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Quiescent Host Galaxies of Extended Quasars Revealed by Spectrophotometric Decomposition

T0 review · 5 major / 6 minor · reviewed 2026-08-03 · deepseek-v4-flash

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Pith's one-line read This paper argues that most quasars with extended optical morphologies at redshifts 0.1–1 are hosted by quiescent, old-stellar-population galaxies—about 83% quiescent and 23% post-starburst—contrary to the star-forming hosts typical of comp

desk verdict First large systematic look at extended quasar hosts at z<1 finds them mostly quiescent, but the headline fractions rest on selection and model-internal SFR validation. read the letter →

arxiv 2607.28732 v1 pith:HKJXRW3Z submitted 2026-07-30 astro-ph.GA astro-ph.IM

Shengxiu Sun , Linhua Jiang , Zhiwei Pan , Mal gorzata Siudek , Mar Mezcua , Gaocheng Yin , Swayamtrupta Panda , Wei-Jian Guo
show 22 more authors
Steven Ahlen David Brooks Todd Claybaugh Axel de la Macorra Peter Doel Enrique Gaztañaga Gaston Gutierrez Theodore Kisner Andrew Lambert Martin Landriau Aaron Meisner Ramon Miquel John Moustakas Ignasi Pérez-Ráfols Eusebio Sanchez David Schlegel Michael Schubnell Hee-Jong Seo David Sprayberry Gregory Tarlé Benjamin Alan Weaver Rongpu Zhou
This is my paper · ORCID
classification astro-ph.GAastro-ph.IM
keywords AGNhostgalaxiesActivegalacticnucleiQuasarsSupermassiveblackholesQuiescentPost-starburstExtendedquasarmorphologySpectrophotometricdecomposition
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

At intermediate redshifts (0.1 < z < 1), quasars whose host galaxies are resolved in optical images are often assumed to resemble the compact quasars studied before—actively star-forming. This paper argues the opposite for extended quasars. By fitting images and spectra together, it separates the bright point-like quasar from the surrounding galaxy and finds that roughly 83% of the hosts are quiescent and about 23% are post-starburst, meaning they recently stopped forming stars and now show strong hydrogen absorption. The hosts are massive and old, and the central black holes follow the local black-hole–stellar-mass relation. If right, this shows that low-redshift quasar hosts are more diverse than earlier samples suggested, with extended morphology selecting a later, quenched evolutionary stage.

What carries the argument

The central mechanism is an iterative spectrophotometric decomposition: five-band optical imaging is fit with a point-source component plus a generalized elliptical surface-brightness profile, and photometry of the residual image gives the host-to-quasar flux ratio in each band. These image-derived ratios are used as priors when fitting the quasar spectrum, which is modeled as an AGN component (broken power-law continuum, blended iron pseudo-continuum, hydrogen emission lines) plus a host stellar component with a star-formation history divided into age bins. Host and AGN are refit alternately until derived parameters change by less than 5%, breaking the usual degeneracy between the featurele

What would settle it

Generate mock extended quasars with a stellar-population library, dust prescription, and star-formation histories different from the one used in the fitting, then run the decomposition; if the recovered quiescent and post-starburst fractions shift by more than the quoted statistical uncertainties, the classification is template-dependent. Observationally, measure star formation in a subset of the same hosts with an indicator that bypasses template fitting—such as resolved H-alpha emission or far-infrared/radio continuum—and compare the resulting fractions.

Watch

Extended reading notes

Core claim

On the paper's own terms, the discovery is that the host galaxies of extended quasars at 0.1<z<1 are mainly quiescent: about 83% have log sSFR < -10.94, and about 23% satisfy post-starburst criteria (strong H-delta absorption, HδA > 4 Å, together with log sSFR < -10.94). The hosts are massive—median stellar mass near 10^10.6 solar masses—with old stellar populations and red colors, and the sample is clearly bimodal in star-formation rate, with no substantial population on the star-forming main sequence. Black-hole masses measured from the decomposed quasar light track host stellar mass with a slope broadly consistent with local relations once systematic uncertainties are included, while the

Load-bearing premise

The quiescent and post-starburst classifications depend on the assumed star-formation-history templates, dust law, and priors used to model the host spectra; the mock tests are generated with the same model family, so they validate internal consistency, not absolute accuracy of the derived star-formation rates.

