Spectral Energy Distribution Modeling of Broad Emission Line Quasars: From X-ray to Radio Wavelengths

Arijit Sar; Avinanda Chakraborty; Maitreya Kundu; Ritaban Chatterjee; Sandra Jaison; Suchetana Chatterjee; Swayamtrupta Panda

REVIEW 3 major objections 6 minor 128 references

Spectral Energy Distribution Modeling of Broad Emission Line Quasars: From X-ray to Radio Wavelengths

T0 review · 3 major / 6 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read The paper claims that radio-loud quasars with low Eddington ratios have substantially lower star-formation rates at fixed stellar mass than comparable radio-quiet quasars, pointing to jet-driven quenching in their host galaxies.

desk verdict A transparent, useful SED modeling paper whose headline claim about jet quenching in low-Eddington radio-loud quasars is confounded by the very sources chosen to test it. read the letter →

arxiv 2411.15836 v1 pith:JFDWGVPE submitted 2024-11-24 astro-ph.GA

Avinanda Chakraborty , Maitreya Kundu , Suchetana Chatterjee , Swayamtrupta Panda , Arijit Sar , Sandra Jaison , Ritaban Chatterjee This is my paper · ORCID

classification astro-ph.GA

keywords quasarsradio-loudhostgalaxiesspectralenergydistributionstarformationEddingtonratioradiodichotomySEDfitting

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper tries to establish that the radio-loud versus radio-quiet divide in quasars shows up in the host galaxies, not just in the central engines. By fitting X-ray-to-radio spectral energy distributions of 56 optically selected broad-line quasars with the CIGALE modeling code, the authors recover host stellar masses and star-formation rates even though the quasar contributes most of the light. They find that radio-loud quasars with lower Eddington ratios sit on a lower star-formation sequence at fixed stellar mass, forming a bimodal split in the main-sequence relation. The result matters because it points to a physical route by which radio jets from weakly accreting quasars could suppress star formation in their hosts, offering a new handle on the long-unexplained radio dichotomy.

What carries the argument

The load-bearing tool is broadband SED fitting with the CIGALE v2022.0 code, which combines a delayed star-formation history, standard stellar population templates, dust attenuation and emission models, the SKIRTOR clumpy-torus AGN templates, a radio synchrotron module, and an X-ray module to separate quasar from host emission across GALEX, SDSS, WISE, FIRST, X-ray, and AstroSat/UVIT bands. The key comparison objects are the analytic main-sequence relation for star-forming galaxies and the Eddington-ratio–stellar-mass plane, where the bimodality among radio-loud quasars appears. The host-galaxy fraction, estimated both by simulating an AGN-only SED and by empirical relations, is used to check that the faint host component, about 20 to 35 percent of the total luminosity, is recoverable.

What would settle it

Measure the cold gas or far-infrared dust emission of the low-Eddington radio-loud quasars: if their gas fractions match radio-quiet controls at the same stellar mass and redshift, the inferred suppression is a modeling artifact rather than real quenching. A larger sample with X-ray detections that shows no star-formation deficit at fixed Eddington ratio would also falsify the claim.

Watch

Extended reading notes

Core claim

The central claim is that, among broad-line quasars at 0.15 < z < 1.9, radio-loud sources separate into two populations in the stellar-mass–star-formation-rate plane. The radio-loud quasars with the lowest Eddington ratios, including the very broad-line subsample with FWHM greater than 15000 km/s and the AstroSat UV sources, have substantially lower star-formation rates at similar stellar masses, whereas radio-quiet quasars do not show the same split. The authors conclude that radio jets from low-Eddington-ratio systems may inhibit star formation in their host galaxies, providing a host-galaxy perspective on the radio dichotomy problem. The mean host properties of the two populations are otherwise similar, so the difference is in how star formation correlates with stellar mass and accretion state, not in the average stellar mass or star-formation rate.

Load-bearing premise

The argument assumes that, when the quasar contributes 65 to 80 percent of the total light, the SED model still recovers unbiased stellar masses and star-formation rates for the 20 to 35 percent host component.

Editorial extensions

If this is right

If the central claim is right, low-Eddington-ratio radio-loud quasars become a natural population for studying negative AGN feedback, since their hosts show suppressed star formation at fixed stellar mass.
The lack of an equivalent bimodality among radio-quiet quasars implies that the radio jet, not the accretion rate alone, is the likely quenching agent.
Because the modeled SEDs reproduce the observed SDSS spectra, the same fitting approach can be applied to larger photometric quasar samples where spectra are unavailable.
The finding that quasar hosts lie off the local main sequence and follow a higher-redshift relation means SED-based host studies must account for redshift evolution of the reference relation.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

A testable extension the paper leaves implicit: low-Eddington-ratio radio-loud quasars should have lower cold-gas masses and dust masses at fixed stellar mass than matched radio-quiet controls, which could be checked with CO or far-infrared observations.
The bimodality is carried largely by six HBL and AstroSat sources that lack X-ray detections, so a larger, X-ray-complete sample would show whether the star-formation deficit survives selection effects.
If jets quench by heating or ejecting gas, the effect should grow with radio luminosity or jet power at fixed Eddington ratio; correlating star-formation offsets with radio morphology, core versus lobe dominated, would test this.
The dichotomy threshold near log lambda_Edd approximately -1.5 could correspond to a transition in accretion state, connecting host-galaxy quenching to the central engine's accretion mode.

