  \nTable 1: Definitions of line ratios adopted throughout the paper.  \nline, in order not to be biased towards the brightest objects. The [O iii ] λ 5007 line is the most common and well-detected line among the CEERS MR spectra, but is not available in 8 AGN and in 14 SFG spectra because for these sources the line falls into a detector gap. Therefore we excluded them from the stacking. We shifted all the spectra to the rest frame, and then we resampled each of the spectra to a uniform and common wavelength grid, given that the three components of each spectrum (corresponding to the three di ff erent gratings) have di ff erent resolutions and wavelength bins. The new, and uniform, wavelength grid was defined, for each line complex, by the wavelength bin allowing for the best spectral resolution among the di ff erent resolutions of the spectra involved in the stacking of the line(s). We checked that the results do not significantly change taking the wavelength bin corresponding to the worst spectral resolution among the spectra. Before stacking the spectra, we also fit and subtract the continuum from the rest-frame rebinned spectra.  \nWe finally opted for spectral stacking involving a bootstrap procedure, given the number of sources involved. The stacked spectrum and uncertainties of each spectral bin were derived taking the median and standard deviation of 250 bootstrap realizations of the input spectra. The resulting spectra from the stacking of all NLAGN and SFG are presented in Fig. 1.', '2.4. SED fitting': 'To investigate the physical properties of the host galaxies of the selected NLAGN and to compare them with the properties of the parent sample, we performed a SED fitting analysis using CIGALE (Boquien et al. 2019). Starting from the 217 spectra of the MR sample with a secure redshift, we first cross-match the target coordinates with the HST + JWST publicly available photometric catalog of the CEERS field reported in the DJA archive 2 . Considering a 0.5" matching radius we found 117 counterparts. This catalog includes seven HST bands (F435W, F606W, F814W, F105W, F125W, F140W, F160W) and ten JWST / NIRCam and MIRI bands (F115W, F150W, 182M, F200W, 210M, F277W, F356W, F410M, F444W, F770W). Since not the whole CEERS MR sample is covered by JWST imaging, we also cross-match the remaining sources with the 3DHST multiwavelength catalog (Momcheva et al. 2016; Skelton et al. 2014), covering the EGS field and using the same crossmatching radius to avoid false matches. We found 93 additional  \ncounterparts, bringing the total number of sources with an associated optical / NIR photometry to 210. For the remaining 7 spectra, we didn\'t find a counterpart closer than 0.5", but their counterparts are returned when we considered a larger cross-matching radius (0 . 5\' < r < 1 . 2\'). For sources detected in the JWST + HST catalog, we didn\'t consider the additional photometry of the 3DHST catalog since most of these sources are undetected in photometric bands bluer than the HST bands (being at highz ), while the photometry at longer wavelengths than HST bands is already covered by JWST (the deepest in the near and mid-infrared).  \nThe SED fitting was performed considering two di ff erent parameter grids, reported in Appendix B, one for sources at z < 3 and the other for sources at z > 3. We used delayed star formation history (SFH) models for both redshift groups because they are able to reproduce both early-type and late-type galaxies, with an additional term that allows for a recent (and constant) variation of the star-formation rate (SFR) that can be in the burst or in the quench phase. We adopted stellar templates from Bruzual & Charlot (2003), and a Chabrier initial mass function (Chabrier 2003). We also include the nebular emission module that is extremely important to account for the contribution of emission lines in the broad-band photometry (Schaerer & de Barros 2012; Salvato et al. 2019), in particular for the low-mass and highz regimes, where emission lines can account for a consistent fraction of the wideband photometric flux. This module is computed by CIGALE based on a grid of userprovided parameters and in a self-consistent manner using a grid of Cloudy photoionization calculations Ferland et al. (2013). For the attenuation of the stellar continuum emission, we considered the dustatt\\_modified\\_CF00 module (Charlot & Fall 2000), which allows di ff erent attenuations for the young and old stellar populations. We also include dust emission in the IR following the empirical templates of Dale et al. (2014). The main di ff erences in the z > 3 grid with respect to the lowz one consist in the larger parameter space explored for the possible final starburst state of highz galaxies and in the lower metallicities and higher ionization parameters allowed in the stellar and nebular modules, according with recent JWST results (Endsley et al. 2023; Tang et al. 2023). Indeed, SFG at highz are observed to be more frequent in a bursty SF regime (Faisst et al. 2020; Dressler et al. 2023; Looser et al. 2023) and also, the gas metallicities are generally 0.5-1 dex lower than in the local universe (Curti et al. 2023b; Nakajima et al. 2023).  \nFor sources classified as AGN based on our NLAGN selection, as well as the BLAGN selected in Harikane et al. (2023), we included AGN modules in the SED fitting to account for the AGN emission. We employed the skirtor2016 module introduced in Yang et al. (2020), which is widely used in the community and has demonstrated reliability in studying various aspects of AGN (e.g., Mountrichas et al. 2022; López et al. 2023; Yang et al. 2023b). The SED produced by the AGN combines emissions from the accretion disk, torus, and polar dust. The accretion disk, responsible for the UV-optical emission at the central region, is parameterized according to Schartmann et al. (2005), with a typical delta value of -0.36. Photons from the accretion disk can be obscured and scattered by dust in the vicinity, within the torus and / or in the polar direction. Specifically, for the torus, the skirtor2016 module employs a clumpy two-phase model (Stalevski et al. 2016), based on the 3D radiative-transfer code SKIRT (Baes et al. 2011; Camps & Baes 2015). As our photometry does not cover the restframe mid-IR, we fixed the optical depth at 9.7 µ m at τ = 3. For the polar dust component, we used the Small Magellanic Cloud (SMC) extinction curve, recommended due to its preference in AGN observations (e.g.,  \nFig. 1: Stacked spectra of the final sample of NLAGN (red) and non-AGN (blue) derived as described in Sec. 2.3. We also marked the positions of some relevant lines.  \n<!-- image -->  \nBongiorno et al. 2012). The extinction amplitude, parameterized as E ( B -V ), is a user-defined free parameter for which we chose a typical value of E ( B -V ) = 0 . 04. Emission from the polar dust maintains energy conservation, assuming isotropic emission and a \'grey body\' model (Casey 2012). Finally, we allowed inclination values from 50 to 80 degrees and varied the AGN fraction (defined as the ratio between the AGN luminosity and the host galaxy luminosity between 0.15 and 2 microns) from 0.1 (weak AGN contamination) to 0.7 (dominant AGN emission).', '2.5. X-ray and radio stacking': 'To investigate the multiwavelength properties of the CEERS NLAGNselected using the diagnostic diagrams, we look at their counterparts in the X-rays and Radio images of the EGS field. The Chandra AEGIS-XD field is the third deepest X-ray field ever performed, with an exposure that reaches ∼ 800 ks. The X-ray observations and the related X-ray catalogue are described in Nandra et al. (2015). The X-ray catalogue contains 937 X-ray sources, and 553 of these sources (those with enough photon counts) also have an X-ray spectral analysis performed by Buchner et al. (2015). By cross-matching the CEERS MR catalog with the X-ray catalogue, we found 7 matches, involving sources at 0 . 5 < z < 3. The X-ray spectral analysis classified two of these sources as galaxies (CEERS-3060, CEERS3051), the other 5 (CEERS-2919, CEERS-2808, CEERS-2904, CEERS-2989, CEERS-2900) as AGN. In particular, CEERS2904, CEERS-2989, and CEERS-2919 are part of the new  \nlow-redshift BLAGN sample presented in Appendix A. Four out of the five X-ray AGN were selected as NLAGN by our spectroscopic selection, as we are going to present in Sec. 3. However, all the other 48 selected NLAGN do not show any indication of X-ray emission. Therefore, we decided to perform an X-ray stacking analysis of the NLAGN not X-ray detected using the publicly available code CSTACK v4.5 Miyaji et al. (2008). For each target, CSTACK provides the net (background-subtracted) count rate in the soft (0.5-2 keV) and hard (2-8 keV) bands using all the observations from the AEGIS-XD survey and the associated exposure maps. Since the survey is a mosaic, multiple observations at di ff erent o ff -axis angles can cover the same position. Due to the variation of the Chandra PSF with the o ff -axis angle, for each observation of an object, CSTACK defines a circular source extraction region with the size determined by the 90% encircled counts fraction (ECF) radius ( r 90) (with a minimum of 1"), to optimize the signal-to-noise ratio of the stacked signals. We set the background region for each source to be a 30 × 30 arcsec 2 area centered on the object, excluding the region around the object used to compute the net counts. Moreover, the code excludes the photon counts of the background circular regions around all the detected X-ray sources, with radii that depend on the net counts of the X-ray source. We derived the count rates in the soft band (0.5-2keV, SB), the band for which the detector is most sensitive and can, therefore, provide tighter constraints on the X-ray analysis. Then we converted the count rates into fluxes assuming an X-ray power spectrum with an intrinsic spectral  \nindex Γ = 1 . 9 and using the Chandra tool PIMMS 3 .  \nThe field targeted by the CEERS survey is also covered by 1.4GHz observations, the AEGIS20 described in Ivison et al. (2007). This radio survey was performed in 2006 with the Very Large Array (VLA) over an area of ∼ 0 . 