Pith. sign in

REVIEW 3 major objections 5 minor 1 cited by

The Lockman-SpReSO project. Spectroscopic analysis of Type 1 AGN

T0 review · 3 major / 5 minor · reviewed 2026-08-06 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read FIR/X-ray-selected quasars follow the same quasar main sequence

desk verdict Solid, useful sample paper with genuinely new measurements; the QMS population counts are internally inconsistent and the UV classification caveat needs a sharper statement, but the core is publishable after revision. read the letter →

arxiv 2507.01952 v1 pith:C26IXCED submitted 2025-07-02 astro-ph.GA

Castalia Alenka Negrete , Hector J. Ibarra-Medel , Erika Benitez , Irene Cruz-Gonzalez , Yair Krongold , J. Jesus Gonzalez , Jordi Cepa , Carmen Padilla-Torres
show 15 more authors
Miguel Cervino Mirjana Povic Martin Herrera-Endoqui Nancy Jenaro-Ballesteros Takamitsu Miyaji Mauricio Elias-Chavez Miguel Sanchez-Portal Bernabe Cedres Jacub Nadolny Mauro Gonzalez-Otero Bereket Assefa Hector Hernandez-Toledo J. Antonio de Diego J. Ignacio Gonzalez-Serrano A. M. Perez Garcia
This is my paper
classification astro-ph.GA
keywords activegalacticnucleiType1AGNquasarmainsequenceLockmanHoleBaldwineffectCIVwindsblackmassscalingEddingtonratio
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

This paper argues that quasars selected by their far-infrared and X-ray emission, rather than by optical brightness, occupy the same "quasar main sequence" as optically selected quasars. For 30 faint Type 1 AGN in the Lockman-SpReSO survey, the authors deblend the UV-optical broad-line regions and find $\log L_{\rm bol}$ between 44.85 and 47.87, $\log M_{\rm BH}$ between 7.59 and 9.80, and $\log R_{\rm Edd}$ between $-1.70$ and $+0.56$. Twenty-five objects are classified as Population B and five as Population A, with no extreme accretors; C IV wind centroids range from 941 to $-1587$ km s$^{-1}$, and the Baldwin effect slope is $-0.23 \pm 0.03$. A reader should care because it suggests that accretion-state demographics derived from bright optical samples are not an artifact of optical selection.

What carries the argument

The load-bearing machinery is the Quasar Main Sequence (QMS) phenomenology: an optical classification scheme, originally defined by H$\beta$ FWHM and Fe II strength, that sorts Type 1 AGN into Population A (FWHM below 4000 km s$^{-1}$, Lorentzian profiles, stronger Fe II) and Population B (Gaussian profiles, weak Fe II). To apply it to UV-only spectra, the paper uses two substitutes: a line-profile decomposition that separates a virialized broad component from blueshifted wind or very broad redshifted components, and a UV line-ratio diagram (C III]/Al III against Al III/Si III]) that places objects without H$\beta$ on the same sequence. Black hole masses are computed from Equation (1) using four single-epoch virial calibrators: VP06 for H$\beta$, TN12 for Mg II, BR23 for Al III, and M19 for C IV, each applied to the isolated broad component.

What would settle it

Obtain rest-frame optical spectra covering H$\beta$ and Fe II for the objects classified as Population B from UV data alone; if a substantial fraction show FWHM(H$\beta$) below 4000 km s$^{-1}$ and strong Fe II, placing them in Population A or the xA domain, then the claimed Population-B dominance and absence of extreme accretors would not hold.

Watch

Extended reading notes

Core claim

The central claim is that a spectroscopically faint, far-infrared and X-ray selected sample of 30 Type 1 AGN reproduces the correlations used to organize optically selected quasars. On the paper's own terms: the sample spans $\log L_{\rm bol} = 44.85$\textendash$47.87$, $\log M_{\rm BH} = 7.59$\textendash$9.80$, and $\log R_{\rm Edd} = -1.70$ to $+0.56$; 25 objects fall in Population B and 5 in Population A, with none in the extreme-accretor (xA) domain; C IV half-height centroids $c(1/2)$ are between $941$ and $-1587$ km s$^{-1}$; the Baldwin effect slope is $-0.23 \pm 0.03$; and the Eddington-ratio/FWHM anticorrelation is $\log R_{\rm Edd} = -0.17\,{\rm FWHM}_{1000}({\rm BC}) + 0.27$ with $r_p = -0.7$. The authors also recover the $R_{\rm MgII}$\textendash$R_{\rm Edd}$ relation seen in SDSS DR17 and find no variability between Lockman-SpReSO and SDSS spectra of the same objects.