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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Desk Editor's Note

read the letter

Thanks for the report. This is a paper worth taking seriously, but its headline result is not yet established. The authors compile a useful sample of 37 radio-loud and 19 radio-quiet broad-line quasars, add new AstroSat FUV photometry, and run a careful CIGALE setup with standard AGN modules. The transparency is real: photometry in tables, robustness checks dropping bands, mock-catalog validation, and a spectral-reconstruction sanity check against SDSS. That is the good part.

The problem is the central claim. The abstract says low-Eddington-ratio RL quasars have substantially lower SFRs at fixed stellar mass, and suggests jets quench their hosts. But the low-Eddington group is exactly the six HBL+AstroSat RL sources that were added because they lack X-ray detections, while the non-HBL comparison sample is X-ray-selected. These sources also sit at z<0.65 and have FWHM>15,000 km/s. The stress-test note is right: the apparent bimodality in Fig. 8 cannot be separated from X-ray selection or FWHM class. The authors themselves call it a 'hint' in the text, which is the right word; the abstract overreaches.

Other soft spots are secondary but real. No error bars or significance tests in Figs. 8 and 10. The SFR-M* slope flips sign when the HBL/AstroSat sources are included. There is an internal IMF contradiction: Salpeter in §2.2 versus Chabrier in Table 4. Several reduced chi-square values are high, up to 7, which suggests the grid may be missing something. And the 'for the first time' framing overstates novelty relative to the existing CIGALE-AGN-host literature.

I read this as a solid data paper with an intriguing but unproven physical suggestion. The right fix is to re-frame the result as a selection-corrected hint, add proper significance testing with error bars, reconcile the IMF, and attempt some control for the X-ray-selected versus non-detected mix. A serious referee can work with this; it should not be desk-rejected. I would not cite the central claim, but the sample and methods deserve attention.

Referee Report

3 major / 6 minor

Summary. The paper compiles a sample of 37 radio-loud and 19 radio-quiet broad-line quasars from SDSS DR7, cross-matched with FIRST, WISE, GALEX, and X-ray catalogs, and adds new AstroSat/UVIT FUV photometry for six sources. The authors use CIGALE v2022.0 with SKIRTOR AGN emission, delayed star-formation histories, and BC03 stellar templates to fit SEDs from X-ray to radio wavelengths and derive host-galaxy stellar masses, star-formation rates, dust luminosities, stellar ages, and e-folding times. They report that the host galaxy contributes 20%-35% of the total luminosity, that the modeled SEDs reproduce the SDSS spectra, that the quasars lie off the star-forming main sequence, and that RL quasars show a bimodality in the M*-SFR plane. The central conclusion is that RL quasars with lower Eddington ratios have substantially lower star-formation rates at similar stellar mass, which the authors interpret as possible jet-induced quenching and a host-galaxy perspective on the radio dichotomy problem.

Significance. The dataset and modeling effort have real value: the paper presents new AstroSat observations, makes full photometric tables available, and applies a modern SED code with AGN modules to an FWHM-classified quasar sample. If the reported low-SFR/low-Eddington-ratio association were robust, it would provide a genuinely interesting host-galaxy constraint on the radio dichotomy problem. However, the central claim is currently not supported by the analysis as presented, because it rests on six sources that differ from the rest of the RL sample in X-ray detection, FWHM, and redshift, with no significance test and no individual error bars in the key figures. The paper also contains an internal inconsistency between the IMF stated in the text and the IMF in Table 4, and several figure-caption errors. With added selection controls, error bars, significance testing, and a more cautious interpretation, the underlying data would support a useful paper.

major comments (3)

[§2.1, Figs. 8–10] The central claim is confounded by sample construction. The 31 non-HBL RL sources were required to have an X-ray counterpart, whereas the 3 HBL and 3 AstroSat RL sources that form the low-Eddington, low-SFR group were added specifically because they lack X-ray detections (stated in §2.1 and §4), and they differ from the non-HBL sample in FWHM class and redshift (all six at z < 0.65 versus the non-HBL sample extending to z ~ 1.9). Since X-ray detection is correlated with accretion luminosity and possibly with host-galaxy emission, the apparent bimodality in Fig. 8 and the dichotomy in Fig. 10 could be selection artifacts rather than physical quenching. No significance test is given for the bimodality, and Fig. 8 shows no individual error bars. A control analysis restricted to X-ray-detected sources, or to z < 0.65, or comparing X-ray-detected and X-ray-undetected non-HBL sources, is needed before the jet-quenching interpretation can be evaluated.
[§3.2, Fig. 8] The power-law fits reveal a sign flip that is not discussed: for RL sources the full sample gives SFR ∝ M*^-0.4±0.02, while the non-HBL sample alone gives SFR ∝ M*^0.5±0.01. The negative slope is therefore driven entirely by the six HBL+AstroSat sources, so the abstract's statement that 'RL quasars with lower Eddington ratios tend to have substantially lower star-formation rates for similar stellar mass' is the opposite of the trend within the X-ray-selected subset. The authors should report the fit for the low-redshift/X-ray-undetected subsample separately, quantify the uncertainties, and explain why the inclusion of these six sources reverses the correlation.
[§3.1, Table 4] The reliability of the SFR and M* estimates for the six low-Eddington sources is not established. Only 54% of the RL sources satisfy the Bayesian/best-fit consistency criterion of Mountrichas et al. (2021), the host contributes only 20%-35% of the total luminosity, and the robustness test in §3.2 shows that omitting UV data changes the stellar mass. Because the central claim rests on a handful of quasar-dominated SEDs, the paper should show marginalized posterior distributions or at least individual uncertainties for SFR and M* for the HBL and AstroSat sources, and should quantify how the apparent M*-SFR dichotomy changes under alternative CIGALE configurations (e.g., different star-formation histories or IMF).

minor comments (6)