Editorial extensions

If this is right

  • A previously undercounted population of active black holes resides in passive galaxies, so AGN activity and strong star formation are not necessarily simultaneous in low-redshift quasars.
  • The 23% post-starburst share implies that a substantial subset of extended quasars is caught shortly after a burst of star formation was shut off, making them direct laboratories for quenching and feedback.
  • The host stellar masses peak near 10^10.6 solar masses and match the mass function of quiescent galaxies, so selecting extended morphology effectively selects massive, structurally evolved, quenched hosts.
  • The black-hole–stellar-mass relation in this sample is consistent with local relations once systematic uncertainties are included, arguing against strong redshift evolution in this restricted population.
  • The absence of a measurable black-hole–velocity-dispersion relation here should not be read as a physical absence, because the same large uncertainties flatten a known input relation in mock tests.

Reading between the lines

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

  • Editorial inference: the 83% and 23% figures are conditional on the morphological selection and do not apply to compact quasars; the combined picture suggests a diversity axis tied to host structure rather than only luminosity or redshift.
  • Editorial inference: the same decomposition procedure could be applied to other imaging-plus-spectroscopy AGN samples to map how the quiescent fraction varies with host size and bulge prominence, with a testable prediction that it rises with effective radius.
  • Editorial inference: the inferred sequence—star-forming compact hosts giving way to post-starburst extended hosts and then to quiescent hosts—could be tested with spatially resolved stellar-population ages, which should show younger cores or tidal features in the post-starburst systems.
  • Editorial inference: if real hosts contain dusty or nebular emission not captured by the template family, the quiescent fraction would be overestimated; resolving this requires star-formation indicators that bypass template fitting, such as infrared luminosity, resolved H-alpha, or radio continuum.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

5 major / 6 minor

Summary. The paper presents a spectrophotometric decomposition technique that jointly fits DESI spectra and Subaru HSC images for 1126 type 1 quasars at 0.1<z<1 with extended optical morphologies. The key claims are that the host galaxies of these extended quasars are predominantly quiescent (83% with log sSFR<−10.94), that a large fraction (23%) show post-starburst signatures (HδA>4 Å and log sSFR<−10.94), and that the host stellar masses and the MBH–M⋆ relation are broadly consistent with local scaling relations. The method iterates between an AGN spectral model (power-law continuum, Fe pseudo-continuum, Balmer continuum, Gaussian emission lines) and a Bagpipes non-parametric SFH stellar population model, using GalfitM photometric decomposition as a prior. Mock tests are used to argue that the decomposition recovers AGN luminosities, host SFRs, and stellar velocity dispersions with acceptable fidelity.

Significance. If the central claims hold, the paper would add an important data point to the quasar-host co-evolution debate: a sizable population of low-redshift quasars with quiescent and post-starburst hosts, complementing the well-studied compact quasars whose hosts are star-forming. The sample size (1126 objects) is substantial for spectroscopically decomposed quasar hosts, and the joint use of imaging priors with spectral fitting is a genuinely useful methodological direction. The paper is also honest in acknowledging that the morphological selection pre-selects a particular host population. However, the quantitative headline fractions (83% quiescent, 23% post-starburst) are only as reliable as the SFR calibration, and the current validation is not strong enough to support them at face value. The MBH–M⋆ analysis is more robust and less dependent on the disputed SFR values.