75deg 2 and reaching, in the central region, a rms of ∼ 10 µ Jy. The resulting radio catalog (Ivison et al. 2007) contains 1123 individual radio sources, of which only two are part of the CEERS MR sample, i.e., CEERS-2900 and CEERS-3129, the first (that is also X-ray detected) showing the typical morphology of a radio-loud AGN. Both these sources were identified as AGN also by our selection, but all the other NLAGN do not have any radio counterparts. Therefore, we perform radio stacking analysis to investigate the radio statistical properties of the NLAGN population below the survey detection threshold. We applied a pixel-by-pixel median stacking, taking 30 × 30 arcsec 2 cutouts around the sources we wanted to stack. This method was proved (White et al. 2007) to be more robust (compared to the mean stacking, for example) towards systematic e ff ects (i.e. confusion) and also less a ff ected by possible high-flux density contaminants. Since the CEERS survey covers only a very small region of the radio image on which the rms is almost uniform, we do not weigh each radio cutout for the corresponding noise value in the stacking procedure. We also estimated the final rms of the stacking images using a median absolute deviation procedure, following Keller et al. (2024).', '3. Results': 'Here we present the result of the NLAGN selection performed on the sample of the 217 MR CEERS spectra with a secure redshift identification. The NLAGN selection was performed using emission line diagnostic diagrams.  \nIn all the diagrams, we plot both the observed data points and also the line ratios derived from the photoionization models described in Feltre et al. (2016) and Gutkin et al. (2016). These models were computed using the Cloudy code (Ferland et al. 2013) for SFG and AGN NL regions and for various gas metallicities, ionization parameters, dust content, and ISM densities, and considering a wide range of the parameters space (for the full grid of values covered by the parameter space we refer to Table 1 in Feltre et al. 2016). To allow a comprehensive enough coverage of the SFG models but to avoid physical conditions rarely (or never) found in the general populations of SFG in the local or highz Universe, we applied to these models the same cut in the parameter space as presented and discussed in Scholtz et al. (2023a). Through the work, photoionization models for AGN and SFG will be shown in red and in blue, respectively. We also mark with distinctive colours the seven sources that are X-ray detected (gold), the two radio-detected sources (green), and the eight sources that were selected as BLAGN at z > 4 . 5 by Harikane et al. (2023) (red). In each diagnostic diagram, the sources with magenta edges are those selected as NLAGN in that specific diagnostic.  \nIt is worth noting that the line fluxes involved in the diagnostic diagrams described in the next Sections are not corrected for the e ff ect of dust. This is because we are always considering ratios between lines close to each other, hence subjected to almost the same reddening, making the ratio insensible to the presence of dust. The few exceptions are discussed and justified. The acronyms used for the line ratios are reported in Tab. 1.', '3.1. Optical diagnostics': "In Fig. 2, we show the traditional BPT (Baldwin et al. 1981), the S2-VO87, and the R3O1 (Veilleux & Osterbrock 1987) diagnostics diagrams based on the R3-N2, R3-S2, and R3-O1 line ratios, respectively. The traditional demarcation lines between SFG and AGN provided by Kau ff mann et al. (2003) and Kewley et al. (2001) already proved to be way less e ff ective in selecting highz AGNcompared to the local universe (Scholtz et al. 2023a; Übler et al. 2023; Maiolino et al. 2023). Indeed, the lower metallicities of highz sources make [N ii ] (but also [S ii ] ) emission lines fainter, shifting the objects (AGN included) towards the left part of the BPT diagram. At the same time, the higher ionization parameter of the highz SFG (Cameron et al. 2023; Sanders et al. 2023; Topping et al. 2024), due to, on average, the presence of younger stars and lower metallicities compared to the local universe, moves the SFG towards higher R3 ratios, generating a large overlap between AGN and SFGs. Therefore, in the R3N2 and R3S2 diagnostics, we used the conservative demarcation lines provided in Scholtz et al. (2023a), derived considering the distribution of the photoionization models of Gutkin et al. (2016); Feltre et al. (2016) and Nakajima & Maiolino (2022). Since the R3O1 diagnostic diagram was not included in the analysis of Scholtz et al. (2023a), we followed the same fitting method to the photoionization models to find more conservative demarcation lines with respect to those presented in Kewley et al. (2001). We derived the following dividing line between the AGN and SFG population:  \nR3 = 2 . 5 + 2 . 65 O1 -0 . 15 . (1)  \nAs it is possible to see from the three plots, none of the BLAGN at highz are in the AGN region of the three diagnostics, based on the new demarcation lines, and only one would be selected considering the traditional demarcation lines in the R3S2 and R3O1 diagrams (is the same source, CEERS-1665).  \nThe five AGNs selected with the R3N2 diagram are all at z < 2 . 9. Three of them are X-ray-detected AGN (one is also radiodetected, i.e. CEERS-2900), and one is another radio-detected source (CEERS-3129). It is worth noting that even the X-ray source at the highest redshift (i.e. CEERS-2808 at z = 3 . 38), does not fall in the pure-AGN region of this diagnostic diagram. The R3S2 diagnostic diagram appears e ff ective in selecting AGN, also at a higher redshift with respect to the BPT. The new demarcation line provided in Scholtz et al. (2023a) partially overlaps with the traditional one proposed in Kewley et al. (2001). In this case, we select 21 AGN, six of which at z > 3, one at z = 5 . 27. None of the BLAGN is selected as AGN based on this diagnostic, while three X-ray sources and the two radio sources are confirmed as AGN also in this diagnostic.  \nAlso the R3O1 diagnostic diagram is more e ff ective in identifying NLAGN compared to the R3N2. In this diagram, we select 12 AGN, 7 at z < 3 (including 2 X-ray sources), and 5 at z > 3, one of these at z ∼ 6. We will further discuss the e ff ectiveness of this diagnostic and of the R3S2 in Sec. 4.1.  \nIn Fig. 3 we show the diagnostic based on the He2 vs N2 lines ratio. In this case, the demarcation line is the original one provided by Shirazi & Brinchmann (2012), which still holds even at highz , as also reported in Dors et al. (2024) and Tozzi et al. (2023). Overall, we detect He ii λ 4686 in seven sources: all except one of these are classified as AGN. None of the CEERS BLAGN show detection of the He ii λ 4686 line. In this diagnostic, there are also five sources that are selected as AGN only based on the N2 ratio. The last diagnostics exploiting rest-frame optical lines are the  \nFig. 2: Left: R3N2 diagnostic diagram (also called BPT). The gray points represent the parent sample of galaxies analyzed in this work, gold, green and red colors are used for X-ray detected sources, radio detected sources and the highz BLAGN reported in (Harikane et al. 2023). The NLAGN selected using this diagram are marked with magenta edges. In magenta and cyan, we show the line ratios derived from the stacked spectra of all the selected NLAGN (52 sources) and non-AGN sources. The dashed lines refer to three di ff erent demarcation lines, as labeled, the one in green is the more conservative demarcation line derived in Scholtz et al. (2023a). The blue and red shaded area represents the regions covered by the SFG and AGN photoionization models computed in Gutkin et al. (2016) and Feltre et al. (2016). The gray contours mark the distribution of SDSS sources (taken from SDSS DR7 Abazajian et al. 2009). In the lower-right corner are reported the median errors of the sample. Right: R3S2 diagnostic diagram (also called VO87) with the demarcation line originally presented in Kewley et al. (2001) (in black) and the new (more conservative) demarcation derived in Scholtz et al. (2023a). Bottom: R3O1 diagnostic diagram with the demarcation line presented in Kewley et al. (2001) (black dashed line) and the new one derived in this work (green solid line).  \n<!-- image -->  \ntwo diagnostics based on the O3Hg ratio and proposed in Mazzolari et al. (2024). Hereafter, we will refer with M1 to the O3Hg versus O32 diagnostic diagram and with M2 to the O3Hg versus Ne3O2 diagram. These diagnostics proved to be e ff ective in selecting those AGN characterized by high O3Hg ratios at a given ratio of O32 or Ne3O2, and were able to select NLAGN also at z > 6 (Mazzolari et al. 2024). The [O iii ] λ 4363 line is sensitive to the electron temperature of the ISM. The e ff ectiveness of these diagnostics is related to the fact that the average energy of AGN's ionizing photons is higher than that of young stars  \nin SFGs, because the AGN ionizing source (the accretion disk) produces a harder SED with respect to stars. Therefore, AGN can more e ffi ciently heat the gas, boosting the [O iii ] λ 4363 line. Using the two diagnostic diagrams reported in Fig. 4, we were able to select 15 distinct NLAGN, up to z ∼ 6. In the case of the left panel of Fig. 4, the O32 line ratio can su ff er from the effect of dust reddening due to the wavelength distance of the two lines involved. However, the e ff ect of dust attenuation on this diagnostic moves sources toward the right, without contaminating  \nFig. 3: He2N2 diagnostic diagram. The colors follow the same scheme as in Fig. 2  \n<!-- image -->  \nthe AGN-only region with SFGs, allowing us to select only pure AGN.", '3.2. UV diagnostic': 'In this section, we will focus on the diagnostic diagrams involving rest-frame UV lines (Mingozzi et al. 2024; Mascia et al. 2024; Scholtz et al. 2023a; Feltre et al. 2016). In particular, we considered the UV diagnostic diagram C3He2-C43 and the diagnostic diagrams involving the so-called high-ionization emission lines, i.e. N iv ] λ 1486, N v λ 1243, [Ne iv ] λ 2425.  \nThe C3He2-C43 diagnostic diagram reported in Fig. 5 allows us to select one single NLAGN (CEERS-613), whose selection is based on a clear detection of the He ii λ 1640 line, that places the source well into the AGN-dominated region according to the demarcation lines presented in Hirschmann et al. (2022). The detection of the UV lines involved in this diagram is challenging with only ∼ 50min of JWST exposure (the average on-source exposure time of the CEERS survey). Also in Scholtz et al. (2023a) the number of detections of these lines is low, even if the exposure time per target of the JADES survey was ∼ 8 times longer than the CEERS observations.  \nThe high-ionization emission lines are characterized by highphotoionization energies that can be produced more probably in AGN, due to their harder ionizing radiation, and therefore can be used as indicators of the presence of an AGN, even if hidden. In the diagnostics diagrams involving these lines, we base the identification of NLAGN on the position of the sources compared to the distribution of AGN and SFG photoionization models of Gutkin et al. (2016) and Feltre et al. (2016). In the top panel of Fig. 6 we show the diagnostic diagram involving the N iv ] λ 1486 emission line, which has an ionization potential of 47eV. This diagnostic allows us to select two NLAGN (CEERS-496, CEERS-1019), based on their extreme position with respect to the distribution of both SFG and AGN photoionization models. However, given their unclear detection of the He ii λ 1640 line in both these sources, and given the uncertainties in the extension of the SFG region in the diagnostic, we decided to mark these NLAGNs only as  \ncandidates. In particular, the source in the upper part of the diagram is CEERS-1019, whose AGN nature has already been discussed in multiple works in the literature (Mascia et al. 2024; Larson et al. 2023), some supporting the presence of an AGN and some discarding it (Tang et al. 2023). In the middle panel of the same figure is represented the diagnostic diagram involving the N v λ 1240 emission line (ionization potential of 77eV). In this case, we could select only one source with a N v λ 1240 detection, CEERS-23, that again we marked as a candidate due to the undetection of the He ii λ 1640 line. In the last panel of Fig. 6, we show the [Ne iv ] 2424 emission line diagnostic, whose ionization potential is 63eV. We detect the [Ne iv ] 2424 line in three di ff erent sources (CEERS-1029, CEERS-13061, CEERS-4210), and all of them occupy a region of the diagram covered only by the AGN models, even considering the upper limits in He ii λ 1640. In this diagnostic diagram, where the [Ne iv ] and [Ne iii ]lines are ∼ 1000Å apart one from the other, the dust correction would move the points towards the right, to even more AGN-extreme values.  \nFurthermore, we detect the [Ne v ] 3426 emission line (97eV of ionization potential) in one source (CEERS-8299, at z = 2 . 15) that we marked as AGN given the extremely high-ionization energy required to produce this line. Even if at highz it has been proposed that the [Ne v ] 3426 could also be associated with SF processes Cleri et al. (2023), it was always related to AGN activity at z < 3 Mignoli et al. (2013); Barchiesi et al. (2024).  \nOverall we selected 52 NLAGN among the initial 217 sources.', '3.3. Stack of the AGN and non-AGN samples': 'In each of the diagnostic diagrams reported in Sec. 3, we also report the line ratios of the stacked spectra of all the selected NLAGN and of the non-AGN selected sources, derived as presented in Sec. 2.3 and shown in Fig. 1. The two stacked spectra were then fitted to measure emission line fluxes using Qubspec , following the same procedure as for all the other single spectra and described in Sec. 2.2.  \nAs it is possible to see from the BPT (R3N2) diagram, the position of the stacked NLAGN and the non-AGN sources are very close together, with AGN having a slightly larger R3 line ratio. This clearly shows how the BPT diagram and its traditional demarcation lines are no longer useful in e ff ectively separating the AGNpopulation from SFG, probably even for relatively low redshifts ( z > 2). We will further discuss this point in Sec. 4.1. On the contrary, in the R3S2 diagnostic diagram (VO87), the line ratios of the stacked NLAGN spectrum clearly lie in the AGN region of the diagnostic, while the non-AGN one is in the SFGdominated region. The R3S2 line ratio seems to be still informative for the AGN selection also at (relatively) highz , as we will discuss in Sec. 4.1. The same applies to the R3O1 diagnostic diagram. As for the He2N2 diagram, we note that while the NLAGN stacked spectrum shows a clear detection of the He ii 4686 line, which places the final NLAGN stack clearly in the AGN region of the diagnostic, for the non-AGN sample the He ii λ 4686 line is not detected and the line ratios fall in the SFG region, as expected. This is also a strong point in favor of the goodness of our NLAGN selection since the He ii λ 4686 line was detected with high-enough S / N only in 5 / 52 of the NLAGN, 4 or them at z < 3. The fact that this line is clearly detected in the NLAGN spectral stack and that the stack line ratios fall in the AGN region of the diagnostic means that signatures of AGN emission are widely present among our NLAGN sample.  \n<!-- image -->  \nFig. 4: M1 and M2 diagnostic diagrams, firstly presented and discussed in Mazzolari et al. (2024). The colors follow the same scheme as in Fig. 2  \n<!-- image -->  \nFig. 5: C3He2 vs C43 diagnostic diagrams, selecting only one NLAGNdueto the di ffi culties in detecting rest-UV lines in highz galaxies with the short exposure times of the CEERS survey. The stacking line ratios and the average errors are not reported because of the poor statistics. The colors follow the same scheme as in Fig. 2. The demarcation lines are those defined in Hirschmann et al. (2022).  \n<!-- image -->  \nIn both the diagnostic diagrams involving the [O iii ] λ 4363 auroral line, NLAGN are characterized by a larger ( ∼ 0 . 3 dex) [O iii ] λ 4363 / H γ line ratio compared to the non-AGN, while the two have a similar O3O2 or Ne3O2 line ratios, meaning that the NLAGN selection is mainly driven by a stronger [O iii ] λ 4363 auroral line in AGN, as discussed in Mazzolari et al. (2024).  \nWe did not put the results of the stack in the rest-UV diagnostic diagrams. This is because in the case of the C3He2-C43 diagnostics, the He ii λ 1640 and C iv lines are available only for 33 / 155 non-AGN and 7 / 52 NLAGN, and both these lines are not clearly  \ndetected in none of the two stacked spectra. This is expected given the faintness of these lines and the observing time of the CEERS survey, and indeed this diagnostic was able to identify only 1 NLAGN. The same goes for the high-ionization emission line diagnostics: none of the high-ionization emission lines involved in the diagnostics in Fig. 6 is clearly detected in our stack.', '4. Discussion': 'The IDs and the main physical properties (that will be presented and discussed in the next Sections) of all the selected 52 NLAGN are reported in Table C.1.', '4.1. Comparison of AGN selection methods': 'In this section, we discuss the e ff ectiveness of the di ff erent diagnostic diagrams reported in Sec. 3. For the discussion below, the term e ff ectiveness refers to the ability of a diagnostic diagram to e ffi ciently select (i.e. isolate in the diagram) NLAGN among all the considered sources.  \nAs presented in the top panel of Fig. 7, most of the NLAGN are selected based on only one single diagnostic diagram (35 / 52, the 65%), 13 are selected in two di ff erent AGN diagnostics, while 4 are selected based on more than two diagnostics diagrams. The fact that most of the NLAGN are selected based on one single NLAGN diagnostic is not surprising. The NLAGN diagnostic diagrams we used for our selection involve emission lines that cover a wide wavelength range (from rest-UV to rest-optical), over which the spectral features of sources at 1 ≲ z ≲ 9 can vary a lot depending on many parameters (metallicities, stellar population in the host galaxy, radio or X-ray emission, etc.). Given this, di ff erent NLAGN diagnostic diagrams are intrinsically sensitive to di ff erent AGN properties and, in turn, can become ineffective (and therefore less useful in separating AGN from SFG) under di ff erent conditions.  \nLooking at the lower panel of Fig. 7, we see the distribution of the sources selected by the di ff erent diagnostic diagrams with respect to their redshift and their selection diagram. The diag-  \n<!-- image -->  \n<!-- image -->  \nFig. 6: From top to the bottom: C3He2 vs N4C3, C3He2 vs N5C3, C3He2 vs Ne4C3 diagnostic diagrams. The stacking line rations and the average errors are not reported because of the poor statistics. The colors follow the same scheme as in Fig. 2  \n<!-- image -->  \nnostic diagram that selected the larger number of the AGN is the R3S2, in particular at z < 3, but with a non-negligible number of NLAGN also selected at z ∼ 5. The e ff ectiveness of the R3S2 (but also of the R3O1) diagnostic diagram in the lowmetallicity (and therefore highz ) regime was already pointed out in some recent works investigating the e ff ectiveness of traditional NLAGN diagnostic diagrams to select AGN among lowmetallicity dwarf galaxies (Polimera et al. 2022). In particular, they show that the S2 and the O1 line ratio are less metallicity sensitive and more successful in identifying AGN in these dwarf environments (more similar to those at highz ) than the R3N2 diagnostic. The lower e ff ectiveness of the R3N2 at low metallicities (hence at high redshift) is an obvious consequence of the fact that the nitrogen abundance scales about quadratically with metallicity (at Z > 0 . 1 Z ⊙ ), hence the [NII] / H α ratio drops strongly, even if irradiated by the energetic radiation of an AGN. We also notice that [N ii ] and [S ii ] get redshifted out from the reddest grating of the spectra at z ∼ 6 . 7, while the [O i ] gets redshifted out at z ∼ 7.  \nIn general, at z < 3 the most e ff ective AGN selection techniques are the R3S2, N2He2, and R3N2, while the large majority of the AGN at z > 3 are selected based on the auroral line diagnostics (both M1 and M2 ), or based on the detection of highionization emission lines. This supports the picture in which the traditional AGN diagnostic diagrams (in particular the R3N2) become less e ff ective at highz , mainly due to metallicity-related e ff ects, while the detection of high-ionization emission lines and the new [O iii ] λ 4363-based AGN diagnostics prove to be e ff ective in selecting AGN also in the early Universe, reinforcing the results pointed out by Maiolino et al. (2023), Übler et al. (2023) and Scholtz et al. (2023a).  \nThe spectra of the NLAGN selected at z > 6 (together with the main spectral features that lead to the NLAGN classification) are presented in Appendix D.', '4.2. Selection of X-ray and radio sources in the diagnostics': 'In this section, we want to summarize the results related to the X-rays and radio sources involved in our analysis. Among the seven X-ray sources with a spectrum in the CEERS MR sample, two sources (CEERS-3050 and CEERS-3061) are at z < 0 . 