[§2.2 vs Table 4] The text states that stellar emission is modeled with the Salpeter (1964) IMF, while Table 4 specifies the Chabrier (2003) IMF; this discrepancy must be resolved because stellar mass estimates depend on the IMF.
[§2.1.1] The astrometry paragraph lists the same object twice ('SDSS 085605.83+450520.0 and SDSS 085605.83+450520.0'); the second identifier is presumably a different source and should be corrected.
[Figs. 7 and 8 captions] The figure captions contain duplicated panel labels: Fig. 7 has two 'Top Left Panel' entries and Fig. 8 has two 'Bottom Left Panel' entries; these should be corrected to Top/Middle/Bottom Left/Right.
[§3.4 and Abstract] The statement that the host galaxy contributes 'about 50% of the total luminosity at relatively lower wavelengths' in the UV-IR range is hard to reconcile with the abstract's '20%-35% of the total luminosity' unless the latter is integrated over all wavelengths; please define the integration range explicitly.
[§3.3] The agreement with SDSS spectra validates the total AGN+host SED, but it does not independently validate the AGN-host decomposition, since the optical bands are AGN-dominated; this limitation should be stated when the validation is claimed.
[§4] The M21 sub-sample power-law slopes are said to be unchanged from the full sample, but the fitted values for the M21 sub-sample are not reported; please provide them.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the SFR–stellar-mass–Eddington-ratio comparison is an empirical correlation among independently fitted quantities, not a fitted input renamed as a prediction.

full rationale

The paper's central claim is an empirical correlation between host-galaxy star-formation rate and Eddington ratio among radio-loud quasars. Stellar masses and SFRs are obtained by fitting broadband photometry with CIGALE v2022.0, while Eddington ratios come from SDSS DR7 virial black-hole masses and luminosities; neither quantity is defined in terms of the other. The group separation (HBL plus AstroSat sources versus non-HBL sources) is based on FWHM, X-ray nondetection, and UVIT observation status, not on SFR. The statement that lower-Eddington-ratio RL quasars have lower SFR at similar stellar mass is a comparison of independently fitted host properties, not a fitted parameter renamed as a prediction. The SDSS spectral overlay is a consistency check of the same photometric fit, not an independent derivation of a derived constant. Self-citations to Chakraborty et al. (2021, 2022) supply the sample definitions and earlier Eddington-ratio results, but the current paper re-derives the Eddington-ratio dichotomy in Fig. 10 and connects it to SFR from its own fits, so these citations are not load-bearing. No equation in the paper reduces the conclusion to its inputs: Eq. 2 defines the host-galaxy fractional contribution, and the model grid in Table 4 consists of external templates. The selection confounds noted in the text—HBL and AstroSat sources lacking X-ray detections and carrying the bimodality—are threats to the astrophysical interpretation, not evidence of circular derivation. The analysis is therefore self-contained for the purpose of circularity assessment.

Assumptions & free parameters 7 free parameters · 5 assumptions · 0 invented entities

The central claim depends on a chain of modeling assumptions: the chosen SFH, stellar population templates (with an internal IMF inconsistency), dust attenuation/emission recipes, the AGN torus model, and the fraction of light assigned to the AGN. Each is a grid choice in CIGALE that is fitted to the data, so the inferred SFR and stellar mass carry model dependence. The paper also imports external empirical relations and prior virial mass estimates for interpretation. The strongest physical conclusion (low Eddington ratio RL quasars have lower SFRs) therefore relies on the validity of these many inputs, several of which are tested only indirectly.

free parameters (7)

Stellar e-folding time tau (sfhdelayed) = varies per source (grid: 0.1, 0.5, 1, 5 Gyr)
Sets the shape of the delayed star-formation history; directly influences SFR and stellar mass estimates.
Stellar population age t_age = varies per source (grid: 0.5, 1, 3, 5, 7 Gyr)
Determines the stellar mass-to-light ratio and the normalization of SFR; degenerate with tau and dust.
Color excess E(B-V) (dust attenuation) = varies per source (grid: 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.7, 0.9 mag)
Dust reddening strongly affects UV/optical SED shape and hence the inferred SFR and stellar mass.
AGN fraction frac_AGN = varies per source (grid: 0.0 to 0.9 in steps of 0.1, and 0.99)
Partitions IR luminosity between AGN torus and host galaxy; critical for the AGN-host decomposition that underlies all host properties.
AGN inclination i = grid: 30, 60, 70, 80, 90 deg
SKIRTOR emission is anisotropic; inclination changes the apparent AGN contribution in optical/IR and therefore affects the host fraction.
Radio-loudness R_AGN (RL only) = grid: 0.01 to 10000
Controls AGN radio contribution; fitted to FIRST 1.4 GHz data; does not directly affect SFR but affects radio module.
X-ray slope alpha_ox = grid: -1.9 to -1.1, plus |Delta alpha_ox|max=0.2
Sets AGN X-ray luminosity relative to 2500 A; weakly impacts host parameters since X-ray is AGN-dominated.