major comments (5)
  1. [Sec. 4, Fig. 9] The SFR recovery test that underpins the quiescent/post-starburst classification contains only N=8 'confident recoveries,' and the mocks are generated with Bagpipes (plus Galsim) and then fitted with Bagpipes. This demonstrates template self-consistency, not external accuracy. The real sample is concentrated at log sSFR<−10.5 (Fig. 12), but no recovery statistics are shown for that low-sSFR regime. If the pipeline systematically biases weak hosts toward even lower sSFR, the 83% and 23% fractions would be inflated. I recommend adding an independent calibration—e.g., mock galaxies from a different SPS code (or with a different dust/nebular prescription) and reporting recovery rates as a function of input sSFR, including upper-limit behavior.
  2. [Sec. 5.2/5.4, Fig. 12] The 83% quiescent fraction appears to include objects whose sSFRs are upper limits: Fig. 12 explicitly states that points in the shaded region 'only indicate upper limits,' and this shaded region covers the low-sSFR area where the quiescent population lies. Treating upper limits as detections can artificially boost the quiescent fraction. The paper should report the quiescent fraction both with and without upper limits, or use a survival-analysis estimator, and state how many of the 1126 objects are non-detections in SFR.
  3. [Sec. 2.3/5.4] The sample is selected to have 'non-psf' (extended) morphologies in the Legacy Survey and to be bright (λLλ(5100 Å)>10^43.3 erg s−1). As the paper itself notes, extended morphology is correlated with large effective radius, high stellar mass, and quiescence. The comparison with previous compact-quasar studies is therefore not apples-to-apples: the claim that extended quasar hosts are 'quite different' from compact quasar hosts conflates selection with a physical difference. To make the comparison meaningful, the authors should at least match the two populations in redshift, AGN luminosity, and host stellar mass, or explicitly frame the result as characterizing a pre-selected morphological class rather than as evidence for diversity among quasars in general.
  4. [Sec. 5.3, Fig. 15] The post-starburst criterion (HδA>4 Å and log sSFR<−10.94) is measured on decomposed host spectra, but no mock test is presented for HδA recovery in the presence of residual AGN contamination. The Lick index is sensitive to continuum placement and to any residual AGN power-law or emission-line leakage. Given that the 23% post-starburst fraction is one of the two central quantitative claims, the paper should validate HδA recovery on mocks with injected AGN at the actual host-fraction and S/N distributions of the sample, and show how the fraction changes under reasonable continuum-placement uncertainties.
  5. [Sec. 6.1, Fig. 17] The MBH–M⋆ slope recovery test is constructed by generating mock galaxies that follow the local relation and then injecting the same systematic uncertainties (σsys,M⋆=0.2 dex, σsys,MBH=0.3 dex) that are used in the ODR fit. This is not an independent validation of the fitted slope; it shows that a steep input relation can survive these uncertainties, not that the data themselves require a steep relation. The paper should also present the best-fit slope without the adopted systematic floors, or a sensitivity analysis over a range of floor values, so the reader can see how much of the 'consistency with local relations' is built into the uncertainty model.
minor comments (6)
  1. [Abstract/Introduction] The phrase 'extended objects' should be defined precisely at first use; it is only fully explained in Sec. 2.3. Also 'Mgii' and 'Caii' are typeset inconsistently (Mgii, Caii, CaI, Mgi) throughout; standard 'Mg II'/'Ca II' would be clearer.
  2. [Sec. 2.1] The sentence 'its spectra were reduced with pipeline from Guy et al. (2023)' should be 'with the pipeline from Guy et al. (2023).' Similarly, 'The Signal-to-Noise ratios (S/N) of the spectra are calculated as flux divided by the flux error (converted from ivar), which is 1σ value' is awkward and should be rephrased.
  3. [Sec. 3.1] The 20% systematic error floor is motivated, but it is not stated whether the 20% is applied in quadrature to the statistical errors or as a multiplicative fractional error in the likelihood. This should be clarified for reproducibility.
  4. [Sec. 4/Appendix B] The text says 'Statistical analysis for the decomposition results of the second mock dataset is displayed in Appendix A (Figure B1)' but the figure appears in Appendix B. The cross-reference should be corrected.
  5. [Fig. 15] The color bar in the upper panel is labeled 'AGN Density' while the panel shows sSFR on the y-axis; the color scale presumably encodes black hole mass (as stated in the caption), so the label is confusing and should be corrected.
  6. [Sec. 5.1] The virial mass calibration uses a=6.91 from Ho & Kim (2015). Since the host galaxy decomposition changes the continuum luminosity, the authors should state whether the systematic uncertainty in the virial factor is propagated into the MBH errors used in the scaling-relation fits. This is relevant to the claimed 1σ agreement with local relations.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the headline quiescent/post-starburst fractions are measurements on real data with independent color, absorption-line, and control-sample support; no fitted parameter is renamed as a prediction and no load-bearing self-citation is used.