5, and therefore, the rest-frame optical and UV lines are not available in JWST spectra. These sources were classified as SFG by the Xray spectral analysis performed in Buchner et al. (2015). Among the other five X-ray sources, four are selected as NLAGN in at least one of the diagnostic. In particular, the one at highest redshift (CEERS-2808, z = 3 . 384) is selected as NLAGN only in the R3S2 diagnostic diagram and not in the R3N2 (considering the more conservative demarcation line reported in Scholtz et al. 2023a). The only three X-ray sources selected as NLAGN in the BPT diagram are CEERS-2919, CEERS-2904, and CEERS2900, all at z ≲ 2, the first two also showing a broad H α emission line (see Appendix A). The only X-ray source not selected in any of the diagnostics is CEERS-2989, at z = 1 . 433, whose spectrum shows only clear H α and [N ii ] detections, and therefore, we could not define the R3 line ratio to place it in the above-mentioned diagnostics. It is worth noting that the lack of [O iii ] λ 5007 and H β detections in this source is probably due to high obscuration levels. Considering the analysis in Sec. 4.6, we found a lower limit to the value of AV ∼ 6 mag. The large AGN obscuration of this source is further supported by the Comptonthick obscuration level derived by the X-ray analysis performed in Buchner et al. (2015). However, this source shows a faint broad H α component, as reported in Fig. A.1.  \nFig. 7: Summurizing plots of the NLAGN selection. Upper: NLAGN counts in the di ff erent redshift bins, colorcoded by the number of diagnostics in which each NLAGN has been selected. Lower: Distribution of the NLAGN according to the di ff erent diagnostic diagrams presented in Sec. 3, as labeled.  \n<!-- image -->  \nThe two radio-detected sources are CEERS-2900 (that is also X-ray detected) and CEERS-3129, both selected in the R3N2 diagram as well as in the R3S2 one. They also both show strong [N ii ] emission, in particular CEERS-3129, probably indicative of a shock (Allen et al. 2008; Nesvadba et al. 2017). Furthermore, CEERS-3129 shows a significant broad H α component, but no indication of X-ray emission, as we will further explore in Sec. 4.9.', '4.3. Comparison with previous CEERS AGN selections': 'Calabrò et al. (2023) attempted to select AGN among the CEERS sources with a MR spectrum using near-infrared emission line diagnostics. To do so, they restricted the redshift range of the sources at 1 < z < 3, therefore considering only 65 single sources. Using the R3N2 and R3S2 diagnostic diagrams, the authors selected 8 NLAGN that were classified as NLAGN also based on at least one NIR diagnostic, i.e. CEERS-2919, CEERS-3129, CEERS-2904, CEERS-2754, CEERS-5106, CEERS-12286, CEERS-16406, and CEERS-  \n17496. The first three were marked as BLAGN, as we also found in Appendix A.1. Five of the sources selected as NLAGN by Calabrò et al. (2023) are also selected in our work, while the other three sources were not selected because of the more conservative demarcation lines used in the R3S2 and R3N2 diagnostics or because the [S ii ] line was not considered detected with enough significance by our fit. The authors also selected 5 NLAGN using near-infrared diagnostic diagrams that were classified as SFG based on the optical diagnostic diagrams, i.e. CEERS-2900, CEERS-8515, CEERS-8588, CEERS-8710, CEERS-9413. Among these, the only one that is classified as NLAGN also in our selection is CEERS-2900; the other three were selected as SFG also by our optical diagnostics (even if CEERS-8588 shows a tentative [Ne v ] line emission, but we conservatively decided to mark it as a non-detection).  \nIn Davis et al. (2023) the authors investigate the presence of extreme emission-line galaxies (EELG) at 4 < z < 9 using JWST NIRCam photometry in the CEERS program. They used a method to photometrically identify EELGs with H β + [O iii ] or H α emission of observed-frame equivalent width > 5000Å. Among the photometrically selected EELGs there are 39 sources with a NIRSpec PRISM or MR spectrum, 25 with a match in our MR parent sample. Among these, 6 are selected as NLAGN in our work, i.e., ∼ 25%, supporting the non-negligible AGN contamination in the photometric selection of this kind of sources, as already shown also by other works (Amorín et al. 2015).', '4.4. AGN prevalence': 'In Fig. 8, we show the fraction of the selected NLAGN among the CEERS MR sample. In particular, we consider as parent sample all the galaxies with a MR spectrum and with a secure redshift (217 sources). Then we divided the distribution into four redshift bins of ∆ z = 2 between z = 0 and z = 9, and for each bin, we computed the fraction of AGN compared to the parent sample. The number of sources in the di ff erent redshift bins is 122, 85, 59 and 49, going from the lower to the higher redshift bin. We derived an almost constant fraction of AGN among the CEERS MRsources ∼ 20%. We remind that this fraction do not represent intrinsic AGN fractions, given the fact the the original selection function of the spectroscopic survey is extremely hard to derive, but just a reference for the sample taken into account. This result agrees well with what was found for the NLAGN selection in the JADES survey by Scholtz et al. (2023a), where, however, the M1 and M2 and the R3O1 diagnostics diagrams were not involved in the AGN selection. Given the di ff erent sensitivities reached by the CEERS and JADES surveys, one would probably expect a lower fraction of NLAGN selected in the CEERS sample since, in most cases, the AGN selection is based on the detection of faint emission lines. At the same time, however, as we are going to show in Sec. 4.7, the median bolometric luminosity of the NLAGN in the CEERS sample is ∼ 1 dex higher compared to those selected in JADES, and so the fact that the targets are brighter partially compensate for the shorter exposure times.', '4.5. Velocity dispersion': 'In Fig. 9 we show the distribution of the intrinsic narrow line FWHM of the [O iii ] λ 5007 emission line compared to the redshift of the sources. In particular, we considered only sources with the [O iii ] λ 5007 line detected at S / N > 5. To estimate the intrinsic FWHM, the observed FWHM retrieved by the fit was de-  \nFig. 9: Redshift distribution of the intrinsic [O iii ] λ 5007 line FWHM,resulting from the line-fitting procedure and subtracting the instrumental FWHM. On the left, we also report the median values of the FWHM of NLAGN (magenta), non-AGN (cyan) and of the global population (black) in five di ff erent redshift bins. Errors are derived using a bootstrap procedure. There is no significant trend of the FWHM of the sources with redshift. On the right, we report the histogram of the NL-FWHM distribution for AGN (red) and non-AGN (blue).  \n<!-- image -->  \nFig. 8: Fraction of the spectroscopically selected NLAGN with respect to the parent sample in this work (CEERS, in red) and in the JADES survey (green) (program ID 1210&3215 Scholtz et al. 2023a) in di ff erent redshift bins. The errors account for the statistical uncertainties and are computed considering a Poissonian noise.  \n<!-- image -->  \nnvolved by subtracting in quadrature the instrumental resolution of the grating at the observed wavelength of the [O iii ] λ 5007 line. The instrumental velocity resolution was derived from the [point\\_source\\_lsff290lp\\_g395m\\_QD1\\_i185\\_j85.csv] line spread function file, which was calculated from the instrument model (Ferruit et al. 2022b), assuming a point-source geometry and a target located in the first MSA quadrant, at the centre of shutter (i,j) = (185,85); this procedure is described in de Graa ff et al. (2024). The median value of the instrumental resolution is ∼ 160km / s.  \nThe lower and upper boundaries of the intrinsic FWHM distribution are limited by the prior on the width of the line given to Qubespec , i.e. 200km / s < FWHM < 700km / s. None of the sources, after the subtraction of the instrumental resolution, shows a negative FWHM, but there is a non-negligible number of sources with an FWHM < 200km / s, meaning that in these cases we are really detecting emission lines at the limits of JWST resolution. Indeed, the cut in S / N and a careful visual inspection confirm beyond any doubt that these lines are real, and, actually, such narrow FWHM are expected given the trend of decreasing host galaxy stellar mass with redshift and given the fact that with JWST high-resolution spectrosocpy were recovered FWHM up to ∼ 100km / s (Maiolino et al. 2023). On the other hand, there are six sources with an intrinsic FWHM > 400 km / s. Four out of these six were classified as AGN using the diagnostic diagrams discussed above; in particular, three of these NLAGN are also low-redshift BLAGN reported in Fig. A.1. Among the analyzed spectra, we did not find any significant residual from the fit of the narrow [O iii ] λ 5007 line that could be indicative of the presence of an outflow component.  \nIn Fig. 9, we also report the median values of the FWHM of the NLAGN population and of the non-AGN in five equally spaced redshift bins. The distribution of AGN and non-AGN, considering the errors, do not di ff er significantly from the other in any of the redshift bins. We also perform the KolmogorovSmirnov (KS) test on the global marginal distributions in FWHM of the two populations (histogram on the right panel), finding a p-value = 0 . 