assumptions (5)

domain assumption CIGALE's energy balance and template set (BC03 SSP, Calzetti attenuation, Dale et al. 2014 dust, SKIRTOR torus) adequately represent the quasar host galaxy SEDs.
Invoked throughout §3.1-§3.4; if the templates are wrong, the derived SFR and stellar mass are biased (e.g., the IMF inconsistency in §2.2 vs Table 4 is a symptom of this fragility).
domain assumption The delayed star-formation history with a recent burst component (constant for up to 50 Myr) spans the true SFHs of the sample.
Chosen in §2.2; SFH shape is degenerate with age and dust, and the authors cite Mountrichas et al. 2023 for degeneracies but do not quantify the impact on the bimodality claim.
domain assumption External empirical relations (Jalan et al. 2023 host-galaxy fraction; Schreiber et al. 2015 main sequence) are valid for this sample and redshift range.
Used in §4 to benchmark the 20-35% host fraction and the MS offset; if these relations do not apply to quasars, the interpretation of the MS bimodality changes.
domain assumption Virial black hole masses and Eddington ratios from Shen et al. (2011) and Chakraborty et al. (2022) are accurate, including for HBL sources.
The Eddington ratio comparison in Fig. 10 is central to the interpretation linking low SFR to low Eddington ratio; errors in virial masses propagate directly.
domain assumption The X-ray-detected non-HBL and the X-ray-undetected HBL/AstroSat subsamples can be combined into a single RL/RQ comparison without systematic bias.
The claimed bimodality is driven by the 6 HBL+AstroSat RL sources, which were selected differently (no X-ray detection); no test demonstrates that this selection difference is not responsible for the lower SFRs.

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Cite this review

Pith. "Pith review of Spectral Energy Distribution Modeling of Broad Emission Line Quasars: From X-ray to Radio Wavelengths." pith.science (2026). https://pith.science/paper/JFDWGVPE

@misc{pith2026241115836,
  author       = {Pith},
  title        = {Pith review of: Spectral Energy Distribution Modeling of Broad Emission Line Quasars: From X-ray to Radio Wavelengths},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/JFDWGVPE}},
  note         = {Machine review of arXiv:2411.15836}
}

read the original abstract

We study the differences in physical properties of quasar-host galaxies using an optically selected sample of radio loud (RL) and radio quiet (RQ) quasars (in the redshift range 0.15 < z < 1.9) which we have further cross-matched with the VLA-FIRST survey catalog. The sources in our sample have broad Hbeta and MgII emission lines (1000 km/s < FWHM < 15000 km/s) with a subsample of high broad line quasars (FWHM > 15000 km/s). We construct the broadband spectral energy distribution (SED) of our broad line quasars using multi-wavelength archival data and targeted observations with the AstroSat telescope. We use the state-of-the-art SED modeling code CIGALE v2022.0 to model the SEDs and determine the best-fit physical parameters of the quasar host galaxies namely their star-formation rate (SFR), main-sequence stellar mass, luminosity absorbed by dust, e-folding time and stellar population age. We find that the emission from the host galaxy of our sources is between 20%-35% of the total luminosity, as they are mostly dominated by the central quasars. Using the best-fit estimates, we reconstruct the optical spectra of our quasars which show remarkable agreement in reproducing the observed SDSS spectra of the same sources. We plot the main-sequence relation for our quasars and note that they are significantly away from the main sequence of star-forming galaxies. Further, the main sequence relation shows a bimodality for our RL quasars indicating populations segregated by Eddington ratios. We conclude that RL quasars in our sample with lower Eddington ratios tend to have substantially lower star-formation rates for similar stellar mass. Our analyses, thus, provide a completely independent route in studying the host galaxies of quasars and addressing the radio dichotomy problem from the host galaxy perspective.

Figures

Figures reproduced from arXiv: 2411.15836 by the authors.

**Figure 1.** Histograms of redshift for the non-HBL+HBL+AstroSatobserved radio-loud (blue dashed) and radio-quiet (orange solid) sources in our sample. Our datasets are described in §2.1. Baldi & Capetti 2008; Herbert et al. 2010a) in powerful RL quasars, contrary to the composition of normal ellipticals that usually host RL quasars (e.g., Dunlop et al. 2003). Many studies have also attempted multi-band optical photometry (e.g… view at source ↗

**Figure 2.** Photometry of the six sources observed with [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗

**Figure 3.** Examples of best-fit SEDs of non-HBL radio-loud quasar sources, constructed using the [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗

Figures from the paper (9 more)

**Figure 4.** Figure 4: Examples of best-fit SEDs of non-HBL radio-quiet quasars sources, constructed using the [PITH_FULL_IMAGE:figures/full_fig_p008_4.png]

**Figure 5.** Figure 5: Best-fit SEDs of HBL sources. Reduced χ 2 values calculated by CIGALE v2022.0 code for individual SEDS are provided in the figures. Top Panel: RL sources. Bottom Panel: RQ sources. 2.2.1. AGN Model CIGALE v2022.0 is potentially very accurate for the characterization o…

**Figure 6.** Figure 6: Best-fit SEDs of the sources observed with [PITH_FULL_IMAGE:figures/full_fig_p010_6.png]

**Figure 7.** Figure 7: Top Left Panel: Orange solid and blue dashed lines denote the histograms of stellar mass (M⋆) for the host galaxies of radio-quiet and radio-loud quasars of the non-HBL+HBL+AstroSat-observed samples. Top Middle Panel: Same as the top left panel but for the SFR distribu…

**Figure 8.** Figure 8: The variation of stellar mass (M⋆) of the host galaxies with their corresponding SFR. Overplotted solid lines are analytical galaxy main-sequence (MS) relations from Schreiber et al. (2015), at different redshifts with corresponding 1-σ uncertainty contours. We note t…

**Figure 9.** Figure 9: The variation of stellar mass (M⋆) of the host galaxies with their corresponding SFR for our sources ( [PITH_FULL_IMAGE:figures/full_fig_p013_9.png]

**Figure 10.** Figure 10: The variation of stellar mass (M⋆) with the Eddington ratio (λEdd) of the central quasar. Top Panel: For RL non-HBL, HBL and AstroSat-observed sources. Bottom Panel: For RQ non-HBL, HBL and AstroSat-observed sources. See, [PITH_FULL_IMAGE:figures/full_fig_p014_10.png]

