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arxiv: 2606.25367 · v1 · pith:RASZYB37new · submitted 2026-06-24 · 🌌 astro-ph.GA

A Statistical Study of HI Gas in AGN-Hosting and Satellite Galaxies from ALFALFA and FASHI

Shuanghao Shu , Wenkai Hu , Junqiang Ge , Jinjiang Yu , Wenxiu Yang , Furen Deng , Yichao Li , Yougang Wang
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Xuelei Chen
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Pith reviewed 2026-06-25 21:27 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords AGN feedbackHI gas fractionsatellite galaxiesstar formation rateenvironmental quenchinggroup environmentsALFALFA survey
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The pith

AGN feedback suppresses HI gas and star formation in satellite galaxies even at the virial radius.

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

The paper compares HI gas fractions and star formation rates between AGN-hosting satellite galaxies and normal satellites without AGN, using data from ALFALFA, FASHI, SDSS, and DESI surveys. It finds that AGN hosts show gas fractions and SFRs roughly ten times lower than non-AGN counterparts at all group-centric distances, including out to the halo virial radius. The radial profiles remain flat rather than showing the expected environmental gradients, leading the authors to conclude that internal AGN feedback depletes cold gas first and environmental processes act later. The apparent gas excess at small radii is attributed to beam confusion rather than real accretion.

Core claim

AGN-hosting satellites exhibit a significant and persistent deficit in both gas fraction and SFR relative to normal satellites without AGN, even at the halo virial radius (R/R180 approx 1). This suggests that cold gas depletion is primarily driven by internal AGN feedback before these galaxies experience intense environmental interactions. The relatively flat radial profiles of gas fraction and sSFR further indicate that the evolution of AGN-hosting satellites is governed by internal physical processes rather than environmental interactions.

What carries the argument

Comparison of HI gas fraction and specific star formation rate as functions of projected group-centric radius (R/R180) for AGN-classified versus non-AGN satellite galaxies.

If this is right

  • Internal AGN feedback operates as the dominant quenching channel for gas-rich satellites before they enter dense group environments.
  • Environmental processes such as ram-pressure stripping become secondary for galaxies that already host AGN.
  • Flat radial trends imply that the observed gas depletion does not strengthen with proximity to the group center for AGN hosts.
  • Beam confusion must be accounted for when interpreting central HI measurements in single-dish surveys.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If AGN feedback precedes environmental effects, models of satellite quenching should incorporate an early internal phase that sets the gas reservoir before infall.
  • Future HI surveys with higher angular resolution could test whether the central gas upturn disappears once beam confusion is removed.
  • The result raises the question of whether AGN activity itself is triggered by the same processes that later drive environmental quenching or arises independently.

Load-bearing premise

Optical spectroscopy from SDSS and DESI accurately identifies AGN hosts without substantial misclassification that could create the observed gas deficits.

What would settle it

Repeating the radial gas-fraction analysis on a sample where AGN classification is independently verified by X-ray or mid-infrared diagnostics instead of optical lines.

Figures

Figures reproduced from arXiv: 2606.25367 by Furen Deng, Jinjiang Yu, Junqiang Ge, Shuanghao Shu, Wenkai Hu, Wenxiu Yang, Xuelei Chen, Yichao Li, Yougang Wang.