Load-bearing premise

The load-bearing premise is that the Population A/B axis, defined optically by H$\beta$ FWHM and Fe II strength, can be recovered from UV-only spectra through broad-component profile shape (Lorentzian versus Gaussian), the 4000 km s$^{-1}$ FWHM boundary, and the C III]/Al III versus Al III/Si III] diagram, with single-epoch virial calibrators for Mg II, Al III, and C IV that are assumed to trace the same virialized gas at high redshift.

Editorial extensions

If this is right

  • Faint FIR/X-ray-selected Type 1 AGN are not preferentially extreme accretors; none of the 30 objects reaches the xA domain.
  • Modest C IV blueshifts, with $c(1/2)$ between 941 and $-1587$ km s$^{-1}$, imply that outflow activity in this sample resembles that of optically selected samples of similar redshift and absolute magnitude.
  • The Baldwin effect slope of $-0.23 \pm 0.03$ extends the C IV equivalent-width versus luminosity anti-correlation to a FIR/X-ray-selected population, supporting a common origin tied to the Eddington ratio.
  • The recovered $R_{\rm Edd}$\textendash FWHM(BC) anticorrelation indicates that single-epoch spectral fits can track the accretion rate in faint, high-redshift samples.
  • Agreement between Lockman-SpReSO and SDSS spectra of the same objects suggests that single-epoch classifications are stable within errors over the sampled time baseline.

Reading between the lines

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

  • If FIR and X-ray selection does not shift main-sequence demographics, then infrared-selected surveys can serve as relatively unbiased tracers of supermassive black hole accretion at high redshift; this is an extension the paper only hints at.
  • The complete absence of extreme accretors among 30 objects could be a small-sample effect or a consequence of FIR selection preferring lower-Eddington, dustier systems; a sample of order 100 objects would distinguish these alternatives.
  • The paper documents a redshift-dependent family of $R_{\rm MgII}$\textendash$R_{\rm Edd}$ relations without modeling it; a testable extension is to recalibrate Mg II Eddington ratios as a function of redshift using the SDSS DR17 data it compiled.
  • Rest-frame optical spectroscopy of the high-redshift UV-classified objects would directly test whether Lorentzian-profile Population A assignments at $z>2$ agree with H$\beta$-based classifications.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 5 minor

Summary. This paper presents a spectroscopic analysis of 30 Type 1 AGN selected from the Lockman-SpReSO survey in the FIR and X-ray, covering redshifts 0.46 < z < 4.97 and faint B-band magnitudes. The authors fit the optical-UV spectra using the Quasar Main Sequence (QMS) methodology, deblending Lyα, Si iv, C iv, the 1900 Å blend, Mg ii, and Hβ, and derive bolometric luminosities, virial black hole masses, and Eddington ratios. They assign the objects to QMS Populations A and B, find no extreme accretors, measure C iv half-height centroid shifts as a wind diagnostic, recover the Baldwin effect with slope -0.23 ± 0.03, compare 12 objects with SDSS DR17 spectra to look for variability, and perform a Galactic extinction check. The central claim is that this faint, FIR/X-ray-selected sample follows the same quasar main sequence relations as optically selected samples, with a predominantly Population B composition.

Significance. If the classification is robust, this is a valuable first systematic QMS analysis of a faint FIR/X-ray-selected Type 1 AGN sample, extending the QMS framework to the UV at z ~ 2-5 and showing that selection at long wavelengths does not produce obvious differences in the optical-UV spectroscopic eigenvector plane. The paper has several strengths: the fitting procedure is described in unusual detail, errors are propagated to the derived quantities, the authors explicitly acknowledge that the R_Edd-FWHM anti-correlation is partly constructed from the FWHM-based mass estimator, and the SDSS DR17 comparison is a good-faith cross-check. However, the headline population statistics rest on UV-only proxies for the majority of the sample, and the reported population counts are internally inconsistent across the abstract, Section 5.1, and Section 6. These issues are fixable in revision but currently prevent the paper's main quantitative claims from being accepted as they stand.