**Figure 11.** Figure 11: Examples of source spectra from SDSS overplotted with the best-fit SEDs from [PITH_FULL_IMAGE:figures/full_fig_p015_11.png]

**Figure 12.** Figure 12: Top Panel: The contribution of the principal AGN Components in the UV–IR range, the accretion disk and the torus, in the total SED of the host galaxy. Bottom Panel: The relative contribution of the emission from the host galaxy in the IR–UV part of the SED, following…

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Works this paper leans on

128 extracted references · 45 canonical work pages

[1]

N., Adelman-McCarthy, J

Abazajian, K. N., Adelman-McCarthy, J. K., Agüeros, M. A., et al. 2009, ApJS, 182, 543

2009
[2]

N., Dunlop, J

Archibald, E. N., Dunlop, J. S., Hughes, D. H., et al. 2001, MNRAS, 323, 417

2001
[3]

Baldi, R. D. & Capetti, A. 2008, A&A, 489, 989

2008
[4]

J., Bennert, V

Barth, A. J., Bennert, V . N., Canalizo, G., et al. 2015, ApJS, 217, 26

2015
[5]

& Järvelä, E

Berton, M. & Järvelä, E. 2021, Universe, 7, 188

2021
[6]

Best, P. N. & Heckman, T. M. 2012, MNRAS, 421, 1569

2012
[7]

N., Kauffmann, G., Heckman, T

Best, P. N., Kauffmann, G., Heckman, T. M., et al. 2005, MNRAS, 362, 25

2005
[8]

N., Kondapally, R., Williams, W

Best, P. N., Kondapally, R., Williams, W. L., et al. 2023, MNRAS, 523, 1729

2023

Show all 128 references

[9]

2009, A&A, 495, 421

Bianchi, S., Guainazzi, M., Matt, G., Fonseca Bonilla, N., & Ponti, G. 2009, A&A, 495, 421

2009
[10]

2019, A&A, 622, A103

Boquien, M., Burgarella, D., Roehlly, Y ., et al. 2019, A&A, 622, A103

2019
[11]

Boyle, B. J. & Terlevich, R. J. 1998, MNRAS, 293, L49

1998
[12]

Brandt, W. N. & Alexander, D. M. 2015, A&A Rev., 23, 1

2015
[13]

2022, Astronomy and Astrophysics, 661, A1

Brunner, H., Liu, T., Lamer, G., et al. 2022, Astronomy and Astrophysics, 661, A1

2022
[14]

& Charlot, S

Bruzual, G. & Charlot, S. 2003, MNRAS, 344, 1000

2003
[15]

C., et al

Calzetti, D., Armus, L., Bohlin, R. C., et al. 2000, ApJ, 533, 682

2000
[16]

A., Clayton, G

Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1988, ApJ, 329, L33

1988
[17]

2003, PASP, 115, 763

Chabrier, G. 2003, PASP, 115, 763

2003
[18]

& Bhattacharjee, A

Chakraborty, A. & Bhattacharjee, A. 2021, Astronomische Nachrichten, 342, 142

2021
[19]

S., et al

Chakraborty, A., Bhattacharjee, A., Brotherton, M. S., et al. 2022, MNRAS, 516, 2824

2022
[20]

2021, Galaxies, 9, 74

Chakraborty, A., Bhattacharjee, A., & Chatterjee, S. 2021, Galaxies, 9, 74

2021
[21]

Condon, J. J. 1992, ARA&A, 30, 575

1992
[22]

2006, ApJ, 647, 1040

Croft, S., van Breugel, W., de Vries, W., et al. 2006, ApJ, 647, 1040

2006
[23]

M., Richards, G

Croom, S. M., Richards, G. T., Shanks, T., et al. 2009, MNRAS, 399, 1755

2009
[24]

A., Coziol, R., & Torres-Papaqui, J

Cutiva-Alvarez, K. A., Coziol, R., & Torres-Papaqui, J. P. 2023, MNRAS, 521, 3058

2023
[25]

2023, A&A, 675, A163

Czerny, B., Panda, S., Prince, R., et al. 2023, A&A, 675, A163

2023
[26]

A., Helou, G., Magdis, G

Dale, D. A., Helou, G., Magdis, G. E., et al. 2014, ApJ, 784, 83

2014
[27]

2022, ApJ, 938, 152

Dey, S., Goyal, A., Małek, K., et al. 2022, ApJ, 938, 152

2022
[28]

S., McLure, R

Dunlop, J. S., McLure, R. J., Kukula, M. J., et al. 2003, MNRAS, 340, 1095

2003
[29]

Emonts, B. H. C., Feain, I., Mao, M. Y ., et al. 2011, ApJ, 734, L25

2011
[30]

S., Frayer, D

Evans, A. S., Frayer, D. T., Surace, J. A., & Sanders, D. B. 2001, AJ, 121, 1893

2001
[31]

N., Primini, F

Evans, I. N., Primini, F. A., Glotfelty, K. J., et al. 2010, ApJS, 189, 37

2010
[32]

Falcke, H., Sherwood, W., & Patnaik, A. R. 1996, ApJ, 471, 106

1996
[33]

J., Korista, K

Ferland, G. J., Korista, K. T., Verner, D. A., et al. 1998, PASP, 110, 761

1998
[34]

J., Porter, R

Ferland, G. J., Porter, R. L., van Hoof, P. A. M., et al. 2013, Rev. Mexicana Astron. Astrofis., 49, 137

2013
[35]