Figure 1
Figure 1. Figure 1: The BPT diagnostic diagram for the sample galaxies. The vertical axis shows the [PITH_FULL_IMAGE:figures/full_fig_p008_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Histograms of the SNR (top left), integrated H [PITH_FULL_IMAGE:figures/full_fig_p013_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Histogram of the angular separations between H [PITH_FULL_IMAGE:figures/full_fig_p014_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Correlations among M∗, MHI , SFR and sSFR. (a): M∗ − MHI ; (b): M∗−SFR; (c): MHI−SFR; (d): M∗ − MHI/M∗; (e): M∗−sSFR ; (f): MHI−sSFR. The gray and blue contours represent the normalized density distributions of star-forming and composite galaxies. The contours represent the bivariate nuclear density estimation (KDE) for the control samples (e.g., star-forming and composite galaxies). Respectively, with red… view at source ↗
Figure 5
Figure 5. Figure 5: HI Gas fraction MHI /M∗ as function of u − r (panel a), log(O + H) + 12 (panel b), log σ∗ (panel c), log µ∗ (panel d). The gray and blue contours represent the normalized density distributions of star￾forming and composite galaxies, respectively, with red points indicating individual AGN systems. The black solid line shows the median trend of the AGN systems, with dot symbols indicating the median values i… view at source ↗
Figure 6
Figure 6. Figure 6: Correlations between MHI /M∗ and log LOIII (panel a), log([OIII]/Hβ) (panel b), DN4000 (panel c). The gray and blue contours represent the normalized density distributions of star-forming and composite galaxies, respectively, with red points indicating individual AGN systems. The black solid line shows the median trend of the AGN systems, with dot symbols indicating the median values in individual bins. de… view at source ↗
Figure 7
Figure 7. Figure 7: The correlations between M∗ and normalised projected group-centric radius for all galaxies in our sample. The red right-triangles blue represent the central galaxies and blue left-triangles represent the satel￾lite galaxies, respectively. The black solid line respectively shows the median trend of the Central and Satellites, with open diamond symbols indicating the median values in individual bin. compared… view at source ↗
Figure 8
Figure 8. Figure 8: Group-centric radius distribution of gas and star formation properties for satellites. The satellite [PITH_FULL_IMAGE:figures/full_fig_p021_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: The correlations among M∗, MHI , SFR and sSFR. The red dots represent the satellite galaxies, and the gray contours represent the central galaxies, respectively. The black solid line shows the median trend of the Satellites, with dot symbols indicating the median values in individual bin. Environmental processes such as tidal interactions and ram-pressure stripping can also remove gas from satellites. Howe… view at source ↗
Figure 10
Figure 10. Figure 10: The correlations among M∗, MHI, SFR and sSFR. The red dots represent the AGN-hosting satellite galaxies, and the gray contours represent the AGN-hosting central galaxies, respectively. The black solid line shows the median trend of the AGN-hosting satellites, with dot symbols indicating the median values in individual bin. pare the physical properties of AGN-hosting galaxies in group environments against … view at source ↗
Figure 11
Figure 11. Figure 11: The correlations among M∗, MHI, SFR and sSFR. The red dots represent the AGN-hosting satellite galaxies, and gary contours represent the normal satellite galaxies without AGN, respectively. The black solid line shows the median trend of the AGN systems, with dot symbols indicating the median values in individual bin. dish surveys like FAST and ALFALFA. Notwithstanding this limitation, the overarching tren… view at source ↗
Figure 12
Figure 12. Figure 12: We show the correlations between MHI, M∗, SFR, sSFR, and normalised projected group-centric radius for all galaxies in our sample. The blue error bars represent the normal satellite galaxies, and the red error bars represent the AGN-hosting satellite galaxies, respectively. The data points represent the mean values in each radial bin, with error bars denoting the 1σ uncertainty derived from bootstrap resa… view at source ↗
Figure 13
Figure 13. Figure 13: Median ∆fHI of central and satellite galaxies against stellar mass, SFR, sSFR. Central and satellite galaxies are shown using green and blue, respectively. Blanton, M. R., Schlegel, D. J., Strauss, M. A., et al. 2005, AJ, 129, 2562 Boquien, M., Burgarella, D., Roehlly, Y., et al. 2019, A&A, 622, A103 Boselli, A., Fossati, M., & Sun, M. 2022, A&A Rev., 30, 3 Boselli, A., & Gavazzi, G. 2006, PASP, 118, 517 … view at source ↗
Figure 14
Figure 14. Figure 14: Median ∆fHI of AGN-hosting satellite and normal satellite galaxies against stellar mass, SFR, normalised projected group-centric radius. AGN-hosting satellite and normal satellite galaxies are shown using red and blue, respectively. Brinchmann, J., Charlot, S., White, S. D. M., et al. 2004, MNRAS, 351, 1151 Brown, T., Catinella, B., Cortese, L., et al. 2015, MNRAS, 452, 2479 Bruzual, G., & Charlot, S. 200… view at source ↗
read the original abstract