major comments (3)
  1. [§5.1; §3.1] The claim that 25 of 30 objects are Population B and none is an extreme accretor rests heavily on UV-only proxies, and for nine objects the proxy is not independent of the population definition. Section 3.1 sets the profile choice by FWHM: Lorentzian for FWHM < 4000 km/s and Gaussian for FWHM > 4000 km/s, while Section 5.1 assigns four C iv-only objects to Population A because their profile is Lorentzian and one to Population B because it is Gaussian. Since the A/B boundary is itself FWHM(Hβ) = 4000 km/s, these assignments merely restate the FWHM that also enters the virial mass estimate, rather than providing an independent UV-photoionization test. For the 18 objects placed via the C iii]/Al iii versus Al iii/Si iii] diagram the method is more defensible, but the three objects at the Population A boundary and the reliance on Marziani & Sulentic (2014) calibrators at z ~ 2-5 need a sensitivity test (e.g., FWHM-only classification, bootstrap reclassification, or stacked spectra) before the Population B dominance can be considered robust.
  2. [Abstract; §5.1; §6] The population counts are internally inconsistent. The abstract reports 18 high-z Population B, three low-z objects (A2, B1, B1+), and "the remaining eight are candidates to be Pop. B and one Pop. A object", which sums to 30 but implies a different B/A split than the text. Section 5.1's detailed enumeration gives 18 (1900-Å blend, Pop B) + 3 (Mg ii, Pop B) + 1 (C iv Gaussian, Pop B) = 22 high-z B and 4 + 1 = 5 high-z A, before adding the three low-z objects, yet ends with "25 Pop. B and 5 Pop. A objects". Section 6 states 23 high-z B and 4 high-z A, which is yet a third distribution. Please reconcile these counts and make the per-object population table available so that the summary numbers can be reproduced.
  3. [§5.1; Fig. 4] The claim that none of the 18 objects in the UV diagram lies in the xA domain cannot be checked from the paper, because the measured C iii]/Al iii and Al iii/Si iii] ratios and their errors are not reported. Please add a table (or machine-readable column) with these ratios, the adopted profile/FWHM for each object, and the resulting population and sub-population, so the boundary placement in Fig. 4 is transparent.
minor comments (5)
  1. [Abstract] The redshift range in the abstract is printed as "0.33 > z > 4.97", which has the inequality signs reversed and disagrees with the value 0.46 < z < 4.97 given in §2.1 and Table 1; please correct it.
  2. [§5.4] The phrase "with a p-value of -0.67" after Eq. (4) is presumably the Pearson correlation coefficient r, not a p-value; please rename it accordingly.
  3. [§5.5] The number of SDSS DR17 matches is inconsistent: Table 1 lists 12 objects and the abstract says 12, but §5.5 says "We found 10 of these"; please clarify how many spectra actually entered the variability comparison and why any were excluded.
  4. [§4; Table 3] Table 3 reports only an average FWHM(BC) for each object, but Eq. (1) is evaluated separately for Hβ, Mg ii, Al iii, and C iv with different calibrators; reporting the line-specific FWHM and luminosity used for each mass estimate would improve reproducibility.
  5. [§6] The summary states the Mg ii subsample as "0.462 > z > 1.956", again with inverted inequality signs; the intended range is 0.462 < z < 1.956.

Circularity Check

1 steps flagged · score 4.0 of 10

The REdd-FWHM anti-correlation (Eq. 2) is partly built into the virial MBH estimator, but the paper explicitly acknowledges this and anchors it with an independent X-ray-based relation, while the central QMS and population claims rest on external calibrations.

  1. self definitional [Section 4, Eq. (2) and following paragraph; Fig. 3 lower panel]
    "We observed a clear trend in the REdd vs. FWHM plot and derived the anti-correlation using the FWHM normalized by 1000 km s−1: logREdd = −0.17 FWHM1000(BC) + 0.27 (2) with a correlation coefficient rp=-0.7. The correlation described above is expected as the MBH that is used to compute REdd uses the FWHM values."

    By Eq. (1), log MBH = 2 log(FWHM/1000) + α log(λLλ) + β (plus a constant). Since REdd ≡ Lbol/LEdd and LEdd ∝ MBH, log REdd = log Lbol − log MBH + const, so any object-to-object change in FWHM induces an anti-correlation in log REdd through the estimator itself. The regression slope -0.17 is therefore not an independent empirical discovery; it is a transformation of the input FWHM used to construct MBH. The paper explicitly concedes this ('expected as the MBH ... uses the FWHM values') and mitigates it by citing an X-ray-mass-based relation (Marziani et al. 2001), which is external evidence.

full rationale

The paper is primarily a measurement and classification study. Bolometric luminosities are computed from continuum windows with published bolometric corrections; black hole masses use Eq. (1) with external virial calibrators (VP06, TN12, BR23, M19) that are not fitted to the present sample or to the quantities being reported. The Baldwin effect slope (−0.23 ± 0.03) is an empirical fit to EW(C IV) versus L(1350), a relation that is not forced to this value by the definition of EW alone; the paper compares it to independent literature, so it is not circular. The C IV half-height centroid wind measurements are direct spectral measurements. The Population A/B and xA classifications apply an externally established QMS taxonomy; whether that taxonomy extends reliably to UV-only spectra is a physical assumption and a correctness risk, not a logical circularity. The one genuine circular reduction is Eq. (2): because REdd is computed from MBH, which is itself derived from FWHM via Eq. (1), the observed REdd-FWHM anti-correlation is partly constructed. The authors explicitly label it 'expected' and cite an independent X-ray-based relation (Marziani et al. 2001) as external support. The centrality of this constructed correlation is limited, and the paper's other headline results retain independent empirical content, so the overall circularity score is moderate rather than severe.