62, which does not point towards di ff erent parent  \nsamples of the two distributions. This indicates that the NLAGN we spectroscopically selected among JWST spectra do not significantly impact their host-galaxy ISM, contrary to what was found in other studies on NLAGN samples, where, however, the NLAGN were selected based on other AGN activity tracers. For example, in the X-ray selected AGN sample of the KASHz survey, investigating sources at Cosmic Noon, (Harrison et al. 2016) found that ∼ 50% of the targets have ionized gas velocities indicative of gas dominated by outflows and / or highly turbulent material, with [O iii ] λ 5007 FWHM ≥ 600km / s. We will further discuss the AGN impact on the sources studied in this work in the next sections.', '4.6. Obscuration': 'In Fig. 10, we show the distribution of the AV values obtained from the Balmer line decrement. In particular, to derive the AV we considered the Small Magellanic Cloud (SMC) attenuation law (Gordon et al. 2003) for sources at z > 3 and the Calzetti et al. (2000) attenuation law for sources at z < 3. While the Calzetti et al. (2000) attenuation law has been extensively used in the lowz Universe to account for the e ff ects of dust, the choice of the SMC attenuation law is more appropriate for the highz Universe, where galaxies are smaller and more compact than in the local Universe (Ono et al. 2023). In particular, we select only those sources that have both H α and H β detected. We assumed CASE B recombination, i.e. an intrinsic H α / H β ratio of 2.86 4 . We also considered sources with upper limits in H β to derive lower limits in the AV . The AV is computed in correspondence to the H α emission line.  \nWe note that a small number of galaxies in Fig. 10 scatter to either surprisingly high values of AV or else negative values, mean-  \nFig. 10: Redshift distribution of the inferred values (using Balmer decrement) of AV in correspondence of the H α line for sources with detected H α and H β lines. For sources with upper limits on H β we derived lower limits on AV . On the left, we also report the median values of AV for NLAGN (magenta), nonAGN (cyan) and for the global population (black) in four different redshift bins. Errors are derived using the bootstrap procedure. On the right, we report the histogram of the AV distribution for AGN (red) and non-AGN (blue).  \n<!-- image -->  \ning an H α / H β line ratio less than the dust-free minimum value of 2.86. Even if sources with a dust-free H α / H β line ratio lower than CASE-B recombination have also been reported recently in the literature (Scarlata et al. 2024; Yanagisawa et al. 2024; McClymont et al. 2024), there is the possibility that a small fraction of these outliers are due to remaining systematics in the NIRSpec grating-to-grating flux calibration, i.e. when H β and H α are measured in di ff erent gratings. A similar result was indeed also observed in Shapley et al. (2023) on the same sample analyzed here. Even if present, these calibration issues do not a ff ect our NLAGN selection, because the line ratios of the diagnostics presented above involve lines close to each other, and so generally in the same grating.  \nIn Fig. 10, we also plot the median value of the obscuration considering four di ff erent redshift bins and taking separately the two populations of NLAGN and sources not identified as AGN. We did not consider for the median values the upper limits in AV . We did not find a significant evolution of AV with redshift. We also note that the AGN population is characterized, in the lower redshift bin (1 < z < 2 . 5), by a ∼ 0 . 7mag higher obscuration. At z < 2 . 5 the average NLAGN obscuration is 1.24 mag compared to the 0.55 mag of non-AGN. On the contrary, when the whole NLAGN and non-AGN populations are taken into account, the average value of the obscuration across all redshifts is very similar, around 0.5 mag.', '4.7. Bolometric luminosities': 'In this section, we investigate the bolometric luminosities of the NLAGN selected in this work. The way to compute the AGN bolometric luminosity is not unique, and it can be done starting from the X-ray luminosity, the luminosity of the BL emission or the UV continuum emission determined by the accretion disk. However, in our case, the majority of the sources are not X-ray  \ndetected, they do not have a BL emission, and their continuum is generally undetected. Therefore to estimate the bolometric luminosities, we rely on the dust-corrected narrow line fluxes of the H β line, using the calibrations reported in Netzer (2009). These fiducial Lbol for the sample of NLAGN (with available H β line) are reported with red squares in Fig. 11. In the same figure, we also report, with a fainter marker, the value of Lbol estimated from the same line fluxes but with the calibration used in Scholtz et al. (2023a) and taken from Hirschmann et al. (in prep). In this second case, the bolometric luminosity depends quadratically on the luminosity of the H β line, while the Netzer (2009) calibration is linear, determining a di ff erence in the estimated Lbol that can go up to ∼ 1 dex (on average the bolometric luminosities computed using Hirschmann et al. calibrations are 0.8 dex lower). To verify the reliability of our fiducial values of Lbol we also considered the bolometric luminosity calibrations derived in Lamastra et al. (2009) where the NLAGN bolometric luminosities are derived from the dust corrected [O iii ] λ 5007 line. The Lbol computed using the calibration in Netzer (2009) and those computed using the calibrations in Lamastra et al. (2009) agree well, with a median discrepancy of only ∼ 0 . 25 dex.  \nHowever, It is worth noting that all these calibrations assume that the lines used to derive Lbol are dominated by the AGN emission. This assumption is not necessarily true for the whole sample of NLAGN, and therefore, our Lbol should be generally taken as upper limits.  \nFor the BLAGN at z ≤ 2 presented in Fig. A.1, we computed the bolometric luminosities considering the same relation used in Harikane et al. (2023) to determine the bolometric luminosities of the BLAGN at z > 4 . 5 of this sample, i.e the bolometric luminosity calibration derived in Greene & Ho (2005) from the broad H α emission.  \nIn Fig. 11, we compare the distribution of Lbol of our sample with the AGN bolometric luminosities taken from the literature. In particular, we report AGN bolometric luminosities derived both from JWST spectroscopic studies and from pre-JWST surveys. Given the bolometric luminosities of z > 3 AGN detected before the advent of JWST, it is clear that we are now able to sample a completely new regime in the luminosity-redshift space. Comparing the bolometric luminosities of our sample with those of the NLAGN selected sample from Scholtz et al. (2023a), we note that our targets are on average ∼ 1 . 5 dex more luminous considering our fiducial calibration, but still more luminous even considering the luminosities derived with the calibration of Hirshman et al. (in prep). On the opposite, the AGN luminosities of our sample are comparable, in the same redshift range, with the distribution of Lbol derived from multiple samples of BLAGN detected with JWST.', '4.8. Host Galaxies Properties': 'In Fig. 12, we show the results from the SED-fitting performed on the whole sample of 217 sources as described in Sec. 2.4. In particular, we compare the trend with redshift of the ratio between the SFR derived from the CIGALE SED fitting and the one obtained from the main sequence (MS) reported in Popesso et al. (2023) at the stellar mass ( M ∗ , obtained from the fit) and redshift of each source. We note that sources at z < 4 are generally distributed almost symmetrically with respect to the MS, with the median value of log SFR / SFRMS ∼ 0 . 1. On the contrary, at z > 4, sources appear to be systematically above the corresponding MS, with a median value of log SFR / SFRMS ∼ 0 . 4, i.e. SFRs 2-3 times larger than the respective MS SFR. Sources with larger SFRs are also the sources with the lower M ∗ , some  \nFig. 11: Bolometric luminosities versus redshift of the sample of NLAGN selected in this work (red squares) compared to the bolometric luminosities of other AGN samples selected using JWST spectroscopic observations or pre-JWST, as labeled. The darker red squares represent the baseline bolometric luminosities, derived using Netzer (2009) calibration, while the fainter red squares show the values of the bolometric luminosities obtained using the same calibration adopted in Scholtz et al. (2023a). The compilation of JWST selected BLAGN includes the sources taken from Maiolino et al. (2023); Harikane et al. (2023); Matthee et al. (2023); Übler et al. (2023); Kocevski et al. (2023). SDSS BLAGN at z > 3 (light-blue crosses) are taken from Wu & Shen (2022). AGN from the KASHz and SUPER surveys at Cosmic Noon (grey and red gold crosses) are taken from Harrison et al. (2016) and Kakkad et al. (2020), respectively. QSOs samples at Epoch of Reionization are taken from Zappacosta et al. (2023) (green crosses, HYPERION sample), and Mazzucchelli et al. (2023) (dark-blue crosses, XQR-30).  \n<!-- image -->  \nof them reaching log M ∗ ≲ 8. This means that the highz galaxies analyzed in this sample seem to have, on average, a higher MS normalization, being less massive and more star-forming than expected from the MS. Di ff erent works, taking advantage of JWST spectroscopy, already showed that highz galaxies are frequently in a state of intense or bursty SF (Dressler et al. 2023; Looser et al. 2023; Endsley et al. 2023), probably driven by a higher SF e ffi ciency related to the lower metallicities of highz galaxies. However, another possibility that can determine this apparent bursty behaviour in our sample is a selection e ff ect. Indeed, given that we are investigating a spectroscopic sample, we are probably more biased towards high SFR, in particular at high-z.  \nFor sources not selected as AGN, we also compared the SFR inferred from CIGALE to the values obtained from the H α line (using the measured dust-corrected H α luminosity and the relations reported in Shapley et al. 2023). On average, we find a good agreement, with log SFRH α = 0 . 7 log SFRSED -0 . 1 with 0.25dex of scatter.  \nThe AGN distribution in Fig. 12 is in agreement with the distribution of the other sources not selected as AGN: considering  \nthe median distribution of the ratios of the two SFRs, even in di ff erent redshift bin, AGN and SFG are indistinguishable, as already found by other works (Ramasawmy et al. 2019). The AGN quenching e ff ect on the host galaxy SF is still a largely debated topic (Bugiani et al. 2024; Man & Belli 2018; Beckmann et al. 2017; Scholtz et al. 2018), and in this case, we do not note a negative impact of the AGN feedback on SF in the host galaxy. This finding is also in line with recent studies based on various cosmological simulations, according to which star formation quenching is not primarily driven by the instantaneous AGN activity but the integrated black hole accretion (as traced by black hole mass Piotrowska et al. 2022; Bluck et al. 2023; Scholtz et al. 2024). The AGN contribution to the final SED is measured in CIGALE by the parameter fAGN , which corresponds to the fraction of the AGN luminosity with respect to the galaxy one in the rest-frame 0.1-2 µ m. As expected, given the NLAGN nature of our sources, for most of the NLAGN, the fit returned a fAGN < 0 . 