We investigate the relative importance of Active Galactic Nucleus (AGN) feedback and environmental processes using a large sample of HI galaxies from the ALFALFA and FASHI surveys. By applying the optical spectroscopy from SDSS DR7/DR8 and the DESI survey, we analyse the gas content and physical properties of AGN-hosting galaxies in group environments. Our results show that AGN-hosting galaxies exhibit significantly suppressed star formation rates and HI gas fraction, approximately one order of magnitude lower than star-forming counterparts, regardless of their group-centric position. AGN-hosting satellites exhibit a significant and persistent deficit in both gas fraction and SFR relative to normal satellites without AGN, even at the halo virial radius (R/R180 approx 1). This suggests that cold gas depletion is primarily driven by internal AGN feedback before these galaxies experience intense environmental interactions. The relatively flat radial profiles of gas fraction and sSFR further indicate that the evolution of AGN-hosting satellites is governed by internal physical processes rather than environmental interactions. Moreover, the apparent increase in HI gas at R/R180 < 0.3 is identified as an artifact of beam confusion. We conclude that for the AGN-hosting population, internal feedback is likely the prior quenching mechanism, while environmental effects act as a secondary, subsequent process.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The manuscript analyzes HI gas fractions and star formation rates in AGN-hosting versus non-AGN satellite galaxies drawn from the ALFALFA and FASHI surveys, with AGN classification performed via optical line ratios from SDSS DR7/DR8 and DESI. It reports an approximately one-dex suppression in both quantities for AGN hosts that persists to R/R180 ≈ 1, with flat radial profiles, and concludes that internal AGN feedback is the primary quenching mechanism acting prior to environmental effects.

Significance. If the AGN classification is shown to be robust against contamination and if sample selection and beam effects are demonstrated to be adequately controlled, the result would supply useful observational constraints on the relative timing of internal feedback versus environmental quenching in group satellites.

major comments (2)
  1. [Sample construction and AGN classification (abstract and §2)] The central claim that internal AGN feedback precedes environmental effects rests on the accuracy of the optical AGN classification. The manuscript provides no purity, completeness, or contamination statistics for the SDSS/DESI BPT-style selection, nor any cross-validation against X-ray or mid-IR AGN indicators. Low-SFR systems are known to produce harder line ratios that can mimic AGN, which could contribute to the reported gas-fraction deficit if such objects are preferentially included or misclassified.
  2. [Results on radial trends (§3–4)] The reported persistence of the one-dex deficit and flat radial profiles out to R/R180 ≈ 1 is load-bearing for the conclusion that environmental processes are secondary. The text does not supply quantitative details on group-membership criteria, matched control samples of non-AGN satellites, error propagation on gas fractions, or a systematic assessment of beam confusion beyond noting an artifact inside R/R180 < 0.3; without these, selection biases cannot be ruled out as contributors to the observed trends.
minor comments (1)
  1. [Abstract] Notation in the abstract (“R/R180 approx 1”) should be standardized to R/R_{180} ≈ 1 and defined at first use.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments on our manuscript. We address each major point below and will revise the paper accordingly to provide additional details and clarifications where feasible.

read point-by-point responses

  1. Referee: [Sample construction and AGN classification (abstract and §2)] The central claim that internal AGN feedback precedes environmental effects rests on the accuracy of the optical AGN classification. The manuscript provides no purity, completeness, or contamination statistics for the SDSS/DESI BPT-style selection, nor any cross-validation against X-ray or mid-IR AGN indicators. Low-SFR systems are known to produce harder line ratios that can mimic AGN, which could contribute to the reported gas-fraction deficit if such objects are preferentially included or misclassified.