Assumptions & free parameters 4 free parameters · 5 assumptions · 0 invented entities

The central claims rest on established spectral fitting methodology and literature virial calibrators rather than on new free parameters. The only numbers fitted to the data in the paper are the coefficients of the REdd-FWHM relation (Eq. 2) and the Baldwin effect relation (Eq. 4), both presented as empirical reproductions of known correlations. The principal assumptions are the validity of the QMS population classification extended to UV-only spectra and the single-epoch virial MBH estimators at high redshift.

free parameters (4)
  • REdd-FWHM slope = -0.17
    Coefficient of the log REdd vs FWHM1000 fit (Eq. 2), fitted to the LS sample; the paper acknowledges this correlation is partly built-in because REdd uses MBH derived from FWHM.
  • REdd-FWHM intercept = 0.27
    Intercept of Eq. 2, fitted to the LS sample.
  • Baldwin effect slope = -0.23 ± 0.03
    Slope of log EW(CIV) vs log L(1350) in Eq. 4, fitted to the combined S14+S17+LS samples.
  • Baldwin effect intercept = 11.75 ± 0.23
    Intercept of Eq. 4 fitted to the same combined samples.
assumptions (5)
  • standard math Concordance cosmology with H0=70 km/s/Mpc, Omega_m=0.3, Omega_Lambda=0.7 is assumed for distance and luminosity computations.
    Stated in Sec. 1.
  • domain assumption The single-epoch virial MBH estimator (Eq. 1) using Hbeta, MgII, AlIII, CIV line widths and continuum luminosities with literature calibrators yields reliable MBH for these high-z faint AGN.
    Used in Sec. 4 to derive MBH; relies on calibrators from VP06, TN12, BR23, M19, which may not be validated for the faint/high-z regime.
  • domain assumption QMS Population A/B classification defined by FWHM(Hbeta)=4000 km/s can be extended to objects without Hbeta using FWHM and line-profile proxies from CIV, MgII, Ly alpha.
    Sec. 5.1 classifies objects without optical coverage via UV line FWHM and Lorentzian/Gaussian profiles, citing Marziani et al. 2013a,b; this extrapolation is the main support for the population distribution claim.
  • domain assumption The spectral decomposition into virialized broad component, blueshifted wind component, very broad redshifted component, narrow lines with shared kinematics, and FeII templates (Bruhweiler & Verner 2008, Vestergaard & Wilkes 2001) uniquely recovers the physical components.
    Sec. 3.1 defines the decomposition; the blueshifted CIV component is the basis for the wind velocity c(1/2) measurements.
  • domain assumption CIV half-height centroid c(1/2) (Eq. 3) is a valid proxy for wind velocities in the BLR.
    Sec. 5.3 uses c(1/2) to quantify winds, following Zamfir et al. 2010.

how reviews work

0 comments
Cite this review

Pith. "Pith review of The Lockman-SpReSO project. Spectroscopic analysis of Type 1 AGN." pith.science (2026). https://pith.science/paper/C26IXCED

@misc{pith2026250701952,
  author       = {Pith},
  title        = {Pith review of: The Lockman-SpReSO project. Spectroscopic analysis of Type 1 AGN},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/C26IXCED}},
  note         = {Machine review of arXiv:2507.01952}
}
read the original abstract

We present the first optical-UV spectral systematic analysis of 30 Type 1 AGN selected in the FIR and X-ray in the Lockman-SpReSO Survey. The sample of faint objects (m_B = 19.6-21.8) covers a large redshift range of 0.33 > z > 4.97 with high S/N (~21 on average). A detailed spectral analysis based on the Quasar Main Sequence phenomenology prescription was applied to deblend the principal optical-UV emitting regions. Our sample spans a bolometric luminosity range of 44.85 < log Lbol < 47.87, absolute B-magnitude -20.46 > M_B > -26.14, BH mass of 7.59 < log MBH < 9.80, and Eddington ratio -1.70 < log REdd < 0.56. The analysis shows that 18 high-z objects correspond to Population B, whereas three low-z fall in Populations A2, B1, and B1+. The remaining eight are candidates to be Pop. B and one Pop. A object. None of them are extreme accretors. We looked for tendencies in our sample and compared them with other samples with different selection criteria. Evidence for winds was explored using CIV1549 line half-height centroid cmed finding wind velocities between 941 and -1587 kms-1. This result is consistent with samples with similar ranges of z and M_B. The Baldwin effect showed a slope of -0.23 pm 0.03 dex consistent with previous studies. Spectra from twelve objects in our sample were found in the Sloan Digital Sky Survey Data Release 17 database. We applied the same methodology to compare them to our spectra, finding no evidence of variability.

Figures

Figures reproduced from arXiv: 2507.01952 by the authors.

