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Ionized Gas Outflows in the Galaxy And Mass Assembly (GAMA) Survey: Signatures of AGN Feedback in Low-Mass Galaxies

T0 review · 3 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read Black hole winds sweep through dwarf galaxies

desk verdict Useful new catalog of 398 outflow candidates in GAMA DR4, but the low-mass AGN feedback claim rests on 15 objects with no significance tests and heavily overlapping velocity distributions. read the letter →

arxiv 2412.00880 v1 pith:CIWIAOSC submitted 2024-12-01 astro-ph.GA

Sheyda Salehirad , Amy E. Reines , Mallory Molina This is my paper · ORCID
classification astro-ph.GA
keywords galaxies:activestar-formingoutflowsevolutionlow-massAGNfeedbackGAMAsurveyW80outflowvelocities
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 searches for ionized-gas outflows in the spectra of 39,612 galaxies from the GAMA survey and identifies 398 reliable outflow candidates, including 45 low-mass galaxies with stellar masses below $10^{10}\,M_\odot$. Its central claim is that outflows in low-mass AGN/composite hosts are faster and more blueshifted than those in low-mass star-forming galaxies, which the authors read as a sign that black hole outflows can affect their host galaxies in this mass range. The upshot, if the interpretation holds, is that AGN feedback should no longer be neglected in galaxy evolution models covering low-mass and dwarf galaxies, where stellar feedback has traditionally been assumed to dominate.

What carries the argument

The central object is the [O III] $\lambda\lambda4959,5007$ doublet line profile, fitted with one- and two-Gaussian models. A second, broader Gaussian component is accepted as an outflow signature when it lowers the reduced chi-square by at least 20%, has a flux S/N $\ge$ 3, a peak at least 3$\sigma$ above the noise, and a width above instrumental resolution. Outflow speed is quantified by $W_{80}$, the velocity width containing 80% of the line flux, chosen for its lower sensitivity to dust and inclination, while the offset velocity $v_0$ between the narrow and broad components is measured separately. Host classification on the BPT diagram assigns each candidate to AGN, composite, or star-forming categories, and the AGN/composite distinction carries the paper's main comparison.

What would settle it

Spatially resolved IFU spectroscopy of the [O III] kinematics in the 45 low-mass hosts would settle whether the second components are winds: if the broad component tracks the rotation curve or vanishes beyond the nucleus, the outflow interpretation fails.

Watch

Extended reading notes

Core claim

The paper reports a systematic search for a second velocity component in the [O III] $\lambda\lambda4959,5007$ doublet across 39,612 galaxies from the GAMA survey, yielding 398 reliable outflow candidates. Among these, 45 have stellar masses $M_*<10^{10}\,M_\odot$, and a third of those are classified as AGNs or composites on the BPT diagram. The outflows in low-mass AGN/composite hosts are faster, with median $W_{80}=777$ km/s versus 609 km/s in star-forming hosts, and more blueshifted, with median offset $v_0=-46$ km/s versus $+42$ km/s. This is presented as evidence that black hole outflows can affect low-mass host galaxies and that AGN feedback should be considered in galaxy evolution models for $M_*<10^{10}\,M_\odot$.

Load-bearing premise

The broad second component in [O III] is assumed to be an outflow rather than beam smearing, disk rotation, biconical geometry, or a merger-inflated line.

Editorial extensions

If this is right

  • AGN feedback should be treated as a viable channel in galaxy evolution models for $M_*<10^{10}\,M_\odot$, not only in massive galaxies.
  • The 398 outflow candidates, only eight of which have SDSS spectra, enlarge the census of ionized outflows in the GAMA fields and provide new targets for follow-up study.
  • Because roughly 97% of AGN/composite outflows have $W_{80}>500$ km/s, the paper concludes these outflows carry enough energy to be AGN-driven rather than starburst-driven.
  • The higher incidence of outflows among AGNs/composites, about 89% of the sample, supports earlier findings that AGN activity is a more common outflow driver than star formation.

Reading between the lines

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

  • Because the low-mass AGN and star-forming outflow samples are not matched in stellar mass and redshift, a matched comparison is needed to confirm that the $W_{80}$ and $v_0$ differences trace AGN activity rather than host properties.
  • The roughly 9% of candidates with double-peaked or similar-width components could be disk rotation or biconical geometry rather than winds; if so, excluding them would shift the median velocities, and spatially resolved follow-up could quantify the contamination.
  • Detecting molecular or neutral-gas outflows in the same 45 low-mass galaxies would test whether the ionized outflows carry enough mass and energy to actually quench or enhance star formation in dwarfs.
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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

3 major / 5 minor

Summary. This paper presents a systematic search for ionized-gas outflow signatures in the [O III] lambda-lambda 4959,5007 doublet in 39,612 GAMA DR4 galaxies with z<0.3, yielding 398 candidates after visual inspection, of which 45 have stellar masses below 10^10 M_sun. The authors fit one- and two-Gaussian models to the doublet, classify the hosts using BPT diagrams, measure W80 and offset velocities, estimate virial black hole masses from broad H-alpha detections, and compare outflow properties between AGN/composite and star-forming hosts, with particular attention to the low-mass regime. They report that low-mass AGN/composite outflows are faster and more blueshifted than those in low-mass star-forming galaxies and conclude that AGN feedback should be considered in galaxy evolution models for M*<10^10 M_sun.