full rationale

The central derivation is not circular. Host sSFR and HδA values are fitted to real DESI spectra and HSC images through an iterative AGN+host decomposition; the headline 83% quiescent and 23% post-starburst fractions are then obtained by applying fixed literature thresholds (log sSFR < -10.94 and HδA > 4 Å) to those fitted values. No parameter is fitted to the headline fractions and then reported as a prediction, and no equation reduces one claimed result to another by construction. The Section 4 mock tests are generated with Bagpipes+Galsim and fitted with the same Bagpipes non-parametric SFH family, so they establish internal self-consistency of the pipeline rather than external accuracy of the SPS templates; this is a validation limitation, not a circular step, because the mock inputs are not the real data and the real-data conclusions are not derived from the mock outputs. Independent evidence supports the classification: the decomposed AGN continuum follows the canonical Hα-L5100 relation (Fig. 11); the host CMD shows red old populations (Fig. 13); the stacked post-starburst spectra show strong Balmer and Ca II absorption (Fig. 15b,c); and an SDSS AGN control sample yields a ~1.2% post-starburst fraction versus 23% for the extended-host sample (Fig. 15a). The sample's morphological pre-selection is explicitly acknowledged as biasing toward quiescent hosts (Sec. 5.4), so it is a stated selection effect rather than a hidden circularity. The self-citations present (e.g., Guo et al. 2018 for PyQSOFit; Siudek et al. 2024 for SED-fitting uncertainties) are code or general-context citations and are not load-bearing. Therefore, under the required quote-and-reduction standard, no circular step is present.

Assumptions & free parameters 5 free parameters · 6 assumptions · 0 invented entities

The paper introduces no new physical entities. Its central results rest on a chain of modeling assumptions: the Bagpipes template library and SFH priors, the PSF+Sérsic imaging decomposition, the binary emission/absorption attribution, and the virial MBH calibration. The mock tests use the same model family to generate and fit host galaxies, so they validate internal consistency, not external accuracy. Several hand-chosen thresholds and systematic error floors directly set the headline numbers.