Figure 1
Figure 1. , where we can see a broad z distribution with a maximum of objects around z ∼ 1.8, nine objects with z > 2.4 and only three low z objects below 0.8. The 1 2 3 4 5 zspec 20 21 22 23 24 25 26 m B [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Examples of spectral fitting using Lorentzian (upper panels) and Gaussian (lower panels) profiles for Lyα, Civλ1549, 1900˚A blend, Mgiiλ2800, and Hβ. The ordinate is the restframe wavelength, while the abscissa is the flux in units 10−16 ergs s−1 cm−2 ˚A−1, considering the continuum subtracted. The thin black line represents the observed spectra, thick black lines represent the BC, blueshifted components are in blue… view at source ↗
Figure 3
Figure 3. , we cannot find a redshift dependency with the RMgII ratio for the SDSS DR17 quasars. However, we find a clear redshift dependency on the RMgII-REdd relation: the latter decreases as the redshift increases. This implies a trend in the REdd, where at lower z we find lower values of REdd, and vice versa, at higher z we have higher values of REdd. In other words, there is a family of RMgII-REdd relations dependent on … view at source ↗
Figures from the paper (2 more)
Figure 4
Figure 4. Figure 4: QMS in the optical (Upper panel) and UV Mid￾dle panel. The vertical dashed lines are the boundary for xA objects. The horizontal dashed lines are the boundary sep￾aration of Pops. A and B. Lower panel: Relation between RMgII and REdd. The meanings of the symbols are de…
Figure 5
Figure 5. Figure 5: (Upper Panel) Dependence of the velocity shift at half intensity of Civλ1549, c(1/2) on FWHM(Civλ1549). The solid line is the reference for zero velocity shift. The dashed lines represent the uncertainty range with respect to zero velocity shift. (Middle Panel) Absolut…

Discussion (0). Sign in to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. The Lockman-SpReSO Project: A Deep X-ray Spectral View of a FIR-selected AGN Population

    astro-ph.GA 2026-06 unverdicted novelty 4.0 of 10

    X-ray analysis of 94 FIR-selected AGNs at z=0.07-5 shows rising obscured fraction with redshift, soft excess in 10 sources, and a luminosity-dependent covering factor correlation supporting the receding torus model.

Reference graph

Works this paper leans on

66 extracted references · 20 canonical work pages · cited by 1 Pith paper

  1. [1]

    2022, ApJS, 259, 35, doi: 10.3847/1538-4365/ac4414

    Abdurro’uf, Accetta, K., Aerts, C., et al. 2022, ApJS, 259, 35, doi: 10.3847/1538-4365/ac4414

    doi:10.3847/1538-4365/ac4414 2022

  2. [2]

    W., et al

    Bachev, R., Marziani, P., Sulentic, J. W., et al. 2004, ApJ, 617, 171, doi: 10.1086/425210

    work page doi:10.1086/425210 2004

  3. [3]

    Baldwin, J. A. 1977, ApJ, 214, 679, doi: 10.1086/155294

    doi:10.1086/155294 1977

  4. [4]

    A., Phillips, M

    Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, PASP, 93, 5, doi: 10.1086/130766 Ben ´ ıtez, E., Ibarra-Medel, H., Negrete, C. A., et al. 2023, ApJ, 952, 45, doi: 10.3847/1538-4357/acce3e Ben ´ ıtez, E., Jim´ enez-Bail´ on, E., Negrete, C. A., et al. 2022, MNRAS, 516, 5270, doi: 10.1093/mnras/stac2244

    doi:10.1086/130766 1981

  5. [6]

    2019, A&A, 622, A103, doi: 10.1051/0004-6361/201834156

    Boquien, M., Burgarella, D., Roehlly, Y., et al. 2019, A&A, 622, A103, doi: 10.1051/0004-6361/201834156

    doi:10.1051/0004-6361/201834156 2019

  6. [7]

    A., & Green, R

    Boroson, T. A., & Green, R. F. 1992, ApJS, 80, 109, doi: 10.1086/191661

    doi:10.1086/191661 1992

  7. [8]

    2008, ApJ, 675, 83, doi: 10.1086/525557

    Bruhweiler, F., & Verner, E. 2008, ApJ, 675, 83, doi: 10.1086/525557

    doi:10.1086/525557 2008

  8. [9]

    2023, A&A, 669, A135, doi: 10.1051/0004-6361/202244177

    Dultzin, D. 2023, A&A, 669, A135, doi: 10.1051/0004-6361/202244177

    doi:10.1051/0004-6361/202244177 2023

Show all 66 references
  1. [10]

    A., Clayton, G

    Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245, doi: 10.1086/167900

    1989 doi

  2. [11]

    M., & Lockman, F

    Dickey, J. M., & Lockman, F. J. 1990, ARA&A, 28, 215, doi: 10.1146/annurev.aa.28.090190.001243

    1990

  3. [12]