Significance. The outflow catalog is a useful community resource: the parent-sample selection is transparent, every candidate is visually inspected, and the electronic tables provide per-object velocities, fluxes, and classifications. If the low-mass comparison is robust, the paper would supply needed evidence that AGN-driven ionized outflows exist in the M*<10^10 M_sun regime and should be incorporated into feedback models. However, the headline inference currently rests on 15 AGN/composite galaxies versus 29 star-forming galaxies, with overlapping velocity distributions and no significance tests, confidence intervals, or comparison of the mass and redshift distributions of the two groups; the claim is therefore not yet established at the strength stated in the abstract and conclusions.

major comments (3)
  1. [Section 4.5, Figure 10] The central claim that low-mass AGN/composite outflows are faster and more blueshifted than those in star-forming galaxies is not supported by a statistical test. The reported medians of W80 = 777 km/s (n=15) versus 609 km/s (n=29) and offset velocities of -46 versus +42 km/s are quoted without uncertainties, and Figures 10a and 10c show strongly overlapping distributions. A two-sample test such as the Mann-Whitney U or a permutation test, with bootstrap confidence intervals for the medians, should be reported for both quantities. If the differences are not significant, the conclusions in Sections 4.5 and 5 must be softened accordingly.
  2. [Section 4.5] The low-mass AGN/composite subsample is entirely drawn from the broad-line-selected Salehirad et al. (2022) sample, while the star-forming subsample is selected solely by BPT classification. The manuscript does not compare the stellar-mass or redshift distributions of the two low-mass groups, even though spectral resolution, signal-to-noise ratio, and host mass can all affect fitted W80 values. A matched analysis, or an explicit demonstration that the two groups have comparable mass and redshift distributions, is needed before the velocity difference can be attributed to AGN activity rather than to selection or resolution effects.
  3. [Sections 3.2 and 5] The interpretation of the second Gaussian component as an outflow is qualified by the paper's own statements that non-Gaussian profiles can result from beam smearing of velocity gradients and that about 9% of candidates are double-peaked lines possibly associated with NLR disk rotation, biconical outflows, or merging AGNs. Given the small size of the low-mass AGN sample, a sensitivity check that excludes the double-peaked candidates, or otherwise quantifies how much of the reported low-mass velocity difference survives removal of these ambiguous cases, is needed to ensure that the comparison cleanly measures outflows.
minor comments (5)
  1. [Section 3, first paragraph] The phrase 'beam-spearing' should read 'beam smearing'.
  2. [Section 3.4 and Table 2] The [O I] line is labeled lambda6003 in the text but lambda6300 in the table caption and elsewhere; the correct wavelength is 6300 Angstroms.
  3. [Abstract] The word 'F eedback' in the abstract should be 'Feedback'.
  4. [Figure 3 caption] Panel (e) is described both as a two-peak example and as a broad blueshifted example; the caption should be corrected so each of the six panels is described once and consistently.
  5. [Section 2.1] The statement that GAMA is 'two magnitudes deeper than the SDSS' would benefit from a citation or a quantitative definition of the magnitude limit comparison.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: outflow velocities are direct fit outputs, AGN/SF classification uses external BPT demarcations, and the one self-citation is not load-bearing.

full rationale

The paper's central quantities are measured, not derived from the conclusions. Outflow candidates are selected by fitting one- and two-Gaussian models to [O III] and requiring a 20% reduced-chi-squared improvement, broader second component, S/N >= 3, and peak >= 3-sigma above noise (Section 3.2); W80 and offset velocity are then direct outputs of those fits (Sections 3.3 and 4.3). AGN/composite versus star-forming classification uses the external BPT demarcation lines of Kewley et al. (2006) and Kauffmann et al. (2003), not a parameter fitted in this paper. The 500 km/s threshold is attributed to Fabian (2012), an external benchmark. The low-mass comparison in Section 4.5 (median W80 777 versus 609 km/s, median offset -46 versus +42 km/s) compares independently measured quantities; no equation in the paper reduces one median to the other. The only self-citation is the statement in Section 4.5 that 'All the AGNs/composites are among the Salehirad et al. (2022) sample,' but the current AGN/composite labels come from the paper's own BPT analysis and the outflow velocities are measured here, so this citation is not load-bearing for the velocity comparison. The acknowledged possibility that some second components are rotation or double-peaked NLR structure is a modeling-interpretation caveat, not a circularity. Overall, the analysis is self-contained as an observational measurement study.

Assumptions & free parameters 2 free parameters · 5 assumptions · 0 invented entities

The central claim depends on classification and selection thresholds more than on fitted physical parameters. The key unvalidated premise is that every fitted second component is an outflow; the authors themselves list alternative kinematic interpretations. The low-mass AGN subsample is small (15 objects) and inherits BPT incompleteness.