free parameters (5)
  • Virial MBH calibration constant a = 6.91 ± 0.02
    Adopted from Ho & Kim (2015), Eq. 2; sets the zero point of every black hole mass and hence the MBH–Mstar comparison.
  • Systematic uncertainty floors in ODR fit = σ_sys,M* = 0.2 dex, σ_sys,MBH = 0.3 dex
    Chosen in Section 6.1 and added in quadrature; these choices transform the fitted MBH–Mstar slope (0.93 global, 1.37 dense core) and are central to the claim of consistency with local relations.
  • Host photometry systematic error floor = 20%
    Applied in Section 3.1 to GalfitM host photometry; controls how strongly the photometric prior constrains the Bagpipes host fit.
  • Quiescent / post-starburst thresholds = log sSFR = −10.94 yr⁻¹; HδA = 4 Å
    Adopted from Dodd et al. (2021) in Section 5.3; directly determines the reported 83% quiescent and 23% post-starburst fractions.
  • Bagpipes SFH setup = 14 age bins, student-t prior
    Model choice in Section 3.2; the derived SFRs and sSFRs, and thus the quiescence classification, depend on this prior.
assumptions (6)
  • domain assumption Bagpipes stellar population synthesis templates and non-parametric SFH priors represent the true stellar populations of quasar host galaxies.
    Sections 3.2/5.2: SFR and stellar mass are outputs of Bagpipes; no independent calibration such as emission-line or radio SFR is used.
  • domain assumption The HSC PSF model is accurate and the central AGN is unresolved, so a PSF+Sérsic decomposition separates AGN and host light.
    Section 3.1: the imaging decomposition relies on this to produce the photometric priors.
  • domain assumption All emission lines are attributed to the AGN and all absorption lines to the host galaxy.
    Section 3.2: if this binary attribution fails, host SFRs and velocity dispersions could be biased.
  • domain assumption The virial BH mass estimator with the Ho & Kim (2015) calibration is valid for this sample.
    Section 5.1, Eq. 2: all MBH values and the MBH–Mstar relation depend on this external calibration.
  • ad hoc to paper Mock validation using Bagpipes-generated galaxies establishes reliability of recovered SFRs.
    Section 4: the mock host galaxies are generated with Bagpipes and Galsim and then fitted with Bagpipes, so the test is internally consistent rather than externally calibrated.
  • domain assumption The 1.5 arcsec aperture photometry on PSF-subtracted images faithfully represents host flux inside the DESI fiber, within the 20% error floor.
    Section 3.1: the photometric priors constrain the spectral host normalization; if the aperture is biased, the host-to-AGN flux ratio is biased.

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Cite this review

Pith. "Pith review of Quiescent Host Galaxies of Extended Quasars Revealed by Spectrophotometric Decomposition." pith.science (2026). https://pith.science/paper/HKJXRW3Z

@misc{pith2026260728732,
  author       = {Pith},
  title        = {Pith review of: Quiescent Host Galaxies of Extended Quasars Revealed by Spectrophotometric Decomposition},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/HKJXRW3Z}},
  note         = {Machine review of arXiv:2607.28732}
}
abstract

Previous works of low-redshift quasar host galaxies have focused on compact quasars and found that their host galaxies are mainly star-forming galaxies. Here we present a study of host galaxies for quasars with extended morphologies in ground-based optical images. We select a sample of more than 1000 type 1 quasars at redshift $0.1<z<1$ that are classified as extended objects by DESI. Combining high-resolution spectra from DESI and high-quality images from Subaru HSC, we develop a spectrophotometric decomposition technique to iteratively decompose each quasar into an AGN component and its host galaxy. The technique can effectively break the degeneracy between the AGN and host components and capture the host spectral features. Our results show that the host galaxies of most quasars have low star-formation rates (SFRs) and low specific SFRs, indicating that they are quiescent galaxies. Many of them exhibit prominent post-starburst features with the existence of significant old stellar populations. These properties are quite different from the nature of compact quasars with star-forming host galaxies. In addition, the relation between the black hole mass and stellar mass for our sample is broadly consistent with the canonical local relations. This work is complementary to the previous studies and suggests that the host galaxies of low-redshift quasars are more diverse than what was thought.

Figures

Figures reproduced from arXiv: 2607.28732 by the authors.