5 according to the scenario, already discussed in Sec. 4.5 and Sec. 4.6, that the AGN activity of the selected NLAGN is significantly buried by the host galaxy, in particular in the rest-frame optical part of the SED traced by the available photometry. This scenario, and the absence of a significant impact of the AGN activity over the host galaxy properties, is even more supported by the fact that we did not find relevant signatures of outflows in our spectroscopic analysis, in particular in the highz galaxies.  \nFrom the NLAGN SED-fitting, we also derived the AGN bolometric luminosities (sum of the disk emission plus the one reprocessed by the tours). However, due to the limited photometric range (the reddest filter is F770W for sources with JWST photometry and IRAC4 for sources with 3D-HST photometry), in most of the cases, we were not able to explore the rest-frame MIR NLAGN emission and the AGN bolometric luminosity is usually largely unconstrained. By selecting only those sources with a reliable bolometric luminosity from the SED-fitting, and comparing these values with the Lbol estimated in Sec. 4.7, we found that the median distributions agree well: the median value of the bolometric luminosity from the H β line is ∼ 0.23dex larger than the one derived from the SED-fitting, but the scatter goes up to ∼ 1 dex.', '4.9. X-ray weakness': 'As described in Sec. 2.5 we performed a detailed analysis of the X-ray and radio counterparts of the selected NLAGN. Four out of five of the X-ray sources classified as AGN by the Xray analysis in Buchner et al. (2015) are also classified as AGN by our NLAGN diagnostics. All the other 48 NLAGN do not show any X-ray counterpart. Therefore, we decided to perform an X-ray stacking analysis on our sample, using CSTACK as described in Sec 2.5. In particular, we decided to divide the sample of NLAGN in two redshift bins, equally populated, using z = 4 . 5 as the dividing threshold. We also include in our analysis the BLAGN selected at z > 4 . 5 in CEERS by Harikane et al. (2023), since none of them show any indication of X-ray emission and to perform a more complete analysis on the AGN sample among the CEERS MR spectra. We did not stack the sample of lowz BLAGN presented in Appendix A because 3 out of 4 of these sources are X-ray detected (except CEERS-3129, which will be discussed later). The median redshifts of the three AGN samples are 2.37 for the low-redshift NLAGN, 5.50 for the highz NLAGN, and 5.43 for the highz BLAGN sample. In Fig. 13, we show the stacking maps in the SB and HB for the two NLAGN redshift bins and for the BLAGN, respectively. Given the me-  \nFig. 12: Redshift distribution of the ratio between the SFR derived from the SED-fitting and the SFR computed from the MS relation derived by Popesso et al. (2023) at the redshift and M ∗ of each source. We plot AGN and non-AGN sources with stars and circles, respectively. The sources are color-coded based on the stellar mass, as derived from the SED-fitting.  \n<!-- image -->  \ndian redshift of the samples, and considering the SB as the reference observing band since it provides the deepest constraint, we are investigating, on average, the following rest-frame X-ray energy bands: ∼ 1.7-6.5 keV for the lowz NLAGN sample and ∼ 3 . 5 -13keV for the other two samples. The stacking analysis did not reveal any X-ray detection in any of the sub-samples. This is quite surprising given the rest-frame energy range tested and the depth of the X-ray observations. To check whether the non-detections in the stacking of the NLAGN were due to possible galaxy contamination in the NLAGN sample, we also performed the same stacking but considering only NLAGN selected in more than two diagnostics diagrams, but again, the X-ray analysis did not reveal any detection.  \nTherefore, we wanted to test if such X-ray non-detections would be compatible or not with the expected X-ray luminosities of these objects.  \nWeused the Lbol -L2 -10keV luminosity relations derived in Duras et al. (2020) to compute the expected X-ray luminosities given the baseline dust-corrected bolometric luminosities computed in Sec. 4.7 for our sample of NLAGN. For the BLAGN, instead, we used the bolometric luminosities computed in Harikane et al. (2023) using the H α broad emission. The comparison between the expected X-ray luminosities and the upper limits derived from the stacking is shown in Fig. 14. For all the AGN, the upper limits in their observed X-ray luminosities are largely below the expected X-ray luminosities, posing severe constraints on their X-ray production and emission. The X-ray deficit is ∼ 1 . 3 dex for BLAGN and for the sample of NLAGN at z > 4 . 5, and is ∼ 2 dex for the NLAGN at z < 4 . 5. The X-ray deficit of this last sample is particularly surprising, given the fact that most of these lowz NLAGNwere selected using the traditional BPT and VOT diagnostic diagrams, which are not expected to fail the NLAGN selection at lowz .  \nWe further check that even taking the bolometric luminosities derived using the calibration of Hirschmann et al. in prep. (shown as faint red squares in Fig. 11) the results remain almost unchanged, with the median expected X-ray luminosities of the two NLAGN samples decreasing only of ∼ 0 . 2 dex.  \nIn Fig. 14 we also show the distribution of the X-ray detected  \n<!-- image -->  \n<!-- image -->  \n<!-- image -->  \n<!-- image -->  \n<!-- image -->  \nFig. 13: 30" × 30" cutouts of the X-ray stacking image in the observed SB (0.5-2keV) and HB (2-8keV) of the three samples taken into account. From the top to the bottom: BLAGN, NLAGN at z > 4 . 5, NLAGN at z < 4 . 5. None of the samples show a detection in either bands.  \n<!-- image -->  \nsources in our MR spectroscopic sample together with the position of their X-ray stack. In particular, for each X-ray source, we plot with a diamond the observed X-ray luminosity derived from their X-ray flux assuming Γ = 1 . 9, namely applying the same procedure as was done for the stack of the other sources. As expected, X-ray sources whose spectral analysis revealed larger column densities are on the left of the 1:1 relation, with a deviation up to ∼ 2 dex for CEER-2989, whose spectral analysis revealed a column density of log( NH / cm -2 ) ∼ 25. This is because the spectral index Γ = 1 . 9, does not properly account for the harder spectrum of these heavily obscured sources. For each X-ray source, we also plot with circles the intrinsic, absorption corrected, X-ray luminosity derived in Buchner et al. (2015), which generally reduces the deviation from the 1:1 relation, especially if we take into account the large uncertainties on the intrinsic X-ray luminosities of the most obscured X-ray AGN. The same applies to the position of the stack of these Xray sources: when we considered the observed X-ray luminosity (derived from the X-ray stacking) the point slightly deviates from the median expected X-ray luminosity, but if we correct  \nFig. 14: The results coming from the X-ray stacking show a significant X-ray weakness of all three samples of NLAGN at z < 4 . 5, NLAGN at z > 4 . 5, and highz BLAGN. Left: expected X-ray luminosity versus observed X-ray luminosity (in the 2-10keV band) of the three AGN samples we used for the stacking, as labeled. We also plot the sources in the CEERS MR sample with an Xray detection color-coded by their obscuration level, as derived from the X-ray spectral analysis (Buchner et al. 2015). Diamonds refer to observed X-ray luminosities, while circles refer to the intrinsic X-ray luminosities derived from the X-ray analysis. Errors bars mark the error on the intrinsic X-ray luminosities of the sources reported in Buchner et al. (2015). The result from the X-ray stacking of these X-ray detected sources is reported as a gold diamond, while the gold circle considers the median of the intrinsic X-ray luminosities of the X-ray sources. The dashed lines correspond to the shift from the observed to intrinsic X-ray luminosities. In cyan, we report the z = 1 . 037 BLAGN CEERS-3129, presented in Appendix A. Right: ratio between the mean bolometric luminosity of the three AGN samples (derived using the values computed in Sec. 4.7) and the observed X-ray luminosity upper limits versus the mean bolometric luminosities. The orange line shows the reference L 2 -10 keV -LBOL relation derived by Duras et al. (2020) and used to derive the expected X-ray luminosity of the sources. The empty hexagons represent the lower limits derived from the X-ray stack of the JWST selected BLAGN (red) and NLAGN (green for z > 3 and blue for z < 3) on the CDFS and CDFN (Maiolino et al. 2024a).  \n<!-- image -->  \nfor the absorption the X-ray luminosities (considering the median of the intrinsic X-ray luminosities on the x-axis), then the golden circle perfectly aligns with the median expected X-ray luminosity of these sources.  \nThe same conclusions about the di ff erent samples can also be drawn by looking at the right panel in Fig. 14 where we compare the position of the sources with respect to the X-ray-bolometric luminosity relation of Duras et al. (2020). In the plot on the right we also show the lower limits derived in Maiolino et al. (2024a) from the X-ray stacking analysis performed on JWST selected BLAGN and NLAGN on the CDFS and Chandra Deep Field North (CDFN, Xue et al. 2016).  \nIn both figures, we also show in cyan the position of the peculiar source CEERS-3129. This is a BLAGN at z = 1 . 037 (whose broad H α component is shown in AppendixA), it is not detected in the X-ray image and shows an X-ray deficit of ∼ 2 dex. This source is also characterized by a consistent dust obscuration: from the Balmer decrement derived in Sec. 4.6 we found AV = 2 . 27. Since the broad H β component is not detected and its upper limit would return an extremely large AV , we assumed for the dust correction of the broad H α emission (and therefore for the bolometric luminosity) the value of AV derived from the NLR. However, this implies that the bolometric luminosity of CEERS-3129 might be underestimated and, consequently, also its expected X-ray luminosity and the amount of its X-ray weak-  \nConsidering the dust-corrected bolometric luminosity, the lower limit to the X-ray weakness of CEERS-3129 is ∼ 2 dex. Assuming that these sources are really AGN, the two possible scenarios that can justify such a lack of X-ray emission are:  \n- -Obscuration coming from large column densities, larger than the CTK limit (log( NH / cm -2 ) > 24).