    2000, ApJ, 545, 63, doi: 10.1086/317778

    Elvis, M. 2000, ApJ, 545, 63, doi: 10.1086/317778

    2000 doi

  4. [13]

    J., Hu, C., Wang, J., et al

    Ferland, G. J., Hu, C., Wang, J., et al. 2009, ApJL, 707, L82, doi: 10.1088/0004-637X/707/1/L82

    2009 doi

  5. [14]

    2012, ApJS, 198, 1, doi: 10.1088/0067-0049/198/1/1

    Fotopoulou, S., Salvato, M., Hasinger, G., et al. 2012, ApJS, 198, 1, doi: 10.1088/0067-0049/198/1/1

    2012 doi

  6. [15]

    J., Hewett, P

    Francis, P. J., Hewett, P. C., Foltz, C. B., et al. 1991, ApJ, 373, 465, doi: 10.1086/170066

    1991 doi

  7. [16]

    A., Marziani, P., et al

    Garnica, K., Negrete, C. A., Marziani, P., et al. 2022, A&A, 667, A105, doi: 10.1051/0004-6361/202142837

    2022 doi

  8. [17]

    2016, MNRAS, 462, 966, doi: 10.1093/mnras/stw1605

    Ge, X., Bian, W.-H., Jiang, X.-L., Liu, W.-S., & Wang, X.-F. 2016, MNRAS, 462, 966, doi: 10.1093/mnras/stw1605

    2016 doi

  9. [18]

    P., Cepa, J., et al

    Gonzalez-Otero, M., Padilla-Torres, C. P., Cepa, J., et al. 2023, A&A, 669, A85, doi: 10.1051/0004-6361/202244480 Gonz´ alez-Otero, M., Cepa, J., Padilla-Torres, C. P., et al. 2024, A&A, 687, A19, doi: 10.1051/0004-6361/202449238 Gr¨ unwald, G., Boller, T., Rakshit, S., et al....

    2023 doi

  10. [19]

    A., Lacerna, I., et al

    Ibarra-Medel, H., Negrete, C. A., Lacerna, I., et al. 2025, MNRAS, 536, 752, doi: 10.1093/mnras/stae2623

    2025 doi

  11. [20]

    K., & Ammon, K

    Jordi, K., Grebel, E. K., & Ammon, K. 2006, A&A, 460, 339, doi: 10.1051/0004-6361:20066082

    2006 doi

  12. [21]

    2009, A&A, 494, L25, doi: 10.1051/0004-6361:200811415

    Juarez, Y., Maiolino, R., Mujica, R., et al. 2009, A&A, 494, L25, doi: 10.1051/0004-6361:200811415

    2009 doi

  13. [22]

    2013, A&A, 549, A100, doi: 10.1051/0004-6361/201219411

    Kollatschny, W., & Zetzl, M. 2013, A&A, 549, A100, doi: 10.1051/0004-6361/201219411

    2013 doi

  14. [23]

    N., Hardcastle, M

    Kondapally, R., Best, P. N., Hardcastle, M. J., et al. 2021, A&A, 648, A3, doi: 10.1051/0004-6361/202038813 Kovaˇ cevi´ c, J., Popovi´ c, L.ˇC., & Dimitrijevi´ c, M. S. 2010, ApJS, 189, 15, doi: 10.1088/0067-0049/189/1/15

    2021 doi

  15. [24]

    M., Richards, G

    Krawczyk, C. M., Richards, G. T., Mehta, S. S., et al. 2013, ApJS, 206, 4, doi: 10.1088/0067-0049/206/1/4

    2013 doi

  16. [25]

    1994, in Astronomical Society of the Pacific Conference Series, Vol

    Kriss, G. 1994, in Astronomical Society of the Pacific Conference Series, Vol. 61, Astronomical Data Analysis Software and Systems III, ed. D. R. Crabtree, R. J. Hanisch, & J. Barnes, 437

    1994

  17. [26]

    2000, A&A, 354, 35, doi: 10.48550/arXiv.astro-ph/9911484

    Lehmann, I., Hasinger, G., Schmidt, M., et al. 2000, A&A, 354, 35, doi: 10.48550/arXiv.astro-ph/9911484

    2000 doi arXiv

  18. [27]

    J., Jahoda, K., & McCammon, D

    Lockman, F. J., Jahoda, K., & McCammon, D. 1986, ApJ, 302, 432, doi: 10.1086/164002

    1986 doi

  19. [28]

    2024, A&A, 685, A121, doi: 10.1051/0004-6361/202348535

    Loiacono, F., Decarli, R., Mignoli, M., et al. 2024, A&A, 685, A121, doi: 10.1051/0004-6361/202348535

    2024 doi

  20. [29]