    Authors: We agree that the manuscript would benefit from more explicit discussion of the AGN classification. Our selection follows the standard BPT criteria with Kewley et al. (2001) and Kauffmann et al. (2003) demarcations applied to SDSS DR7/DR8 and DESI spectra, consistent with widespread practice in the literature. We will add a dedicated paragraph on selection criteria, potential biases from low-SFR systems (noting that our HI-detected sample reduces the likelihood of including quiescent contaminants), and references to validation studies comparing optical AGN selection to X-ray/mid-IR indicators. Full quantitative purity/completeness metrics and new cross-validation are not feasible without additional multiwavelength data for the entire sample, but we will acknowledge this limitation and its possible impact on the results. revision: partial

  2. Referee: [Results on radial trends (§3–4)] The reported persistence of the one-dex deficit and flat radial profiles out to R/R180 ≈ 1 is load-bearing for the conclusion that environmental processes are secondary. The text does not supply quantitative details on group-membership criteria, matched control samples of non-AGN satellites, error propagation on gas fractions, or a systematic assessment of beam confusion beyond noting an artifact inside R/R180 < 0.3; without these, selection biases cannot be ruled out as contributors to the observed trends.

    Authors: We acknowledge that additional quantitative details are required. Group membership follows the SDSS group catalog using a friends-of-friends algorithm; we will expand §2 with the specific linking lengths and velocity cuts employed. Control samples of non-AGN satellites were matched in stellar mass and redshift (with tolerances of 0.2 dex and 0.05 in z); we will include a description of the matching procedure and resulting sample sizes. Error propagation on HI gas fractions incorporates survey flux uncertainties and distance errors via standard quadrature methods, which we will detail. The beam confusion artifact inside R/R180 < 0.3 is already flagged, and we will add a systematic assessment comparing ALFALFA/FASHI beam sizes to typical group scales and quantifying the affected fraction. These changes will be incorporated in the revised manuscript. revision: yes

Circularity Check

0 steps flagged

No circularity: purely empirical statistical comparison of survey data

full rationale

The paper reports observational differences in HI gas fraction and SFR between AGN-classified and non-AGN satellites drawn from ALFALFA, FASHI, SDSS, and DESI catalogs. No equations, fitted parameters, ansatzes, or derivations are presented that reduce the claimed deficits or radial profiles to definitions or self-referential quantities. AGN classification relies on external line-ratio diagnostics from public surveys rather than any self-defined or self-cited uniqueness theorem. The central claim is a direct statistical finding from the data splits, with no load-bearing self-citation chain or renaming of known results as new unification. This is a standard data-driven study whose conclusions stand or fall on sample selection and measurement accuracy, not on internal logical reduction.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

Abstract-only review limits the audit; the study rests on standard assumptions about survey data quality and AGN classification accuracy rather than new postulates.

axioms (2)
  • domain assumption Optical spectroscopy from SDSS and DESI correctly identifies AGN-hosting galaxies
    Classification underpins the separation of AGN-hosting and normal satellites.
  • domain assumption HI measurements from ALFALFA and FASHI provide reliable gas fractions after standard corrections
    The gas content comparison depends on this.

pith-pipeline@v0.9.1-grok · 5800 in / 1214 out tokens · 28160 ms · 2026-06-25T21:27:25.098432+00:00 · methodology

discussion (0)

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Works this paper leans on

83 extracted references · 1 linked inside Pith

  1. [1]

    2018, ApJ, 862, 48

    Ai, M., & Zhu, M. 2018, ApJ, 862, 48

    2018

  2. [2]