free parameters (2)
  • Two-Gaussian model selection threshold = reduced chi2 improvement of at least 20%
    Adopted by hand (Section 3.2) to decide when a second velocity component is real; directly controls which galaxies enter the outflow sample and therefore the median velocities reported.
  • Minimum second-component S/N and peak significance = S/N >= 3; peak >= 3 sigma above rms
    Chosen to reject noise fits (Section 3.2); inherited from prior work but hand-set, and affects detectability of broad components, particularly in fainter SF galaxies.
assumptions (5)
  • domain assumption A second Gaussian component in [O III] traces a distinct kinematic component, generally an outflow
    Used throughout; the paper itself notes in Section 3 that non-Gaussian profiles can also result from beam smearing of velocity gradients (Garcia-Lorenzo et al. 2015) and that double-peaked lines may indicate NLR rotation or mergers (Section 5).
  • domain assumption BPT emission-line ratios separate AGN photoionization from star formation in this sample
    Used to classify hosts (Section 4.1); the authors acknowledge in Section 4.5 that low-metallicity AGNs can overlap with starbursts, making low-mass classification incomplete.
  • standard math The W80 to FWHM relation for a Gaussian (W80 = 1.09 FWHM)
    Used in Section 3.3 to convert fitted Gaussian widths into outflow velocities.
  • domain assumption GAMA stellar masses and redshifts are reliable
    Parent sample construction uses GAMA DMU values (Section 2.2); no independent cross-check is provided.
  • domain assumption The 500 km/s W80 threshold indicates AGN-driven outflows
    Inherited from Fabian (2012) and used in Sections 4.3.1 and 5 to argue that most AGN outflows are AGN-driven; external benchmark, not derived here.

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Cite this review

Pith. "Pith review of Ionized Gas Outflows in the Galaxy And Mass Assembly (GAMA) Survey: Signatures of AGN Feedback in Low-Mass Galaxies." pith.science (2026). https://pith.science/paper/CIWIAOSC

@misc{pith2026241200880,
  author       = {Pith},
  title        = {Pith review of: Ionized Gas Outflows in the Galaxy And Mass Assembly (GAMA) Survey: Signatures of AGN Feedback in Low-Mass Galaxies},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/CIWIAOSC}},
  note         = {Machine review of arXiv:2412.00880}
}
abstract

We present a sample of 398 galaxies with ionized gas outflow signatures in their spectra from the Galaxy and Mass Assembly (GAMA) Survey Data Release 4, including 45 low-mass galaxies with stellar masses $M_*<10^{10}$ $M_\odot$. We assemble our sample by systematically searching for the presence of a second velocity component in the [O III]$\lambda\lambda 4959, 5007$ doublet emission line in 39,612 galaxies with redshifts $z<0.3$. The host galaxies are classified using the BPT diagram, with $\sim$89% identified as AGNs and composites and 11% as star-forming (SF) galaxies. The outflows are typically faster in AGNs with a median velocity of 936 km s$^{-1}$ compared to 655 km s$^{-1}$ in the SF objects. Of particular interest are the 45 galaxies in the low-mass range, of which a third are classified as AGNs/composites. The outflows from the low-mass AGNs are also faster and more blueshifted compared to those in the low-mass SF galaxies. This indicates that black hole outflows can affect host galaxies in the low-mass range and that AGN feedback in galaxies with $M_*<10^{10}$ $ M_\odot$ should be considered in galaxy evolution models.

Figures

Figures reproduced from arXiv: 2412.00880 by the authors.

Figure 1
Figure 1. An example of stellar continuum fit (AGN with CATAID 518451). Here the redshift-corrected spectrum is shown in black and the best-fitted stellar continuum model is in blue. See Section 3.1 for details. We also find a handful of AGN-dominated spectra among the flagged galaxies in which the stellar templates do not provide an optimal fit to the continuum. How￾ever, since we include a linear component in the fit of the… view at source ↗
Figure 2
Figure 2. [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Examples of the [O III]λλ4959, 5007 doublet line profiles from our outflow sample, fitted using two-Gaussian models. The color scheme matches that of [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figures from the paper (7 more)
Figure 4
Figure 4. Figure 4: This plot illustrates an example of W80 ∼ FWHM (dashed gray lines) for the outflow component (green line) from the [O III]λ5007 emission, indicating outflow ve￾locity. See Section 3.3 for details. We also fit Gaussian models to the [S II]λλ6716, 6731, [N II]+Hα, Hβ, an…
Figure 5
Figure 5. Figure 5: This figure shows chunks of emission-line spectra for Hβ, [O I]λ6003, [N II]+Hα complex, and the [S II]λλ6716, 6731 lines. The color scheme matches that of [PITH_FULL_IMAGE:figures/full_fig_p008_5.png]
Figure 6
Figure 6. Figure 6: The left panel shows the [O III]/Hβ vs. [N II]/Hα narrow-line diagnostic diagram for our outflow candidates in the GAMA survey using the classification scheme summarized in Kewley et al. (2006). Here 394/398 of the outflow galaxies with reliable emission lines relevant…
Figure 7
Figure 7. Figure 7: Distributions of Broad Hα emission parameters and BH mass. Panels (a) and (b) display the histograms of the FWHM and log luminosity of the broad Hα component for AGNs shown in maroon, and SF galaxies shown in blue. Virial BH mass distribution for the broad-line AGNs is…
Figure 8
Figure 8. Figure 8: Outflow properties. (a)–(b): Distributions of outflow velocity (vout) and offset velocity (vo) for the BPT-AGNs and composites in our outflow sample shown in maroon histograms. The medians of outflow velocity and offset velocity are 936 km s −1 and −84 km s−1 , respect…
Figure 9
Figure 9. Figure 9: Host galaxy properties for the outflow candidates. (a)–(c): Panels (a) and (b) show the distributions of host galaxy stellar mass and redshift (hashed maroon histograms) for AGNs/composites. Our parent sample (normalized to the number of outflow galaxies) is also shown…
Figure 10
Figure 10. Figure 10: Same as [PITH_FULL_IMAGE:figures/full_fig_p013_10.png]

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Works this paper leans on

111 extracted references · 9 canonical work pages

  1. [1]