    2011, A&A, 532, A90, doi: 10.1051/0004-6361/201117107 Mart ´ ınez-Aldama, M

    Lutz, D., Poglitsch, A., Altieri, B., et al. 2011, A&A, 532, A90, doi: 10.1051/0004-6361/201117107 Mart ´ ınez-Aldama, M. L., Del Olmo, A., Marziani, P., et al. 2018, Frontiers in Astronomy and Space Sciences, 4, 65, doi: 10.3389/fspas.2017.00065

    2011

  21. [30]

    Marziani, P., & Sulentic, J. W. 2014, MNRAS, 442, 1211, doi: 10.1093/mnras/stu951

    2014 doi

  22. [31]

    W., Negrete, C

    Marziani, P., Sulentic, J. W., Negrete, C. A., et al. 2010, MNRAS, 409, 1033, doi: 10.1111/j.1365-2966.2010.17357.x

    2010

  23. [32]

    2013a, ApJ, 764, 150, doi: 10.1088/0004-637X/764/2/150 16 —

    Olmo, A. 2013a, ApJ, 764, 150, doi: 10.1088/0004-637X/764/2/150 16 —. 2013b, A&A, 555, A89, doi: 10.1051/0004-6361/201321374

    doi

  24. [33]

    2009, A&A, 495, 83, doi: 10.1051/0004-6361:200810764

    Calvani, M. 2009, A&A, 495, 83, doi: 10.1051/0004-6361:200810764

    2009 doi

  25. [34]

    W., Zwitter, T., Dultzin-Hacyan, D., & Calvani, M

    Marziani, P., Sulentic, J. W., Zwitter, T., Dultzin-Hacyan, D., & Calvani, M. 2001, ApJ, 558, 553, doi: 10.1086/322286

    2001 doi

  26. [35]

    W., et al

    Marziani, P., Dultzin, D., Sulentic, J. W., et al. 2018, Frontiers in Astronomy and Space Sciences, 5, 6, doi: 10.3389/fspas.2018.00006

    2018

  27. [36]

    A., et al

    Marziani, P., del Olmo, A., Mart ´ ınez-Carballo, M. A., et al. 2019, A&A, 627, A88, doi: 10.1051/0004-6361/201935265

    2019 doi

  28. [37]

    2022, Astronomische Nachrichten, 343, e210082, doi: 10.1002/asna.20210082

    Marziani, P., Bon, E., Bon, N., et al. 2022, Astronomische Nachrichten, 343, e210082, doi: 10.1002/asna.20210082

    2022 doi

  29. [38]

    T., Del Olmo, A., Marziani, P., et al

    Mengistue, S. T., Del Olmo, A., Marziani, P., et al. 2023, MNRAS, 525, 4474, doi: 10.1093/mnras/stad2467

    2023 doi

  30. [39]

    A., Dultzin, D., Marziani, P., & Sulentic, J

    Negrete, C. A., Dultzin, D., Marziani, P., & Sulentic, J. W. 2012, ApJ, 757, 62, doi: 10.1088/0004-637X/757/1/62 —. 2013, ApJ, 771, 31, doi: 10.1088/0004-637X/771/1/31 —. 2014, ApJ, 794, 95, doi: 10.1088/0004-637X/794/1/95

    2012 doi

  31. [40]

    A., Dultzin, D., Marziani, P., et al

    Negrete, C. A., Dultzin, D., Marziani, P., et al. 2018, A&A, 620, A118, doi: 10.1051/0004-6361/201833285

    2018 doi

  32. [41]

    Osterbrock, D. E. 1981, ApJ, 249, 462, doi: 10.1086/159306

    1981 doi

  33. [42]

    2024, Frontiers in Astronomy and Space Sciences, doi: 10.3389/fspas.2024.1479874

    Panda, S. 2024, Frontiers in Astronomy and Space Sciences, doi: 10.3389/fspas.2024.1479874

    2024

  34. [43]

    L., & Zajaˇ cek, M

    Panda, S., Mart ´ ınez-Aldama, M. L., & Zajaˇ cek, M. 2019, Frontiers in Astronomy and Space Sciences, 6, 75, doi: 10.3389/fspas.2019.00075

    2019

  35. [44]

    H., Flannery, B

    Press, W. H., Flannery, B. P., & Teukolsky, S. A. 1986, Numerical recipes. The art of scientific computing (Cambridege University Press)

    1986

  36. [45]

    2023, A&A, 678, A189, doi: 10.1051/0004-6361/202346738

    Prince, R., Zajaˇ cek, M., Panda, S., et al. 2023, A&A, 678, A189, doi: 10.1051/0004-6361/202346738

    2023 doi

  37. [46]

    M., & Kallman, T

    Proga, D., Stone, J. M., & Kallman, T. R. 2000, ApJ, 543, 686, doi: 10.1086/317154

    2000 doi

  38. [47]

