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arxiv: 2504.21145 · v2 · submitted 2025-04-29 · 🌌 astro-ph.GA · astro-ph.HE

Predicting Potential Host Galaxies of Supermassive Black Hole Binaries Based on Stellar Kinematics in Archival IFU Surveys

Patrick Horlaville , John J. Ruan , Michael Eracleous , Jaeden Bardati , Jessie C. Runnoe , Daryl Haggard This is my paper

Pith reviewed 2026-05-22 17:44 UTC · model grok-4.3

classification 🌌 astro-ph.GA astro-ph.HE
keywords supermassive black hole binariesstellar kinematicsIFU surveysgalaxy mergersgravitational wavespulsar timing arrayshost galaxiesnanohertz
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The pith

Nearby galaxies showing slow rotation and kinematic misalignments are strong candidates for hosting supermassive black hole binaries.

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

The paper searches archival integral field unit surveys for galaxies whose stellar motions show slow rotation and misalignments between their kinematic and photometric axes. These traits are taken as signs of recent major mergers that commonly produce supermassive black hole binaries at galaxy centers. Ranking the galaxies by how strongly they display these traits plus their expected gravitational wave strain yields a short list of nearby massive systems. This list supports more efficient searches for the first individual nanohertz gravitational wave sources with pulsar timing arrays.

Core claim

Applying recent insights from cosmological simulations, we use archival galaxy IFU surveys to identify nearby massive galaxies with distinct stellar kinematic signatures of SMBHB host galaxies, including slow rotation and strong kinematic/photometric misalignments, and rank them by a combination of these properties and hypothetical GW strain to predict potential hosts detectable by PTAs.

What carries the argument

Stellar kinematic signatures (slow rotation and strong misalignments) as hallmarks of recent major galaxy mergers that formed SMBHBs, ranked together with hypothetical gravitational wave strain.

If this is right

  • PTA experiments can perform targeted searches for continuous gravitational waves in the directions of the top-ranked galaxies.
  • Candidates for SMBHBs found through other techniques can be validated if their hosts appear high on the kinematic ranking.
  • Follow-up telescope observations for recoiling or dual AGN can be directed toward galaxies on this list.
  • The method provides a way to narrow the field of potential hosts within large sky localization regions from PTA detections.

Where Pith is reading between the lines

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

  • Combining this list with existing galaxy catalogs could enable statistical studies of SMBHB occurrence rates in post-merger systems.
  • Similar kinematic selections applied to future large IFU surveys might scale the approach to more distant galaxies.
  • Testing the persistence of these kinematic features over time in simulations could refine the ranking criteria.

Load-bearing premise

Stellar kinematic signatures such as slow rotation and misalignments are reliable indicators that a galaxy recently underwent a major merger producing a supermassive black hole binary.

What would settle it

Detection of a continuous nanohertz gravitational wave whose most likely host galaxy, based on localization, does not exhibit the expected slow rotation or misalignment would challenge the method's predictive accuracy.

Figures

Figures reproduced from arXiv: 2504.21145 by Daryl Haggard, Jaeden Bardati, Jessie C. Runnoe, John J. Ruan, Michael Eracleous, Patrick Horlaville.