& Merritt, D

Ferrarese, L. & Merritt, D. 2000, The Astrophysical Journal, 539, L9

2000
[36]

L., Kraemer, S., et al

Fischer, T., Smith, K. L., Kraemer, S., et al. 2019, The Astrophysical Journal, 887, 200

2019
[37]

1999, MNRAS, 310, L5

Franceschini, A., Hasinger, G., Miyaji, T., & Malquori, D. 1999, MNRAS, 310, L5

1999
[38]

Gadallah, K. A. K. 2023, MNRAS, 520, 2351

2023
[39]

2000, The Astrophysical Journal, 539, L13

Gebhardt, K., Bender, R., Bower, G., et al. 2000, The Astrophysical Journal, 539, L13

2000
[40]

2023, A&A, 673, A67

Georgantopoulos, I., Pouliasis, E., Mountrichas, G., et al. 2023, A&A, 673, A67

2023
[41]

M., et al

Giacintucci, S., O’Sullivan, E., Vrtilek, J. M., et al. 2010, in American Institute of Physics Conference Series, V ol. 1248, X-ray Astronomy 2009; Present Sta- tus, Multi-Wavelength Approach and Future Perspectives, ed. A. Comastri, L. Angelini, & M. Cappi (AIP), 277–280 Gürk...

2010
[42]

Hamilton, T. S. 2010, MNRAS, 407, 2393

2010
[43]

Harrison, C. M. C. 2014, PhD thesis, Durham University, UK

2014
[44]

Heckman, T. M. & Best, P. N. 2014, ARA&A, 52, 589

2014
[45]

T., & Rowan-Robinson, M

Helou, G., Soifer, B. T., & Rowan-Robinson, M. 1985, ApJ, 298, L7

1985
[46]

Hopkins, A. M. & Beacom, J. F. 2006, ApJ, 651, 142

2006
[47]

Inoue, A. K. 2011, MNRAS, 415, 2920 Ivezi´c, Ž., Menou, K., Knapp, G. R., et al. 2002, AJ, 124, 2364

2011
[48]

Jalan, P., Rakshit, S., Woo, J.-J., Kotilainen, J., & Stalin, C. S. 2023, MNRAS, 521, L11

2023
[49]

2007, ApJ, 656, 680

Jiang, L., Fan, X., Ivezi´c, Ž., et al. 2007, ApJ, 656, 680

2007
[50]

J., Bonfield, D

Kalfountzou, E., Jarvis, M. J., Bonfield, D. G., & Hardcastle, M. J. 2012, Monthly Notices of the Royal Astronomical Society, 427, 2401

2012
[51]

2011, MNRAS, 413, 249

Kalfountzou, E., Trichas, M., Rowan-Robinson, M., et al. 2011, MNRAS, 413, 249

2011
[52]

M., & Best, P

Kauffmann, G., Heckman, T. M., & Best, P. N. 2008, MNRAS, 384, 953

2008
[53]

M., Tremonti, C., et al

Kauffmann, G., Heckman, T. M., Tremonti, C., et al. 2003, MNRAS, 346, 1055

2003
[54]

Kauffmann, G., White, S. D. M., Heckman, T. M., et al. 2004, MNRAS, 353, 713

2004
[55]

I., Sramek, R., Schmidt, M., Sha ffer, D

Kellermann, K. I., Sramek, R., Schmidt, M., Sha ffer, D. B., & Green, R. 1989, AJ, 98, 1195

1989
[56]

E., Kellermann, K

Kimball, A. E., Kellermann, K. I., Condon, J. J., Ivezi´c, Ž., & Perley, R. A. 2011, ApJ, 739, L29

2011
[57]

2022, A&A, 658, A35 Kovaˇcevi´c, J., Popovi´c, L

Koutoulidis, L., Mountrichas, G., Georgantopoulos, I., Pouliasis, E., & Plionis, M. 2022, A&A, 658, A35 Kovaˇcevi´c, J., Popovi´c, L. ˇC., & Dimitrijevi´c, M. S. 2010, ApJS, 189, 15

2022
[58]

Lagos, C. D. P., Padilla, N. D., & Cora, S. A. 2009, MNRAS, 395, 625

2009
[59]

& Behar, E

Laor, A. & Behar, E. 2008, MNRAS, 390, 847

2008
[60]

J., & McDowell, J

Laor, A., Fiore, F., Elvis, M., Wilkes, B. J., & McDowell, J. C. 1997, ApJ, 477, 93 Le Fèvre, O., Lemaux, B. C., Nakajima, K., et al. 2019, Astronomy and Astro- physics, 625, A51

1997
[61]

Leitherer, C., Calzetti, D., & Martins, L. P. 2002, 574, 114

2002
[62]

C., Dickinson, M

Madau, P., Ferguson, H. C., Dickinson, M. E., et al. 1996, MNRAS, 283, 1388

1996
[63]

2005, MNRAS, 362, 799

Maraston, C. 2005, MNRAS, 362, 799

2005
[64]

C., Fanson, J., Schiminovich, D., et al

Martin, D. C., Fanson, J., Schiminovich, D., et al. 2005, ApJ, 619, L1

2005
[65]

2023, Galaxies, 11, 52

Marziani, P., Panda, S., Deconto Machado, A., & Del Olmo, A. 2023, Galaxies, 11, 52

2023
[66]

2021, in American Astronomical Society Meeting Abstracts, V ol

Marziani, P., Sniegowska, M., Panda, S., et al. 2021, in American Astronomical Society Meeting Abstracts, V ol. 53, American Astronomical Society Meeting Abstracts, 337.03

2021
[67]

McLure, R. J. & Dunlop, J. S. 2001, Monthly Notices of the Royal Astronomical Society, 321, 515