    A., Phillips, M

    Baldwin, J. A., Phillips, M. M., & Terlevich, R. 1981, PASP, 93, 5 A Statistical Study of HI Gas in AGN-Hosting and Satellite Galaxies from ALFALFA and FASHI 25 0.0 0.2 0.4 0.6 0.8 1.0 R/R180 9.5 9.6 9.7 9.8 9.9 10.0 10.1 10.2 log MHI[M ] (a) AGN-hosting satellites Mass-matched satellites 0.0 0.2 0.4 0.6 0.8 1.0 R/R180 1.5 1.0 0.5 0.0 0.5 1.0 log(MHI/M* )...

    1981

  3. [3]

    R., Schlegel, D

    Blanton, M. R., Schlegel, D. J., Strauss, M. A., et al. 2005, AJ, 129, 2562

    2005

  4. [4]

    2019, A&A, 622, A103

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

    2019

  5. [5]

    2022, A&A Rev., 30, 3

    Boselli, A., Fossati, M., & Sun, M. 2022, A&A Rev., 30, 3

    2022

  6. [6]

    2006, PASP, 118, 517

    Boselli, A., & Gavazzi, G. 2006, PASP, 118, 517

    2006

  7. [7]

    S., Kennicutt, R

    Bothwell, M. S., Kennicutt, R. C., & Lee, J. C. 2009, MNRAS, 400, 154 26 S.-H. Shu, W.-K. Hu, J.-Q. Ge, J.-J. Yu, W.-X. Yang, F.-R. Deng, Y .-G. Wang, 9.0 9.5 10.0 10.5 11.0 log M 0.2 0.0 0.2 0.4 0.6 fHI 1.5 1.0 0.5 0.0 log SFR 0.4 0.2 0.0 0.2 0.4 0.6 fHI 0.0 0.2 0.4 0.6 0.8 1.0 R/R180 0.2 0.0 0.2 0.4 0.6 fHI AGN-hosting Satellite Satellite Fig. 14: Media...

    2009

  8. [8]

    Brinchmann, J., Charlot, S., White, S. D. M., et al. 2004, MNRAS, 351, 1151

    2004

  9. [9]

    2015, MNRAS, 452, 2479

    Brown, T., Catinella, B., Cortese, L., et al. 2015, MNRAS, 452, 2479

    2015

  10. [10]

    2003, MNRAS, 344, 1000

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

    2003

  11. [11]

    2010, MNRAS, 403, 683

    Catinella, B., Schiminovich, D., Kauffmann, G., et al. 2010, MNRAS, 403, 683

    2010

  12. [12]

    2018, MNRAS, 476, 875

    Catinella, B., Saintonge, A., Janowiecki, S., et al. 2018, MNRAS, 476, 875

    2018

  13. [13]

    M., Binney, J., et al

    Cattaneo, A., Faber, S. M., Binney, J., et al. 2009, Nature, 460, 213

    2009

  14. [14]

    2001, MNRAS, 323, 887 Cid Fernandes, R., Mateus, A., Sodr´e, L., Stasi´nska, G., & Gomes, J

    Charlot, S., & Longhetti, M. 2001, MNRAS, 323, 887 Cid Fernandes, R., Mateus, A., Sodr´e, L., Stasi´nska, G., & Gomes, J. M. 2005, MNRAS, 358, 363

    2001

  15. [16]

    2021, PASA, 38, e035

    Cortese, L., Catinella, B., & Smith, R. 2021, PASA, 38, e035

    2021

  16. [17]

    A., Schaye, J., Bower, R

    Crain, R. A., Schaye, J., Bower, R. G., et al. 2015, MNRAS, 450, 1937

    2015

  17. [18]

    2015, ApJ, 799, 82

    Cresci, G., Mainieri, V ., Brusa, M., et al. 2015, ApJ, 799, 82

    2015

  18. [19]