    1998, ARA&A, 36, 267, doi: 10.1146/annurev.astro.36.1.267

    Rauch, M. 1998, ARA&A, 36, 267, doi: 10.1146/annurev.astro.36.1.267

    1998 doi

  39. [48]

    T., Strauss, M

    Richards, G. T., Strauss, M. A., Fan, X., et al. 2006, AJ, 131, 2766, doi: 10.1086/503559

    2006 doi

  40. [49]

    T., Kruczek, N

    Richards, G. T., Kruczek, N. E., Gallagher, S. C., et al. 2011, AJ, 141, 167, doi: 10.1088/0004-6256/141/5/167

    2011 doi

  41. [50]

    2011, A&A, 529, A135, doi: 10.1051/0004-6361/201015763

    Rovilos, E., Fotopoulou, S., Salvato, M., et al. 2011, A&A, 529, A135, doi: 10.1051/0004-6361/201015763

    2011 doi

  42. [52]

    P., Schmidt, M., Hasinger, G., et al

    Schneider, D. P., Schmidt, M., Hasinger, G., et al. 1998, AJ, 115, 1230, doi: 10.1086/300307

    1998 doi

  43. [53]

    Shen, Y., & Ho, L. C. 2014, Nature, 513, 210, doi: 10.1038/nature13712

    2014 doi

  44. [54]

    2021, ApJ, 917, 107, doi: 10.3847/1538-4357/ac0adf

    Shin, J., Woo, J.-H., Nagao, T., Kim, M., & Bahk, H. 2021, ApJ, 917, 107, doi: 10.3847/1538-4357/ac0adf

    2021 doi

  45. [55]

    2007, ApJ, 666, 757, doi: 10.1086/519916

    Dultzin, D. 2007, ApJ, 666, 757, doi: 10.1086/519916

    2007 doi

  46. [56]

    W., Marziani, P., del Olmo, A., et al

    Sulentic, J. W., Marziani, P., del Olmo, A., et al. 2014, A&A, 570, A96, doi: 10.1051/0004-6361/201423975

    2014 doi

  47. [57]

    W., Marziani, P., & Dultzin-Hacyan, D

    Sulentic, J. W., Marziani, P., & Dultzin-Hacyan, D. 2000a, ARA&A, 38, 521, doi: 10.1146/annurev.astro.38.1.521

    doi

  48. [58]

    2000b, ApJL, 536, L5, doi: 10.1086/312717

    Dultzin-Hacyan, D. 2000b, ApJL, 536, L5, doi: 10.1086/312717

    doi

  49. [59]

    W., del Olmo, A., Marziani, P., et al

    Sulentic, J. W., del Olmo, A., Marziani, P., et al. 2017, A&A, 608, A122, doi: 10.1051/0004-6361/201630309

    2017 doi

  50. [60]

    2012, MNRAS, 427, 3081, doi: 10.1111/j.1365-2966.2012.22056.x Vanden Berk, D

    Trakhtenbrot, B., & Netzer, H. 2012, MNRAS, 427, 3081, doi: 10.1111/j.1365-2966.2012.22056.x Vanden Berk, D. E., Richards, G. T., Bauer, A., et al. 2001, AJ, 122, 549, doi: 10.1086/321167

    2012

  51. [61]

    Vestergaard, M., & Peterson, B. M. 2006, ApJ, 641, 689, doi: 10.1086/500572

    2006 doi

  52. [62]

    Vestergaard, M., & Wilkes, B. J. 2001, ApJS, 134, 1, doi: 10.1086/320357

    2001 doi

  53. [63]

    Wang, Y., Liu, W., Shang, Z., & Brotherton, M. S. 2022, MNRAS, 515, 5836, doi: 10.1093/mnras/stac2076

    2022 doi

  54. [64]

    2000, A&A, 358, 77, doi: 10.48550/arXiv.astro-ph/0004162

    Wisotzki, L., Christlieb, N., Bade, N., et al. 2000, A&A, 358, 77, doi: 10.48550/arXiv.astro-ph/0004162

    2000 doi arXiv

  55. [65]

    2022, ApJS, 263, 42, doi: 10.3847/1538-4365/ac9ead

    Wu, Q., & Shen, Y. 2022, ApJS, 263, 42, doi: 10.3847/1538-4365/ac9ead

    2022 doi

  56. [66]

    W., et al

    Zamanov, R., Marziani, P., Sulentic, J. W., et al. 2002, ApJL, 576, L9, doi: 10.1086/342783

    2002 doi

  57. [67]

    W., Marziani, P., & Dultzin, D

    Zamfir, S., Sulentic, J. W., Marziani, P., & Dultzin, D. 2010, MNRAS, 403, 1759, doi: 10.1111/j.1365-2966.2009.16236.x

    2010

  58. [68]

    Zheng, W., & Malkan, M. A. 1993, ApJ, 415, 517, doi: 10.1086/173182

    1993 doi

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.