2001
[68]

McLure, R. J. & Dunlop, J. S. 2004, MNRAS, 352, 1390

2004
[69]

McLure, R. J. & Jarvis, M. J. 2004, MNRAS, 353, L45

2004
[70]

2024, Astronomy and Astrophysics, 682, A34

Merloni, A., Lamer, G., Liu, T., et al. 2024, Astronomy and Astrophysics, 682, A34

2024
[71]

A., & Mead, A

Miller, L., Peacock, J. A., & Mead, A. R. G. 1990, MNRAS, 244, 207

1990
[72]

1993, MNRAS, 263, 425

Miller, P., Rawlings, S., & Saunders, R. 1993, MNRAS, 263, 425

1993
[73]

2017, Nature Astronomy, 1, 596

Morganti, R. 2017, Nature Astronomy, 1, 596

2017
[74]

2021, A&A, 653, A74

Mountrichas, G., Buat, V ., Yang, G., et al. 2021, A&A, 653, A74

2021
[75]

A., Xilouris, E

Mountrichas, G., Masoura, V . A., Xilouris, E. M., et al. 2022, A&A, 661, A108

2022
[76]

2023, A&A, 675, A137

Mountrichas, G., Yang, G., Buat, V ., et al. 2023, A&A, 675, A137

2023
[77]

2015, ARA&A, 53, 365

Netzer, H. 2015, ARA&A, 53, 365

2015
[78]

G., Mobasher, B., et al

Pacifici, C., Iyer, K. G., Mobasher, B., et al. 2023, ApJ, 944, 141

2023
[79]

J., Stevens, J

Page, M. J., Stevens, J. A., Mittaz, J. P. D., & Carrera, F. J. 2001, Science, 294, 2516

2001
[80]

P., et al

Panda, S., Czerny, B., Adhikari, T. P., et al. 2018, ApJ, 866, 115

2018
[81]

2024, ApJS, 272, 11

Panda, S., Kozłowski, S., Gromadzki, M., et al. 2024, ApJS, 272, 11

2024
[82]

2023, Universe, 9, 492

Panda, S., Marziani, P., Czerny, B., Rodríguez-Ardila, A., & Pozo Nuñez, F. 2023, Universe, 9, 492

2023
[83]

L., Czerny, B., Panda, S., & Zajaˇcek, M

Pandey, A., Martínez-Aldama, M. L., Czerny, B., Panda, S., & Zajaˇcek, M. 2024, arXiv e-prints, arXiv:2401.18052

2024 arXiv
[84]

Peterson, B. M. 2008, New Astronomy Reviews, 52, 240 Article number, page 17 of 18 A&A proofs: manuscript no. SED

2008
[85]

Postma, J. E. & Leahy, D. 2017, PASP, 129, 115002

2017
[86]

2022, A&A, 667, A56 Pozo Nuñez, F., Bruckmann, C., Deesamutara, S., et al

Pouliasis, E., Mountrichas, G., Georgantopoulos, I., et al. 2022, A&A, 667, A56 Pozo Nuñez, F., Bruckmann, C., Deesamutara, S., et al. 2023, MNRAS, 522, 2002

2022
[87]

L., Lequeux, J., Maurice, E., Prevot, L., & Rocca-V olmerange, B

Prevot, M. L., Lequeux, J., Maurice, E., Prevot, L., & Rocca-V olmerange, B. 1984, A&A, 132, 389

1984
[88]

E., Crenshaw, D

Rafter, S. E., Crenshaw, D. M., & Wiita, P. J. 2011, AJ, 141, 85

2011
[89]

& Woo, J.-H

Rakshit, S. & Woo, J.-H. 2018, ApJ, 865, 5

2018
[90]

E., Hopkins, A

Randall, K. E., Hopkins, A. M., Norris, R. P., et al. 2012, MNRAS, 421, 1644

2012
[91]

2004, Monthly Notices of the Royal Astronomical Society, 353, 377

Reuland, M., R ottgering, H., Van Breugel, W., & De Breuck, C. 2004, Monthly Notices of the Royal Astronomical Society, 353, 377

2004
[92]

Richards, G. T. & Kratzer, R. 2014, in American Astronomical Society Meeting

2014
[93]

Salpeter, E. E. 1964, ApJ, 140, 796 Sánchez, S. F., Jahnke, K., Wisotzki, L., et al. 2004, ApJ, 614, 586

1964
[94]

1965, ApJ, 141, 1560

Sandage, A. 1965, ApJ, 141, 1560

1965
[95]

2005, A&A, 437, 861

Schartmann, M., Meisenheimer, K., Camenzind, M., Wolf, S., & Henning, T. 2005, A&A, 437, 861

2005
[96]

1963, Nature, 197, 1040

Schmidt, M. 1963, Nature, 197, 1040

1963
[97]

& Green, R

Schmidt, M. & Green, R. F. 1983, ApJ, 269, 352

1983
[98]

2015, A&A, 575, A74

Schreiber, C., Pannella, M., Elbaz, D., et al. 2015, A&A, 575, A74

2015
[99]

Z., Frayer, D

Scoville, N. Z., Frayer, D. T., Schinnerer, E., & Christopher, M. 2003, ApJ, 585, L105

2003
[100]

E., Strauss, M

Shen, Y ., Greene, J. E., Strauss, M. A., Richards, G. T., & Schneider, D. P. 2008, ApJ, 680, 169

2008
[101]

T., Strauss, M

Shen, Y ., Richards, G. T., Strauss, M. A., et al. 2011, ApJS, 194, 45

2011
[102]