\n- -An intrinsic X-ray weakness due to a possible di ff erent accretion disk / corona structure. This can determine, for example, a larger ratio between optical and X-ray fluxes due to a lower e ffi ciency of the corona in producing X-ray photons.\n- -A combination of the two possibilities above  \nYue et al. (2024) analyzing a sample of so-called \'Little Red Dots\' (LRD) showing clear AGN signatures (as the detection of a broad H α component) and selected on various fields covered by JWST imaging and spectroscopy, found a similar result. The amount of the X-ray weakness of the LRD is comparable to what we found in this work for the sample of BLAGN at highz , while they did not investigate the population of NLAGN. In Yue et al. (2024), the authors suggest an intrinsic X-ray weakness as a possible origin of this discrepancy or a wrong AGN classification of these sources; in the latter case, the broad H α component might be due to fast galactic outflows (with velocities ∼ 1000km / s). In our case, however, we did not detect any signature of any outflow component in the forbidden lines of the BLAGN. More evidence  \nand strong arguments against the outflow scenario have been presented by Juodžbalis et al. (2024a).  \nAlso Maiolino et al. (2024a), considering a large sample of BLAGN and NLAGN spectroscopically selected in the JADES survey over the Chandra Deep Field South (CDFS, with 7Ms of Chandra observations Liu et al. 2017) show that almost all the AGN discovered by JWST lack any X-ray detection, even in the stack. In this work, the authors investigated di ff erent possible origins of this X-ray weakness, focusing in particular on the three possibilities reported above and finding indications in support of one or the other. In particular, they found an enhanced EW(H α broad ) in these sources that can suggest the Broad-line region to be distributed with a large covering factor around the central source acting as a dense dust-free absorbing medium, that can potentially reach Compton-thick column densities. On the other hand, the authors also find that many of the AGN newly discovered by JWST have features in common with the population of Narrow-line Seyfert 1 (NLS1), which are known to have a steep X-ray spectrum (and therefore more shifted towards a softer X-ray emission) and / or are characterized by high accretion rates, that are expected to result into a weaker X-ray emission, especially at high redshift, where higher rest frame energies are probed with Chandra.', '4.10. Radio stacking to discriminate the nature of X-ray weakness': 'To attempt to discriminate between the heavily obscured versus intrinsic X-ray weakness scenario to explain the observed X-ray weakness of these AGNs, we took into account the 1.4GHz radio image of the EGS field (Ivison et al. 2007). Di ff erent works showed that the physical processes and the magnetic fields at the origin of the hot corona, where the inverse Compton scattering produces the AGN X-ray emission, are also responsible for (at least part of) the synchrotron radiation at the origin of the AGN-related radio emission (Laor & Behar 2008; Panessa et al. 2019). The connection between these two emissions is also at the basis of the so-called fundamental plane relations (Merloni et al. 2003) or of X-ray - radio luminosity relations reported in di ff erent works in the literature (D\'Amato et al. 2022; Panessa et al. 2019; Fan & Bai 2016). Radio emission is generally largely una ff ected by obscuration and can pass freely even from the most obscured environments, contrary to the X-rays that are almost completely absorbed at CTK hydrogen column densities.  \nHowever, some works show that even the radio emission can be partially or completely absorbed by the BLR clouds if their uniform distribution is also dense enough to determine free-free absorption (Juodžbalis et al. 2024a, Mazzolari et al. in prep.). However, it is still not clear whether the X-ray and radio emissions originate and are distributed on the same scale, and, therefore, if the e ff ect of obscuration from BLR clouds can suppress both or not (Paul et al. 2024). For example, in Laor & Behar (2008) the authors found that the smallest possible scale of radio emission ( ν ∼ 1 -5 GHz ) in radio-quiet (RQ) AGN, e.g., coming from a compact radio corona or jet base, should originate from a region ≥ 100 times the extent of the X-ray emitting core. In this case, the radio emission would probably originate (or be being mainly distributed) outside of the BLR without being absorbed. Therefore in the following computations we assume that there is not a free-free absorption e ff ect on the radio emission of the NLAGN and BLAGN investigated in this work, and we leave a more detailed discussion to Mazzolari et al. in prep.  \nConsequently, if these AGN are normal AGN (in terms of bolometric to intrinsic X-ray luminosity), and heavily obscured (but  \nFig. 15: Median radio stacking of the three AGN samples taken into account. From the top to the bottom we report 25" × 25" cutouts of BLAGN, NLAGN at z > 4 . 5, NLAGN at z < 4 . 5. None of the samples show radio detection.  \n<!-- image -->  \nwithout absorbing also the radio emission), we might expect not to detect their X-ray emission, but we would expect to detect their radio emission at the level returned by the intrinsic X-ray to radio luminosity relations derived in the literature. On the contrary, if the radio image is deep enough to detect the expected AGN radio emission, but none is detected, we would prefer a scenario in which both the radio and X-ray emissions are intrinsically lower with respect to what is observed in normal AGN at lower redshifts. None of the NLAGN or BLAGN are detected in the 1.4GHz image of the field, apart from two sources CEERS-2900 and CEERS-3129. Therefore, we perform a detailed stacking analysis at the position of the sources, as described in Sec. 2.5, considering the same three samples as for the X-ray stacking. The radio stacking analysis didn\'t recover any 1.4GHz detection, but allowed us to derive upper limits on the median radio luminosities of these sources in the three samples. We compared these values with the expected AGN radio luminosities. Given the expected X-ray luminosities of the sources derived in Sec. 4.9, we can estimate the expected 1.4GHz luminosities using the L 1 . 4 GHz -L 2 -10 keV luminosity relation derived for radio-quiet (RQ) AGN by D\'Amato et al. (2022). The assumption that the sources are RQ is reasonable given that the  \nFig. 16: Expected 1.4GHz radio luminosity versus observed radio luminosity from the stack of the three AGN samples, as labeled. The diamonds refer to the assumption that AGN are RQ, while circles to the hypothesis that sources are RL. We also show the positions of the single sources according to the color of the respective sample. With a cyan diamond, we report the z = 1 . 037 BLAGN CEERS-3129 (presented in Appendix A). The purple diamond represents the position of CEERS-2900 with the expected L 1 . 4 GHz derived using the RQ AGN relation, while the purple circle marks the expected L 1 . 4 GHz derived using the RL AGN relation. The gray shaded region represents the dispersion of the L 1 . 4 GHz -L 2 -10 keV luminosity relation derived for radioquiet AGN by D\'Amato et al. (2022).  \n<!-- image -->  \nfraction of radio-loud (RL) AGN has been found to be ∼ 10% of the radio AGN population by di ff erent works, and it is not observed to vary with redshift (Liu et al. 2021; Williams & Röttgering 2015).  \nIt is worth noting that the e ff ectiveness of this test also depends on the fact that the AGN-related radio emission has to be dominant over the radio emission coming from star formation in the host galaxy. To check this, we considered the SFR derived for these AGNs from the SED fitting in Sec. 4.8, and we converted them into radio luminosities using the relations reported in Novak et al. (2017); Delvecchio et al. (2021). For all the three AGN samples the median 1.4GHz luminosities due to star formation are ∼ 1.5 dex lower than the AGN radio luminosity derived from the L 1 . 4 GHz -L 2 -10 keV luminosity relation of D\'Amato et al. (2022).  \nThe comparison between the observed and the expected 1.4GHz luminosities of the three AGN samples is presented in Fig. 16, together with the upper limits of the single sources in the three samples. Unfortunately, the AEGIS20 radio image is too shallow to give conclusive constraints on the nature of the X-ray weakness of these samples of AGN, being the upper limits of the stack still compatible with the expected radio luminosities.  \nWe also explore the possibility that the bulk of the sources are instead RL, and, therefore, we computed the expected radio luminosities of the three stacks considering the L 1 . 4 GHz -L 2 -10 keV luminosity relation of Fan & Bai (2016), derived for RL AGN. In this case, the upper limits on the 1.4GHz luminosities are different orders of magnitudes lower than expected, excluding the RL scenario, which was, however, already considered improbable implying all (or most of) the sources to be RL.  \nIn Fig. 16, we also report the position of the two radio-detected sources, i.e., CEERS-2900 and CEERS-3129, at z = 1 . 9 and z = 1 . 03, respectively. The first has a 1.4GHz radio flux of 58mJy, which corresponds to an observed radio luminosity of L 1 . 4 GHz ∼ 10 43 erg / s. If we assume that CEERS-2900 is a RQ AGN, the expected radio luminosity given its intrinsic 2-10keV X-ray luminosity reported in Buchner et al. (2015) (where the source is classified as a CTK AGN) is only L 1 . 4 GHz , exp = 6 × 10 39 erg / s. This strongly points toward the RL nature of this source. Indeed, considering the RL L 1 . 4 GHz / log L 2 -10 keV luminosity relation reported in Fan & Bai (2016), the observed and expected radio luminosities correspond almost perfectly.  \nCEERS-3129 has instead a 1.4GHz radio flux of 286 µ Jy that translates into a radio luminosity L 1 . 4 GHz ∼ 10 40 erg / s. The value of the expected L 1 . 