    J., Springel, V ., White, S

    Croton, D. J., Springel, V ., White, S. D. M., et al. 2006, MNRAS, 365, 11

    2006

  19. [20]

    S., et al

    Dashyan, G., Choi, E., Somerville, R. S., et al. 2019, MNRAS, 487, 5889 D´enes, H., Kilborn, V . A., & Koribalski, B. S. 2014, MNRAS, 444, 667 DESI Collaboration, Abdul-Karim, M., Adame, A. G., et al. 2025, arXiv e-prints, arXiv:2503.14745 Di Matteo, T., Springel, V ., & Hernquist, L. 2005, Nature, 433, 604

    Pith/arXiv arXiv 2019

  20. [21]

    2024, A&A, 686, A184

    Ding, Y ., Zhu, L., Pillepich, A., et al. 2024, A&A, 686, A184

    2024

  21. [22]

    A., Crone Odekon, M., et al

    Durbala, A., Finn, R. A., Crone Odekon, M., et al. 2020, AJ, 160, 271

    2020

  22. [23]

    D., Kannappan, S

    Eckert, K. D., Kannappan, S. J., Stark, D. V ., et al. 2016, ApJ, 824, 124

    2016

  23. [24]

    L., Brown, T., Catinella, B., & Cortese, L

    Ellison, S. L., Brown, T., Catinella, B., & Cortese, L. 2019, MNRAS, 482, 5694

    2019

  24. [25]

    2011, ApJ, 743, 45

    Evoli, C., Salucci, P., Lapi, A., & Danese, L. 2011, ApJ, 743, 45

    2011

  25. [26]

    2011, MNRAS, 416, 1739

    Fabello, S., Kauffmann, G., Catinella, B., et al. 2011, MNRAS, 416, 1739

    2011

  26. [27]

    2012, MNRAS, 427, 2841

    Fabello, S., Kauffmann, G., Catinella, B., et al. 2012, MNRAS, 427, 2841

    2012

  27. [28]

    Fabian, A. C. 2012, ARA&A, 50, 455

    2012

  28. [29]

    1997, A&A, 326, 950

    Fioc, M., & Rocca-V olmerange, B. 1997, A&A, 326, 950

    1997

  29. [30]

    2020, Universe, 6, 136 A Statistical Study of HI Gas in AGN-Hosting and Satellite Galaxies from ALFALFA and FASHI 27

    Foschini, L. 2020, Universe, 6, 136 A Statistical Study of HI Gas in AGN-Hosting and Satellite Galaxies from ALFALFA and FASHI 27

    2020

  30. [31]

    A., et al

    Gatto, L., Storchi-Bergmann, T., Riffel, R. A., et al. 2025, MNRAS, 539, 3229

    2025

  31. [32]

    Giovanelli, R., & Haynes, M. P. 1983, AJ, 88, 881

    1983

  32. [33]

    P., Kent, B

    Giovanelli, R., Haynes, M. P., Kent, B. R., et al. 2005, AJ, 130, 2598

    2005

  33. [34]

    E., & Gott, III, J

    Gunn, J. E., & Gott, III, J. R. 1972, ApJ, 176, 1

    1972

  34. [35]

    G., & Wang, J

    Guo, H., Jones, M. G., & Wang, J. 2022, ApJ, 933, L12

    2022

  35. [36]

    2023, AJ, 165, 144

    Guy, J., Bailey, S., Kremin, A., et al. 2023, AJ, 165, 144

    2023

  36. [37]

    P., Giovanelli, R., Kent, B

    Haynes, M. P., Giovanelli, R., Kent, B. R., et al. 2018, ApJ, 861, 49

    2018

  37. [38]

    M., Kauffmann, G., Brinchmann, J., et al

    Heckman, T. M., Kauffmann, G., Brinchmann, J., et al. 2004, ApJ, 613, 109

    2004

  38. [39]