2007, ApJ, 658, 815

Sikora, M., Stawarz, Ł., & Lasota, J.-P. 2007, ApJ, 658, 815

2007
[103]

& Nusser, A

Silk, J. & Nusser, A. 2010, ApJ, 725, 556

2010
[104]

F., Cutri, R

Skrutskie, M. F., Cutri, R. M., Stiening, R., et al. 2006, AJ, 131, 1163

2006
[105]

Stalevski, M., Fritz, J., Baes, M., Nakos, T., & Popovi ´c, L. ˇC. 2012, MNRAS, 420, 2756

2012
[106]

2016, MNRAS, 458, 2288

Stalevski, M., Ricci, C., Ueda, Y ., et al. 2016, MNRAS, 458, 2288

2016
[107]

A., Page, M

Stevens, J. A., Page, M. J., Ivison, R. J., et al. 2005, MNRAS, 360, 610

2005
[108]

A., Hill, P., Pauliny-Toth, I

Strittmatter, P. A., Hill, P., Pauliny-Toth, I. I. K., Steppe, H., & Witzel, A. 1980, A&A, 88, L12

1980
[109]

2017, A&A, 603, A127

Svoboda, J., Guainazzi, M., & Merloni, A. 2017, A&A, 603, A127

2017
[110]

G., González Delgado, R

Tadhunter, C., Robinson, T. G., González Delgado, R. M., Wills, K., & Morganti, R. 2005, MNRAS, 356, 480

2005
[111]

N., Postma, J., Joseph, P., et al

Tandon, S. N., Postma, J., Joseph, P., et al. 2020, AJ, 159, 158

2020
[112]

2019, Research in Astronomy and Astrophysics, 19, 096

Tiwari, P. 2019, Research in Astronomy and Astrophysics, 19, 096

2019
[113]

2021, Monthly Notices of the Royal Astronomical Society, 506, 2619

Torbaniuk, O., Paolillo, M., Carrera, F., et al. 2021, Monthly Notices of the Royal Astronomical Society, 506, 2619

2021
[114]

2024, MNRAS, 527, 12091

Torbaniuk, O., Paolillo, M., D’Abrusco, R., et al. 2024, MNRAS, 527, 12091

2024
[115]

J., Silverman, J

Trichas, M., Green, P. J., Silverman, J. D., et al. 2012, ApJS, 200, 17

2012
[116]

2010, MNRAS, 405, 2243

Trichas, M., Rowan-Robinson, M., Georgakakis, A., et al. 2010, MNRAS, 405, 2243

2010
[117]

1982, Advances in Space Research, 2, 241

Truemper, J. 1982, Advances in Space Research, 2, 241

1982
[118]

F., Barthelmy, S., et al

Tueller, J., Mushotzky, R. F., Barthelmy, S., et al. 2008, ApJ, 681, 113

2008
[119]

2004, ApJ, 615, L17

Walter, F., Carilli, C., Bertoldi, F., et al. 2004, ApJ, 615, L17

2004
[120]

L., Helfand, D

White, R. L., Helfand, D. J., Becker, R. H., Glikman, E., & de Vries, W. 2007, ApJ, 654, 99

2007
[121]

L., Eisenhardt, P

Wright, E. L., Eisenhardt, P. R. M., Mainzer, A. K., et al. 2010, AJ, 140, 1868

2010
[122]

2023, ApJS, 265, 37

Yamada, S., Ueda, Y ., Herrera-Endoqui, M., et al. 2023, ApJS, 265, 37

2023
[123]

N., et al

Yang, G., Boquien, M., Brandt, W. N., et al. 2022, ApJ, 927, 192

2022
[124]

2020, MNRAS, 491, 740

Yang, G., Boquien, M., Buat, V ., et al. 2020, MNRAS, 491, 740

2020
[125]

G., Adelman, J., Anderson, John E., J., et al

York, D. G., Adelman, J., Anderson, John E., J., et al. 2000, AJ, 120, 1579

2000
[126]

W., & Marziani, P

Zamfir, S., Sulentic, J. W., & Marziani, P. 2008, MNRAS, 387, 856

2008
[127]

N., Zou, F., et al

Zhu, S., Brandt, W. N., Zou, F., et al. 2023, MNRAS, 522, 3506

2023
[128]

N., Chen, C.-T., et al

Zou, F., Brandt, W. N., Chen, C.-T., et al. 2022, ApJS, 262, 15 Article number, page 18 of 18

2022

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.

[1] [1]

N., Adelman-McCarthy, J

Abazajian, K. N., Adelman-McCarthy, J. K., Agüeros, M. A., et al. 2009, ApJS, 182, 543

2009

[2] [2]

N., Dunlop, J

Archibald, E. N., Dunlop, J. S., Hughes, D. H., et al. 2001, MNRAS, 323, 417

2001

[3] [3]

Baldi, R. D. & Capetti, A. 2008, A&A, 489, 989

2008

[4] [4]

J., Bennert, V

Barth, A. J., Bennert, V . N., Canalizo, G., et al. 2015, ApJS, 217, 26

2015

[5] [5]

& Järvelä, E

Berton, M. & Järvelä, E. 2021, Universe, 7, 188

2021

[6] [6]

Best, P. N. & Heckman, T. M. 2012, MNRAS, 421, 1569

2012

[7] [7]

N., Kauffmann, G., Heckman, T

Best, P. N., Kauffmann, G., Heckman, T. M., et al. 2005, MNRAS, 362, 25

2005

[8] [8]

N., Kondapally, R., Williams, W

Best, P. N., Kondapally, R., Williams, W. L., et al. 2023, MNRAS, 523, 1729

2023