    M., Swinbank, A

    Alexander, D. M., Swinbank, A. M., Smail, I., McDermid, R., & Nesvadba, N. P. H. 2010, MNRAS, 402, 2211, doi: 10.1111/j.1365-2966.2009.16046.x Angl´ es-Alc´ azar, D., Faucher-Gigu` ere, C.-A., Quataert, E., et al. 2017, MNRAS, 472, L109, doi: 10.1093/mnrasl/slx161

    arXiv 2010

  2. [2]

    2023, ApJ, 950, 33, doi: 10.3847/1538-4357/acca7c Astropy Collaboration, Robitaille, T

    Aravindan, A., Liu, W., Canalizo, G., et al. 2023, ApJ, 950, 33, doi: 10.3847/1538-4357/acca7c Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ ocz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f

    work page doi:10.3847/1538-4357/acca7c 2023

  3. [3]

    2016, ApJ, 828, 97, doi: 10.3847/0004-637X/828/2/97

    Bae, H.-J., & Woo, J.-H. 2016, ApJ, 828, 97, doi: 10.3847/0004-637X/828/2/97

    doi:10.3847/0004-637x/828/2/97 2016

  4. [4]

    F., Reines, A

    Baldassare, V. F., Reines, A. E., Gallo, E., et al. 2016, ApJ, 829, 57, doi: 10.3847/0004-637X/829/1/57

    doi:10.3847/0004-637x/829/1/57 2016

  5. [6]

    K., Liske, J., Brown, M

    Baldry, I. K., Liske, J., Brown, M. J. I., et al. 2018, MNRAS, 474, 3875, doi: 10.1093/mnras/stx3042

    doi:10.1093/mnras/stx3042 2018

  6. [7]

    A., Phillips, M

    Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, PASP, 93, 5, doi: 10.1086/130766

    doi:10.1086/130766 1981

  7. [8]

    2016, A&A, 585, A148, doi: 10.1051/0004-6361/201526694

    Balmaverde, B., Marconi, A., Brusa, M., et al. 2016, A&A, 585, A148, doi: 10.1051/0004-6361/201526694

    work page doi:10.1051/0004-6361/201526694 2016

  8. [9]

    Barai, P., & de Gouveia Dal Pino, E. M. 2019, MNRAS, 487, 5549, doi: 10.1093/mnras/stz1616

    doi:10.1093/mnras/stz1616 2019

Show all 111 references
  1. [10]

    J., Greene, J

    Barth, A. J., Greene, J. E., & Ho, L. C. 2008, AJ, 136, 1179, doi: 10.1088/0004-6256/136/3/1179

    2008 doi

  2. [11]

    P., Robotham, A

    Bellstedt, S., Driver, S. P., Robotham, A. S. G., et al. 2020, MNRAS, 496, 3235, doi: 10.1093/mnras/staa1466

    2020 doi

  3. [12]

    J., Bower, R

    Benson, A. J., Bower, R. G., Frenk, C. S., et al. 2003, ApJ, 599, 38, doi: 10.1086/379160

    2003 doi

  4. [13]

    2022, MNRAS, 516, 3092, doi: 10.1093/mnras/stac2439

    Bizyaev, D., Chen, Y.-M., Shi, Y., et al. 2022, MNRAS, 516, 3092, doi: 10.1093/mnras/stac2439

    2022 doi

  5. [15]

    D., Geha, M

    Bradford, J. D., Geha, M. C., Greene, J. E., Reines, A. E., & Dickey, C. M. 2018, ApJ, 861, 50, doi: 10.3847/1538-4357/aac88d

    2018 doi

  6. [16]

    2003, MNRAS, 344, 1000, doi: 10.1046/j.1365-8711.2003.06897.x

    Bruzual, G., & Charlot, S. 2003, MNRAS, 344, 1000, doi: 10.1046/j.1365-8711.2003.06897.x

    2003

  7. [17]

    2017, MNRAS, 466, 798, doi: 10.1093/mnras/stw3020

    Cappellari, M. 2017, MNRAS, 466, 798, doi: 10.1093/mnras/stw3020

    2017 doi

  8. [18]

    2015, A&A, 580, A102, doi: 10.1051/0004-6361/201526557

    Carniani, S., Marconi, A., Maiolino, R., et al. 2015, A&A, 580, A102, doi: 10.1051/0004-6361/201526557

    2015 doi

  9. [19]

    2014, A&A, 569, A14, doi: 10.1051/0004-6361/201323296

    Cazzoli, S., Arribas, S., Colina, L., et al. 2014, A&A, 569, A14, doi: 10.1051/0004-6361/201323296

    2014 doi

  10. [20]

    2005, MNRAS, 363, L91, doi: 10.1111/j.1745-3933.2005.00093.x

    Churazov, E., Sazonov, S., Sunyaev, R., et al. 2005, MNRAS, 363, L91, doi: 10.1111/j.1745-3933.2005.00093.x

    2005

  11. [21]

    2018, Nature Astronomy, 2, 176, doi: 10.1038/s41550-018-0406-3

    Cicone, C., Brusa, M., Ramos Almeida, C., et al. 2018, Nature Astronomy, 2, 176, doi: 10.1038/s41550-018-0406-3

    2018 doi

  12. [22]

    2012, A&A, 543, A99, doi: 10.1051/0004-6361/201218793

    Cicone, C., Feruglio, C., Maiolino, R., et al. 2012, A&A, 543, A99, doi: 10.1051/0004-6361/201218793

    2012 doi

  13. [23]