Figure 1
Figure 1. Redshift and luminosity distributions of our sample of DESI quasars with extended morphologies, color-coded by the estimated MBH. The majority of the sample is at z < 0.6. The luminosity is represented by the monochromatic luminosity at 5100˚A, which is derived from the DESI spectra. 2017; Dey et al. 2019) and tested to be robust through validation (e.g., Chaussidon et al. 2023). Several meth￾ods were applied for qu… view at source ↗
Figure 2
Figure 2. Flowchart explaining how our pipeline works. This is a concise demonstration for the fitting iterations. Details are provided in Section 3.2. pipeline optimized for galaxy morphology characteriza￾tion, to provide the initial morphological values. This second iteration significantly improves the host galaxy model. To break the spectral degeneracy, we utilize these imaging decomposition results to constrain the host g… view at source ↗
Figure 3
Figure 3. Representative example of the imaging decomposition with GalfitM on a quasar at z = 0.51. The images from top to bottom are HSC g, r, i, z, y five broadband images, respectively. The image size is about 8′′ on a side. The five columns from left to right show the following information: (1) observed HSC images; (2) the constructed GalfitM best-fitting models consisting of a point source plus a single S´ersic host gala… view at source ↗
Figures from the paper (13 more)
Figure 4
Figure 4. Figure 4: Example of spectrophotometric fitting results for four quasar host galaxies. The blue solid line shows the original observed spectrum. The magenta densely dotted and dark orange densely dotted lines indicate the decomposed host galaxy spectrum and AGN model spectrum, r…
Figure 5
Figure 5. Figure 5: Demonstration of the decomposed host galaxy spectra. The grey lines represent our final spectral results of the spectrophotometric decomposition method and the yellow lines represent the corresponding Bagpipes galaxy models. We highlight the important absorption line f…
Figure 6
Figure 6. Figure 6 [PITH_FULL_IMAGE:figures/full_fig_p011_6.png]
Figure 7
Figure 7. Figure 7: Recovery of the embedded host galaxy spectra in the second mock data set using our spectrophotometric decompo￾sition pipeline. Input spectra combine simulated pure galaxy observation and quasar templates. Here we show four examples which are located at different redshi…
Figure 8
Figure 8. Figure 8: Validation of the recovered AGN monochromatic fluxes at 3000 ˚A (top row) and 5100 ˚A (bottom row) using our mock dataset. Left panels: Comparison between the input and recovered AGN fluxes. The dashed lines represent the one-to-one relations. Right panels: Logarithmic…
Figure 9
Figure 9. Figure 9: Comparison of the input host galaxy SFRs against the recovered SFRs from our mock dataset. The dashed line represents the one-to-one relation. The recovered SFRs are generally consistent with the input values across the sample. 10 15 20 25 30 35 40 Spectral S/N 0.4 0.2…
Figure 10
Figure 10. Figure 10: Logarithmic residuals (∆ log σ⋆) of the recovered host galaxy stellar velocity dispersion as a function of the input spectral S/N. Data points are color-coded by the host galaxy flux fraction. The binned median of the recovered distribution is shown as a solid blue cu…
Figure 12
Figure 12. Figure 12: Distribution of our quasars in the SFR − M⋆ plane. The overlaid black contours represent the 2D ker￾nel density estimate, highlighting a distinct bimodal sepa￾ration within the host galaxy population. The data points in the shaded region only indicate upper limits. We…
Figure 14
Figure 14. Figure 14: Distribution of our DESI quasars in the M⋆−σ⋆ plane, color-coded by the black hole mass. The majority of our DESI quasar hosts have relatively large stellar masses, and a wide spread range of M⋆ and σ⋆. lar populations are old, with inactive star formation (mainly bel…
Figure 15
Figure 15. Figure 15: Absorption line features and sSFRs. Upper panel: Distribution of our quasar hosts in the log(sSFR) versus HδA plane. Data points are color-coded by black hole mass (log MBH/M⊙). Grey contours show the density dis￾tribution of an SDSS AGN control sample (MPA-JHU cat￾al…
Figure 16
Figure 16. Figure 16: The MBH − M⋆ relation for our sample of 1083 quasars with extended morphology. The upper panel is color￾coded by sSFR, and the lower panel is color-coded by the density of the quasar distribution. The solid purple line shows the relation at 1 < z < 2 from Ding et al. …
Figure 17
Figure 17. Figure 17: MBH − M⋆ distribution for a sample of mock galaxies that follow the local relation. The upper panel only considers the intrinsic scatter/uncertainty, and the lower panel includes all the measurement uncertainties. Notations are the same as those in [PITH_FULL_IMAGE:f…
Figure 18
Figure 18. Figure 18: MBH−σ⋆ relation for our quasars. The pentacles show our quasar sample color-coded by sSFR of the host galaxies. The mean errors are plotted in the bottom left corner of the two panels. We plot the classical MBH − σ⋆ relation for local dormant galaxies from Kormendy & …

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