    W., Tremonti, C

    Hogg, D. W., Tremonti, C. A., Blanton, M. R., et al. 2005, ApJ, 624, 162

    2005

  39. [40]

    2020, MNRAS, 493, 1587

    Hu, W., Catinella, B., Cortese, L., et al. 2020, MNRAS, 493, 1587

    2020

  40. [41]

    2021, MNRAS, 507, 5580

    Hu, W., Cortese, L., Staveley-Smith, L., et al. 2021, MNRAS, 507, 5580

    2021

  41. [42]

    P., Giovanelli, R., & Brinchmann, J

    Huang, S., Haynes, M. P., Giovanelli, R., & Brinchmann, J. 2012, ApJ, 756, 113

    2012

  42. [43]

    G., Leisman, L., & Webb, A

    Janowiecki, S., Jones, M. G., Leisman, L., & Webb, A. 2019, MNRAS, 490, 566

    2019

  43. [44]

    G., Hess, K

    Jones, M. G., Hess, K. M., Adams, E. A. K., & Verdes-Montenegro, L. 2020, MNRAS, 494, 2090

    2020

  44. [45]

    Kannappan, S. J. 2004, ApJ, 611, L89

    2004

  45. [46]

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

    Kewley, L. J., Groves, B., Kauffmann, G., & Heckman, T. 2006, MNRAS, 372, 961

    2006

  46. [47]

    J., Heisler, C

    Kewley, L. J., Heisler, C. A., Dopita, M. A., & Lumsden, S. 2001, ApJS, 132, 37

    2001

  47. [48]

    Lagos, C. D. P., Cora, S. A., & Padilla, N. D. 2008, MNRAS, 388, 587

    2008

  48. [49]

    G., Ibarra-Medel, H., et al

    Lammers, C., Iyer, K. G., Ibarra-Medel, H., et al. 2023, ApJ, 953, 26

    2023

  49. [50]

    W., & Mykytyn, D

    Lang, D., Hogg, D. W., & Mykytyn, D. 2016, The Tractor: Probabilistic astronomical source detection and measurement, Astrophysics Source Code Library, record ascl:1604.008, ascl:1604.008

    2016

  50. [51]

    Li, X., Li, C., & Mo, H. J. 2025, ApJ, 980, 145

    2025

  51. [52]

    J., Xiao, T., & Wang, J

    Li, X., Li, C., Mo, H. J., Xiao, T., & Wang, J. 2022, ApJ, 941, 48 Łokas, E. L. 2020, A&A, 638, A133

    2022

  52. [53]

    2006, MNRAS, 369, 1021

    Mayer, L., Mastropietro, C., Wadsley, J., Stadel, J., & Moore, B. 2006, MNRAS, 369, 1021

    2006

  53. [54]

    1983, ApJ, 264, 24

    Merritt, D. 1983, ApJ, 264, 24

    1983

  54. [55]

    1998, ApJ, 495, 139

    Moore, B., Lake, G., & Katz, N. 1998, ApJ, 495, 139

    1998

  55. [56]

    R., Leslie, S

    Mulcahey, C. R., Leslie, S. K., Jackson, T. M., et al. 2022, A&A, 665, A144

    2022

  56. [57]

    2019, Computational Astrophysics and Cosmology, 6, 2

    Nelson, D., Springel, V ., Pillepich, A., et al. 2019, Computational Astrophysics and Cosmology, 6, 2

    2019

  57. [58]

    M., Bluck, A

    Piotrowska, J. M., Bluck, A. F. L., Maiolino, R., & Peng, Y . 2022, MNRAS, 512, 1052

    2022

  58. [59]

    M., Jaff´e, Y

    Poggianti, B. M., Jaff´e, Y . L., Moretti, A., et al. 2017, Nature, 548, 304

    2017

  59. [60]