    2014, A&A, 562, A21, doi: 10.1051/0004-6361/201322464

    Cicone, C., Maiolino, R., Sturm, E., et al. 2014, A&A, 562, A21, doi: 10.1051/0004-6361/201322464

    2014 doi

  14. [24]

    M., & Vestergaard, M

    Collin, S., Kawaguchi, T., Peterson, B. M., & Vestergaard, M. 2006, A&A, 456, 75, doi: 10.1051/0004-6361:20064878

    2006 doi

  15. [25]

    2017, A&A, 606, A36, doi: 10.1051/0004-6361/201629519

    Concas, A., Popesso, P., Brusa, M., et al. 2017, A&A, 606, A36, doi: 10.1051/0004-6361/201629519

    2017 doi

  16. [26]

    F., & Dunn, J

    Mushotzky, R. F., & Dunn, J. P. 2010, ApJ, 708, 419, doi: 10.1088/0004-637X/708/1/419

    2010 doi

  17. [27]

    2015, A&A, 582, A63, doi: 10.1051/0004-6361/201526581

    Cresci, G., Marconi, A., Zibetti, S., et al. 2015, A&A, 582, A63, doi: 10.1051/0004-6361/201526581

    2015 doi

  18. [29]

    2018, MNRAS, 473, 5698, doi: 10.1093/mnras/stx2716

    Hartwig, T. 2018, MNRAS, 473, 5698, doi: 10.1093/mnras/stx2716

    2018 doi

  19. [30]

    L., F¨ orster Schreiber, N

    Davies, R. L., F¨ orster Schreiber, N. M.,¨Ubler, H., et al. 2019, ApJ, 873, 122, doi: 10.3847/1538-4357/ab06f1

    2019 doi

  20. [31]

    P., Bellstedt, S., Robotham, A

    Driver, S. P., Bellstedt, S., Robotham, A. S. G., et al. 2022, MNRAS, 513, 439, doi: 10.1093/mnras/stac472

    2022 doi

  21. [32]

    2013, The Messenger, 154, 32

    Edge, A., Sutherland, W., Kuijken, K., et al. 2013, The Messenger, 154, 32

    2013

  22. [33]

    L., Wong, T., S´ anchez, S

    Ellison, S. L., Wong, T., S´ anchez, S. F., et al. 2021, MNRAS, 505, L46, doi: 10.1093/mnrasl/slab047

    2021 doi

  23. [34]

    Everett, J. E. 2005, ApJ, 631, 689, doi: 10.1086/432678

    2005 doi

  24. [35]

    Fabian, A. C. 2012, ARA&A, 50, 455, doi: 10.1146/annurev-astro-081811-125521

    2012 doi

  25. [36]

    2000, ApJL, 539, L9, doi: 10.1086/312838

    Ferrarese, L., & Merritt, D. 2000, ApJL, 539, L9, doi: 10.1086/312838

    2000 doi

  26. [37]

    2010, A&A, 518, L155, doi: 10.1051/0004-6361/201015164

    Feruglio, C., Maiolino, R., Piconcelli, E., et al. 2010, A&A, 518, L155, doi: 10.1051/0004-6361/201015164

    2010 doi

  27. [38]

    V., & Sargent, W

    Filippenko, A. V., & Sargent, W. L. W. 1988, ApJ, 324, 134, doi: 10.1086/165886 —. 1989, ApJL, 342, L11, doi: 10.1086/185472

    1988 doi

  28. [39]

    2021, MNRAS, 505, 5753, doi: 10.1093/mnras/stab1666

    Fluetsch, A., Maiolino, R., Carniani, S., et al. 2021, MNRAS, 505, 5753, doi: 10.1093/mnras/stab1666

    2021 doi

  29. [40]

    2023, MNRAS, 524, 5827, doi: 10.1093/mnras/stad2214 Garc ´ ıa-Lorenzo, B., M´ arquez, I., Barrera-Ballesteros, J

    Fu, Y., Cappellari, M., Mao, S., et al. 2023, MNRAS, 524, 5827, doi: 10.1093/mnras/stad2214 Garc ´ ıa-Lorenzo, B., M´ arquez, I., Barrera-Ballesteros, J. K., et al. 2015, A&A, 573, A59, doi: 10.1051/0004-6361/201423485 17

    2023 doi

  30. [41]

    E., Tremonti, C., Diamond-Stanic, A

    Geach, J. E., Tremonti, C., Diamond-Stanic, A. M., et al. 2018, ApJL, 864, L1, doi: 10.3847/2041-8213/aad8b6

    2018 doi

  31. [42]

    2000, ApJL, 539, L13, doi: 10.1086/312840

    Gebhardt, K., Bender, R., Bower, G., et al. 2000, ApJL, 539, L13, doi: 10.1086/312840

    2000 doi

  32. [43]

    A., Owers, M

    Gordon, Y. A., Owers, M. S., Pimbblet, K. A., et al. 2017, MNRAS, 465, 2671, doi: 10.1093/mnras/stw2925

    2017 doi

  33. [44]

    E., & Ho, L

    Greene, J. E., & Ho, L. C. 2004, ApJ, 610, 722, doi: 10.1086/421719 —. 2005, ApJ, 627, 721, doi: 10.1086/430590

    2004 doi

  34. [46]

    2021, MNRAS, 502, 3618, doi: 10.1093/mnras/stab245

    Guolo-Pereira, M., Ruschel-Dutra, D., Storchi-Bergmann, T., et al. 2021, MNRAS, 502, 3618, doi: 10.1093/mnras/stab245