4 GHz , computed starting from the expected L 2 -10 keV luminosity, is almost consistent with the hypothesis of CEERS-3129 being a RQ AGN, since the observed and expected radio luminosities are quite consistent (close to the scatter of the relation). This is even more true if we recall that the expected L 2 -10 kev , derived from the dust-corrected Lbol computed using the broad H α emission, is probably slightly underestimated because the obscuration of the broad H α component is probably larger than the one derived from the narrow-line Balmer decrement (see Sec. 4.9).  \nThe fact that the expected and observed radio luminosities of CEERS-3129 almost correspond supports the extreme CTK scenario to explain the X-ray weakness of this source. However, this scenario is not free from problematics. For example, it requires the CTK envelope around the central SMBH absorbing the X-ray emission to be almost completely dust-free to allow the broad H α emission to escape. A natural solution to this problem is that the BLR clouds themselves, with large column densities distributed with approximately a 4 π covering factor, absorb the X-ray photons, as discussed and analyzed in Maiolino et al. (2024a).', '5. Conclusions': "In this work, we analyzed the public JWST / NIRSpec medium resolution (MR) spectra of the CEERS survey (PID.1340) to identify NLAGN using multiple emission-line diagnostic diagrams. In particular, we identify a secured spectroscopic redshift of 217 / 313 targets observed with MR setup. We performed spectral line fitting using QubeSpec , and fitting separately di ff erent complexes of emission lines, ranging from rest-UV to restoptical. We considered 10 di ff erent emission line diagnostic diagrams to perform the NLAGN selection, using both demarcation lines taken from the literature and also exploiting the distribution of SFG and AGN photoionization models taken from Gutkin et al. (2016) and Feltre et al. (2016). This process led to the identification of 52 NLAGN, whose IDs and main physical parameters are reported in Table C.1 to allow the scientific community to perform further studies. The main results are the following:  \n- -Traditional AGN diagnostic diagrams, in particular the BPT (R3N2), are less e ff ective in selecting AGN at z > 3, because highz galaxies and AGN generally overlap in these diagnostics due to the di ff erent physical conditions of highz sources. For the highz regime, the most e ff ective AGN diagnostic diagrams are those based on the [O iii ] λ 4363 line or on the high-ionization emission lines from Mazzolari et al. (2024).\n- -We select 10 NLAGN at z > 6 (3 of them marked as candidates NLAGN), whose spectra are reported in Appendix D.\n- -The NLAGN selection includes only one out of the eight BLAGN at z > 4 . 5 selected in (Harikane et al. 2023), i.e. CEERS-1244, four out of five of the X-ray sources with a CEERS MR spectrum and classified as AGN by the X-ray spectral analysis in Buchner et al. (2015), and both the radio detected sources reported in the radio catalog of Ivison et al. (2007).\n- -The fraction of NLAGN selected among the CEERS spectra analyzed in this work is ∼ 20%, a fraction that is almost constant across di ff erent redshifts and agrees well with what was found by Scholtz et al. (2023a) for the JADES survey.\n- -We analyzed the distribution of [O iii ] λ 5007 NL FWHM of the AGN and non-AGN samples without finding any significantly di ff erent distribution for the two populations, suggesting that the NLAGN identified in this work do not significantly impact the ISM of their host galaxies. This probably happens because, thanks to the sensitivity of JWST, we are sampling a di ff erent population of NLAGN without outflows compared to previous NLAGN samples. Furthermore, in many cases, and in particular for low-mass high-redshift sources, the FWHM are very close to the resolution limit of JWST.\n- -We also investigated the average obscuration level of the sources by computing the AV values for those sources having both the H α and H β lines available in their spectra. We did not find a significant evolution with a redshift of the value of AV . We also note that the AGN population is characterized, in the lower redshift bin 1 < z < 2 . 5, by a ∼ 0 . 7 mag larger obscuration value, while in the other redshift bins the median value of obscuration of NLAGN and SFG is almost the same.\n- -We computed the bolometric luminosities of the sources using the dust-corrected H β fluxes and the scaling relation reported in Netzer (2009). The range of Lbol spanned by our NLAGN sample at z > 3 is much lower than the AGN bolometric luminosities reported in any pre-JWST samples, but ∼ 1 -2 dex larger than bolometric luminosities of the sample of JWST detected NLAGN reported in Scholtz et al. (2023a) selected in the JADES survey (where the observing times are significantly longer). We tested the robustness of the derived bolometric luminosities by comparing our baseline results with those derived using the calibrations reported in Lamastra et al. (2009) for the [O iii ] λ 5007 line, finding a good agreement between the two.\n- -We performed a SED-fitting analysis using CIGALE to derive the main physical properties of the host galaxies of the sample NLAGN and non-AGN. We found that, on average, sources at z > 4 deviate from the main sequence of Popesso et al. (2023), moving toward higher values of SFR than what is predicted by the MS. The range of stellar masses extends down to ∼ 10 7 M ∗ . We didn't find any significant di ff erence in the SFR or M ∗ distribution of the NLAGN compared to those of the parent sample, suggesting that any potential AGN positive or negative e ff ect on the host-galaxy SFR is not significantly taking place. This is further supported by the lack of significant outflow detections in their spectra.\n- -We investigate the X-ray properties of the selected NLAGN and of the BLAGN selected in Harikane et al. (2023). We found that none of the BLAGN is detected in the X-ray image of the field and that only 4 of the 52 NLAGN are X-ray detected. We performed an X-ray stacking analysis on the AGN that are not X-ray detected, finding an X-ray deficit of ∼ 1 . 3 dex for the highz BLAGN and for the sample of NLAGN at z > 4 . 5, and ∼ 2 dex for the NLAGN at z < 4 . 5 between their expected X-ray luminosities (given their bolometric luminosity) and what comes from the X-ray stacking. We tried to investigate the origin of this X-ray weakness by studying the radio emission of these sources, which can help to disentangle the heavily obscured AGN scenario from the intrinsic X-ray weak one. Unfortunately, the radio observation covering the region of the CEERS survey is not deep enough to provide a conclusive answer. However, this shows the key role that present and future deep radio continuum observations can have in understanding the problem of the X-ray weakness of highz AGN.  \nInterestingly, one of the low-redshift BLAGN, which has also been selected by the NLAGN selection, CEERS-3129, is undetected in the deep X-ray image (showing an X-ray deficit of ∼ 2 dex), but it is detected in the radio image of the field, with a radio luminosity compatible with the RQ AGN nature. The radio detection of CEERS-3129 supports the CTK AGN scenario at the origin of the observed X-ray weakness.  \nJWSTis allowing us to reveal the population of heavily obscured AGNupto very high redshift ( z > 8) and, at the same time, to investigate the NLAGN population at low redshift with a spectroscopic sensitivity not explored by pre-JWST surveys. This work highlights the necessity of defining new NLAGN diagnostic diagrams and, in general, di ff erent and complementary AGN selection techniques suited for the identification at high redshift AGN. Future works will have to explore in more detail the actual number density and the demography of these objects in the early Universe, carefully accounting for the selection function of each spectroscopic campaign. We also stress that a multiwavelength approach, such as the one outlined in this work, is necessary to explore and potentially provide answers to the peculiar features characterizing high redshift AGN.  \nAcknowledgements. GM acknowledges useful conversations with Andrea Comastri, Roberto Decarli, Sandro Tacchella, William Baker, Callum Witten, Lola Danhaive, Ignas Juodzbalis, Amanda Sto ff er, Brian Xing Jiang, and William McClaymont. FDE, JS, RM, and XJ acknowledge support by the Science and Technology Facilities Council (STFC), from the ERC Advanced Grant 695671 'QUENCH', and by the UKRI Frontier Research grant RISEandFALL. RM also acknowledges funding from a research professorship from the Royal Society. HÜgratefully acknowledges support by the Isaac Newton Trust and by the Kavli Foundation through a Newton-Kavli Junior Fellowship.", 'References': "Abazajian, K. N., Adelman-McCarthy, J. K., Agüeros, M. A., et al. 2009, ApJS, 182, 543  \n- Aird, J., Coil, A. L., Georgakakis, A., et al. 2015, MNRAS, 451, 1892\n- Allen, M. G., Groves, B. A., Dopita, M. A., Sutherland, R. S., & Kewley, L. 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Three of these sources are X-ray detected (CEERS-2904, CEERS-2919, CEERS-2989), while one is radio detected (CEERS-3129). These sources were first fitted in the range around the H α line using a narrow-line only fit (as described in Sec. 2.2) and then adding a single broad component accounting for the emission of the BLR around the AGN, as presented in Fig. A.1. In order to test the significance of the broad H α component we used the Bayesian Information Criterion (BIC) parameter (Liddle 2007), we found that the BLR model is strongly preferred to the narrow-only fit ( ∆ BIC = BICH α NL -BICH α BL > 40 for all the sources). The ∆ BIC values for the single fit are shown in the right part of each panel in Fig. A.1.  \nIn fitting the H β and [O iii ] λ 5007 lines complex of these sources we didn't find any significant broad component in none of the two lines.", 'Appendix B: CIGALE SED fitting parameters grid': 'Here we report the grid of parameters used for the SED-fitting described in Sec. 2.4  \nAppendix C: NLAGN Table  \nAppendix D: Spectra of the NLAGN at z > 6', 'G. Mazzolari et al.: Narrow-line AGN selection in CEERS': 'Fig. D.2: Continuation of Figure D.1  \n<!-- image -->', 'A & A proofs: manuscript no. main': 'Fig. D.1: Spectra of the sources selected as NLAGN at z > 6. In each plot, we highlight in the box the main spectral features that led to the identification as a NLAGN. CEERS-1019, CEERS-23 and CEERS-496 are marked as tentative selections due to their dubious position in the diagnostic diagrams reported in Sec. 3  \n<!-- image -->'}