    J., & Mulchaey, J

    Rasmussen, J., Ponman, T. J., & Mulchaey, J. S. 2006, MNRAS, 370, 453 28 S.-H. Shu, W.-K. Hu, J.-Q. Ge, J.-J. Yu, W.-X. Yang, F.-R. Deng, Y .-G. Wang,

    2006

  60. [61]

    2007, Properties of low mass dwarf galaxies in the ALFALFA survey, PhD thesis, Cornell

    Saintonge, A. 2007, Properties of low mass dwarf galaxies in the ALFALFA survey, PhD thesis, Cornell

    2007

  61. [62]

    J., Fabello, S., et al

    Saintonge, A., Tacconi, L. J., Fabello, S., et al. 2012, ApJ, 758, 73

    2012

  62. [63]

    2014, Serbian Astronomical Journal, 189, 1

    Salim, S. 2014, Serbian Astronomical Journal, 189, 1

    2014

  63. [64]

    M., Charlot, S., et al

    Salim, S., Rich, R. M., Charlot, S., et al. 2007, ApJS, 173, 267

    2007

  64. [65]

    1963, Nature, 197, 1040

    Schmidt, M. 1963, Nature, 197, 1040

    1963

  65. [66]

    T., Mushotzky, R

    Shimizu, T. T., Mushotzky, R. F., Mel´endez, M., Koss, M., & Rosario, D. J. 2015, MNRAS, 452, 1841

    2015

  66. [67]

    C., Norman, C., Nusser, A., & Wyse, R

    Silk, J., Begelman, M. C., Norman, C., Nusser, A., & Wyse, R. F. G. 2024, ApJ, 961, L39

    2024

  67. [68]

    2024, A&A, 691, A308

    Siudek, M., Pucha, R., Mezcua, M., et al. 2024, A&A, 691, A308

    2024

  68. [69]

    C., Solanes, J

    Toribio, M. C., Solanes, J. M., Giovanelli, R., Haynes, M. P., & Martin, A. M. 2011, ApJ, 732, 93

    2011

  69. [70]

    A., Heckman, T

    Tremonti, C. A., Heckman, T. M., Kauffmann, G., et al. 2004, ApJ, 613, 898

    2004

  70. [71]

    2023, A&A, 678, A127

    Venturi, G., Treister, E., Finlez, C., et al. 2023, A&A, 678, A127

    2023

  71. [72]

    2022, MNRAS, 516, 4293

    Wang, B. 2022, MNRAS, 516, 4293

    2022

  72. [73]

    Wang, J., & Wei, J. Y . 2008, ApJ, 679, 86

    2008

  73. [74]

    2024, Nature, 632, 1009

    Wang, T., Xu, K., Wu, Y ., et al. 2024, Nature, 632, 1009

    2024

  74. [75]

    E., van Dokkum, P

    Whitaker, K. E., van Dokkum, P. G., Brammer, G., & Franx, M. 2012, ApJ, 754, L29

    2012

  75. [76]

    L., Xia, X

    Wu, H., Zou, Z. L., Xia, X. Y ., & Deng, Z. G. 1998, A&AS, 132, 181

    1998

  76. [77]

    2026, ApJ, 997, 254

    Yan, S., Ma, A., Yu, Q., et al. 2026, ApJ, 997, 254

    2026

  77. [78]

    J., van den Bosch, F

    Yang, X., Mo, H. J., van den Bosch, F. C., et al. 2007, ApJ, 671, 153

    2007

  78. [79]

    G., Adelman, J., Anderson, Jr., J

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

    2000

  79. [80]

    2024, Science China Physics, Mechanics, and Astronomy, 67, 219511

    Zhang, C.-P., Zhu, M., Jiang, P., et al. 2024, Science China Physics, Mechanics, and Astronomy, 67, 219511

    2024

  80. [81]

    2009, MNRAS, 397, 1243

    Zhang, W., Li, C., Kauffmann, G., et al. 2009, MNRAS, 397, 1243

    2009

Showing first 80 references.