    2021 doi

  35. [47]

    Swinbank, A. M. 2014, MNRAS, 441, 3306, doi: 10.1093/mnras/stu515

    2014 doi

  36. [49]

    M., Alexander, D

    Harrison, C. M., Alexander, D. M., Mullaney, J. R., et al. 2016, MNRAS, 456, 1195, doi: 10.1093/mnras/stv2727

    2016 doi

  37. [50]

    Butcher, H. R. 1981, ApJ, 247, 403, doi: 10.1086/159050

    1981 doi

  38. [51]

    M., & Thompson, T

    Heckman, T. M., & Thompson, T. A. 2017, arXiv e-prints, arXiv:1701.09062, doi: 10.48550/arXiv.1701.09062 Hermosa Mu˜ noz, L., M´ arquez, I., Cazzoli, S., Masegosa, J., & Ag ´ ıs-Gonz´ alez, B. 2022, A&A, 660, A133, doi: 10.1051/0004-6361/202142629

    2017 doi arXiv

  39. [52]

    2012, MNRAS, 427, 146, doi: 10.1111/j.1365-2966.2012.21952.x

    Heymans, C., Van Waerbeke, L., Miller, L., et al. 2012, MNRAS, 427, 146, doi: 10.1111/j.1365-2966.2012.21952.x

    2012

  40. [53]

    J., & Zakamska, N

    Hill, M. J., & Zakamska, N. L. 2014, MNRAS, 439, 2701, doi: 10.1093/mnras/stu123

    2014 doi

  41. [54]

    C., Filippenko, A

    Ho, L. C., Filippenko, A. V., & Sargent, W. L. W. 1997, ApJ, 487, 568, doi: 10.1086/304638

    1997 doi

  42. [55]

    F., Hernquist, L., Cox, T

    Hopkins, P. F., Hernquist, L., Cox, T. J., et al. 2006, ApJS, 163, 1, doi: 10.1086/499298

    2006 doi

  43. [56]

    Hunter, J. D. 2007, Computing in Science Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

    2007 doi

  44. [57]

    M., Tremonti, C., et al

    Kauffmann, G., Heckman, T. M., Tremonti, C., et al. 2003, MNRAS, 346, 1055, doi: 10.1111/j.1365-2966.2003.07154.x

    2003

  45. [58]

    J., Dopita, M

    Kewley, L. J., Dopita, M. A., Sutherland, R. S., Heisler, C. A., & Trevena, J. 2001, ApJ, 556, 121, doi: 10.1086/321545

    2001 doi

  46. [59]

    J., Groves, B., Kauffmann, G., & Heckman, T

    Kewley, L. J., Groves, B., Kauffmann, G., & Heckman, T. 2006, MNRAS, 372, 961, doi: 10.1111/j.1365-2966.2006.10859.x

    2006

  47. [60]

    Kormendy, J., & Ho, L. C. 2013, ARA&A, 51, 511, doi: 10.1146/annurev-astro-082708-101811

    2013 doi

  48. [61]

    1995, ARA&A, 33, 581, doi: 10.1146/annurev.aa.33.090195.003053

    Kormendy, J., & Richstone, D. 1995, ARA&A, 33, 581, doi: 10.1146/annurev.aa.33.090195.003053

    1995

  49. [62]

    A., & Sijacki, D

    Koudmani, S., Henden, N. A., & Sijacki, D. 2021, MNRAS, 503, 3568, doi: 10.1093/mnras/stab677

    2021 doi

  50. [63]

    A., & Smith, M

    Koudmani, S., Sijacki, D., Bourne, M. A., & Smith, M. C. 2019, MNRAS, 484, 2047, doi: 10.1093/mnras/stz097

    2019 doi

  51. [64]

    2019, A&A, 625, A2, doi: 10.1051/0004-6361/201834918

    Kuijken, K., Heymans, C., Dvornik, A., et al. 2019, A&A, 625, A2, doi: 10.1051/0004-6361/201834918

    2019 doi

  52. [65]

    K., Driver, S

    Liske, J., Baldry, I. K., Driver, S. P., et al. 2015, MNRAS, 452, 2087, doi: 10.1093/mnras/stv1436

    2015 doi

  53. [66]

    2020, ApJ, 905, 166, doi: 10.3847/1538-4357/abc269

    Liu, W., Veilleux, S., Canalizo, G., et al. 2020, ApJ, 905, 166, doi: 10.3847/1538-4357/abc269

    2020 doi

  54. [67]

    M., Canalizo, G., & Sales, L

    Manzano-King, C. M., Canalizo, G., & Sales, L. V. 2019, ApJ, 884, 54, doi: 10.3847/1538-4357/ab4197

    2019 doi

  55. [68]

    Marconi, A., & Hunt, L. K. 2003, ApJL, 589, L21, doi: 10.1086/375804

    2003 doi

  56. [69]

    1998, ApJ, 504, 27, doi: 10.1086/306080 Mart ´ ın-Navarro, I., & Mezcua, M

    Markevitch, M. 1998, ApJ, 504, 27, doi: 10.1086/306080 Mart ´ ın-Navarro, I., & Mezcua, M. 2018, ApJL, 855, L20, doi: 10.3847/2041-8213/aab103

    1998 doi

  57. [70]

    L., et al

    Matzko, W., Satyapal, S., Ellison, S. L., et al. 2022, MNRAS, 514, 4828, doi: 10.1093/mnras/stac1506

    2022 doi

  58. [71]

    G., Schaye, J., Ponman, T

    McCarthy, I. G., Schaye, J., Ponman, T. J., et al. 2010, MNRAS, 406, 822, doi: 10.1111/j.1365-2966.2010.16750.x

    2010

  59. [72]

    J., & Ma, C.-P

    McConnell, N. J., & Ma, C.-P. 2013, ApJ, 764, 184, doi: 10.1088/0004-637X/764/2/184

    2013 doi

  60. [73]

    2010, in Proceedings of the 9th Python in Science Conference, Vol

    McKinney, W., et al. 2010, in Proceedings of the 9th Python in Science Conference, Vol. 445, Austin, TX, 51–56

    2010

  61. [74]

    2006, ApJ, 647, 753, doi: 10.1086/505528

    Salimbeni, S. 2006, ApJ, 647, 753, doi: 10.1086/505528

    2006 doi

  62. [75]

    2021, ApJ, 922, 155, doi: 10.3847/1538-4357/ac1ffa

    Salehirad, S. 2021, ApJ, 922, 155, doi: 10.3847/1538-4357/ac1ffa

    2021 doi

  63. [76]

    C., Shahinyan, K., Sugarman, H

    Moran, E. C., Shahinyan, K., Sugarman, H. R., V´ elez, D. O., & Eracleous, M. 2014, AJ, 148, 136, doi: 10.1088/0004-6256/148/6/136

    2014 doi

  64. [77]

    2017, Frontiers in Astronomy and Space Sciences, 4, 42, doi: 10.3389/fspas.2017.00042

    Morganti, R. 2017, Frontiers in Astronomy and Space Sciences, 4, 42, doi: 10.3389/fspas.2017.00042

    2017

  65. [78]

    R., Alexander, D

    Mullaney, J. R., Alexander, D. M., Fine, S., et al. 2013, MNRAS, 433, 622, doi: 10.1093/mnras/stt751 M¨ uller-S´ anchez, F., Comerford, J. M., Nevin, R., et al. 2015, ApJ, 813, 103, doi: 10.1088/0004-637X/813/2/103

    2013 doi

  66. [79]

    1995, ApJL, 454, L105, doi: 10.1086/309775 18

    Murray, N., & Chiang, J. 1995, ApJL, 454, L105, doi: 10.1086/309775 18

    1995 doi

  67. [80]

    M., M¨ uller-S´ anchez, F., Barrows, R., & Cooper, M

    Nevin, R., Comerford, J. M., M¨ uller-S´ anchez, F., Barrows, R., & Cooper, M. C. 2018, MNRAS, 473, 2160, doi: 10.1093/mnras/stx2433

    2018 doi

  68. [81]

    B., & Ingargiola, A

    Newville, M., Stensitzki, T., Allen, D. B., & Ingargiola, A. 2014, LMFIT: Non-Linear Least-Square Minimization and Curve-Fitting for Python, 0.8.0, Zenodo, doi: 10.5281/zenodo.11813

    2014 doi

  69. [82]

    J., Masters, K

    Penny, S. J., Masters, K. L., Smethurst, R., et al. 2018, MNRAS, 476, 979, doi: 10.1093/mnras/sty202

    2018 doi

  70. [83]

    2018, A&A, 616, A171, doi: 10.1051/0004-6361/201833089

    Pereira-Santaella, M., Colina, L., Garc ´ ıa-Burillo, S., et al. 2018, A&A, 616, A171, doi: 10.1051/0004-6361/201833089

    2018 doi

  71. [84]

    Pogge, R. W. 1989, ApJ, 345, 730, doi: 10.1086/167945

    1989 doi

  72. [85]

    2007, ApJ, 661, 693, doi: 10.1086/515389

    Proga, D. 2007, ApJ, 661, 693, doi: 10.1086/515389

    2007 doi

  73. [86]

    Reines, A. E. 2022, Nature Astronomy, 6, 26, doi: 10.1038/s41550-021-01556-0

    2022 doi

  74. [87]

    E., Greene, J

    Reines, A. E., Greene, J. E., & Geha, M. 2013, ApJ, 775, 116, doi: 10.1088/0004-637X/775/2/116

    2013 doi

  75. [88]

    J., McGurk, R

    Rosario, D. J., McGurk, R. C., Max, C. E., et al. 2011, ApJ, 739, 44, doi: 10.1088/0004-637X/739/1/44

    2011 doi

  76. [89]

    2018, Galaxies, 6, 138, doi: 10.3390/galaxies6040138

    Rupke, D. 2018, Galaxies, 6, 138, doi: 10.3390/galaxies6040138

    2018 doi

  77. [90]

    S., Veilleux, S., & Sanders, D

    Rupke, D. S., Veilleux, S., & Sanders, D. B. 2002, ApJ, 570, 588, doi: 10.1086/339789 —. 2005, ApJS, 160, 115, doi: 10.1086/432889

    2002 doi

  78. [91]

    Rupke, D. S. N., & Veilleux, S. 2011, ApJL, 729, L27, doi: 10.1088/2041-8205/729/2/L27 —. 2013, ApJ, 768, 75, doi: 10.1088/0004-637X/768/1/75

    2011 doi

  79. [92]

    E., & Molina, M

    Salehirad, S., Reines, A. E., & Molina, M. 2022, ApJ, 937, 7, doi: 10.3847/1538-4357/ac8876

    2022 doi

  80. [93]

    F., Schawinski, K., Treister, E., et al

    Sartori, L. F., Schawinski, K., Treister, E., et al. 2015, MNRAS, 454, 3722, doi: 10.1093/mnras/stv2238

    2015 doi

  81. [94]

    2004, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol

    Saunders, W., Bridges, T., Gillingham, P., et al. 2004, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 5492, Ground-based Instrumentation for Astronomy, ed. A. F. M. Moorwood & M. Iye, 389–400, doi: 10.1117/12.550871

    2004 doi

  82. [95]

    A., Bower, R

    Schaye, J., Crain, R. A., Bower, R. G., et al. 2015, MNRAS, 446, 521, doi: 10.1093/mnras/stu2058

    2015 doi

  83. [96]

    Schutte, Z., & Reines, A. E. 2022, Nature, 601, 329, doi: 10.1038/s41586-021-04215-6

    2022 doi

  84. [97]

    S., Brooks, A

    Sharma, R. S., Brooks, A. M., Somerville, R. S., et al. 2020, ApJ, 897, 103, doi: 10.3847/1538-4357/ab960e

    2020 doi

  85. [98]

    2006, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol

    Sharp, R., Saunders, W., Smith, G., et al. 2006, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 6269, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, ed. I. S. McLean & M. Iye, 62690G, doi: 10.1117/12.671022

    2006 doi

  86. [99]

    E., & Strauss, M

    Shen, Y., Liu, X., Greene, J. E., & Strauss, M. A. 2011, ApJ, 735, 48, doi: 10.1088/0004-637X/735/1/48

    2011 doi

  87. [100]

    2013, ApJ, 772, 112, doi: 10.1088/0004-637X/772/2/112

    Silk, J. 2013, ApJ, 772, 112, doi: 10.1088/0004-637X/772/2/112

    2013 doi

  88. [101]

    Silk, J., & Rees, M. J. 1998, A&A, 331, L1, doi: 10.48550/arXiv.astro-ph/9801013

    1998 doi arXiv

  89. [102]

    2004, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol

    Smith, G., Brzeski, J., Miziarski, S., et al. 2004, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 5495, Astronomical Structures and Mechanisms Technology, ed. J. Antebi & D. Lemke, 348–359, doi: 10.1117/12.551004

    2004 doi

  90. [103]

    S., Hopkins, P

    Somerville, R. S., Hopkins, P. F., Cox, T. J., Robertson, B. E., & Hernquist, L. 2008, MNRAS, 391, 481, doi: 10.1111/j.1365-2966.2008.13805.x

    2008

  91. [104]

    2005, MNRAS, 361, 776, doi: 10.1111/j.1365-2966.2005.09238.x

    Springel, V., Di Matteo, T., & Hernquist, L. 2005, MNRAS, 361, 776, doi: 10.1111/j.1365-2966.2005.09238.x

    2005

  92. [105]

    1976, ApJL, 205, L113, doi: 10.1086/182102

    Stockton, A. 1976, ApJL, 205, L113, doi: 10.1086/182102

    1976 doi

  93. [106]

    N., Hopkins, A

    Taylor, E. N., Hopkins, A. M., Baldry, I. K., et al. 2011, MNRAS, 418, 1587, doi: 10.1111/j.1365-2966.2011.19536.x

    2011

  94. [107]

    2018, MNRAS, 478, 5607, doi: 10.1093/mnras/sty1406

    Trebitsch, M., Volonteri, M., Dubois, Y., & Madau, P. 2018, MNRAS, 478, 5607, doi: 10.1093/mnras/sty1406

    2018 doi

  95. [108]

    2002, ApJ, 574, 740, doi: 10.1086/341002

    Tremaine, S., Gebhardt, K., Bender, R., et al. 2002, ApJ, 574, 740, doi: 10.1086/341002

    2002 doi

  96. [109]

    2005, ARA&A, 43, 769, doi: 10.1146/annurev.astro.43.072103.150610

    Veilleux, S., Cecil, G., & Bland-Hawthorn, J. 2005, ARA&A, 43, 769, doi: 10.1146/annurev.astro.43.072103.150610

    2005 arXiv

  97. [110]

    D., & Aalto, S

    Veilleux, S., Maiolino, R., Bolatto, A. D., & Aalto, S. 2020, A&A Rv, 28, 2, doi: 10.1007/s00159-019-0121-9

    2020 doi

  98. [111]

    Veilleux, S., & Osterbrock, D. E. 1987, ApJS, 63, 295, doi: 10.1086/191166

    1987 doi

  99. [112]

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

    2006 doi

  100. [113]

    2014, MNRAS, 444, 1518, doi: 10.1093/mnras/stu1536

    Vogelsberger, M., Genel, S., Springel, V., et al. 2014, MNRAS, 444, 1518, doi: 10.1093/mnras/stu1536

    2014 doi

  101. [114]

    2018, Nature Astronomy, 2, 181, doi: 10.1038/s41550-018-0409-0

    Wylezalek, D., & Morganti, R. 2018, Nature Astronomy, 2, 181, doi: 10.1038/s41550-018-0409-0

    2018 doi

  102. [115]

    L., & Greene, J

    Zakamska, N. L., & Greene, J. E. 2014, MNRAS, 442, 784, doi: 10.1093/mnras/stu842

    2014 doi

  103. [116]

    2013, MNRAS, 433, 3079, doi: 10.1093/mnras/stt952

    Zubovas, K., Nayakshin, S., King, A., & Wilkinson, M. 2013, MNRAS, 433, 3079, doi: 10.1093/mnras/stt952

    2013 doi

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