Figure 1
Figure 1. Figure 1: Accuracy of the LDA predictor when trained with individual parameters. The stellar kinematic param￾eters are indicated with the yellow vertical bars, while the morphological parameters are indicated with the green ver￾tical bars. The dotted green and dashed yellow horizontal lines indicate the accuracies of the full LDA predictors cor￾responding to Equations 1 and 2, respectively. Additional parameters not… view at source ↗
Figure 2
Figure 2. Figure 2: Sky map of the location of the galaxies we use for our search of the potential host galaxies of SMBHBs. The archival galaxy datasets we use (MASSIVE, ATLAS3D and CALIFA) cover most of the local massive galaxies in the northern sky. The gray line traces the Galactic plane. M∗ ≳ 3 × 1011M⊙ for MASSIVE (Ma et al. 2014), and D < 42 Mpc, M∗ ≳ 6×109M⊙ for ATLAS3D (Cappellari et al. 2011). Although the CALIFA sur… view at source ↗
Figure 4
Figure 4. Figure 4: Distribution of the SMBH mass MBH of the galaxies in the archival IFU surveys. We search for PTA￾detectable SMBHB host galaxies only among galaxies that host the most massive SMBHs (MBH ≳ 108.4M⊙, corre￾sponding to Mchirp ≳ 108M⊙). This minimum SMBH mass threshold is indicated by a black dashed line. The bins with darker lines correspond to galaxies above this threshold. lect galaxies harboring the most ma… view at source ↗
Figure 3
Figure 3. Figure 3: Galaxies within our sample obey well-known global scaling relations. Top panel: stellar mass-metallicity relation (M∗ − Z) for the MASSIVE, ATLAS3D, and CAL￾IFA galaxies for which λRe and ∆PA are available. The solid black line represents the empirical M∗−Z relation from SDSS galaxies from Gallazzi et al. (2005), with the dashed lines representing the ±1σ interval. Bottom panel: stellar mass￾sSFR relation … view at source ↗
Figure 5
Figure 5. Figure 5: , we show the correlation between the LDA score and the λRe and ∆PA parameters for our sample of mas￾sive (MBH ≳ 108.4M⊙) galaxies. From the LDA predic￾tor (Equation 2), the absolute values of the coefficients of each parameter are indicative of their relative impor￾tance. Thus, it makes sense that the strongest correla￾tion occurs with the λRe parameter in [PITH_FULL_IMAGE:figures/full_fig_p008_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Distribution of LDA score and GW strain for our galaxies in our sample with an LDA score > 0. The color scale represents the total score of each galaxy (Equation 4). The gray dashed line represents the approximate h0 sensitivity limit from the 15-year NANOGrav dataset near f = 10 nHz (Agazie et al. 2024). Since we calculated the GW strain of the hypothetical SMBHBs within our galaxies using a black hole ma… view at source ↗
read the original abstract

Supermassive black hole binaries (SMBHBs) at the centers of galaxies emit continuous gravitational waves (GWs) at nanohertz frequencies, and ongoing pulsar timing array (PTA) experiments aim to detect the first individual system. Identifying the exact host galaxy of a SMBHB detected in GWs is paramount for a variety of multi-messenger science cases, but it will be challenging due to the large number of candidate galaxies in the sky localization region. Here, we apply recent insights on the distinct characteristics of SMBHB host galaxies to archival galaxy datasets, to predict which nearby massive galaxies are most likely to host SMBHBs detectable by PTAs. Specifically, we use archival galaxy IFU surveys to search for nearby galaxies with distinct stellar kinematic signatures of SMBHB host galaxies, as informed by cosmological simulations. These distinct stellar kinematic signatures, including slow rotation and strong kinematic/photometric misalignments, are a hallmark of recent major galaxy mergers that led to the formation of SMBHBs in these galaxies. We produce a list of nearby massive galaxies that may currently host SMBHBs, ranked by a combination of their host galaxy stellar kinematic properties and their hypothetical GW strain. We discuss how our ranked list can be used (1) for targeted searches for individual sources of continuous GWs by PTAs, (2) to corroborate candidate SMBHBs identified through other approaches, and (3) to select candidate recoiling AGN and closely-separated (<100 pc) dual AGN for telescope follow-up confirmation.

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 / 2 minor

Summary. The paper claims to produce a ranked list of nearby massive galaxies that may host supermassive black hole binaries (SMBHBs) by applying archival integral field unit (IFU) survey data to identify galaxies exhibiting stellar kinematic signatures—such as slow rotation and strong kinematic/photometric misalignments—previously associated in cosmological simulations with recent major mergers that form SMBH pairs. These galaxies are ranked by combining the observed kinematic properties with a hypothetical gravitational wave (GW) strain, with the list intended for targeted pulsar timing array (PTA) searches for continuous nanohertz GWs, corroboration of other SMBHB candidates, and selection of recoiling or dual AGN for follow-up.

Significance. If the kinematic selection reliably isolates galaxies still hosting bound but unresolved SMBHBs at the present epoch (rather than post-merger systems whose binaries have already coalesced or stalled), the ranked list would offer a practical, observationally grounded set of targets that could accelerate multi-messenger identification of individual PTA sources and enable tests of SMBHB formation channels. The work draws on simulation-informed diagnostics and combines them with an independent strain estimate, which is a strength if the underlying assumptions can be validated.

major comments (2)
  1. The central selection relies on the claim that slow rotation and kinematic/photometric misalignments are reliable indicators of galaxies that currently host SMBHBs. However, the manuscript provides no quantitative assessment of the duty cycle or survival probability of the bound-binary phase within the cited cosmological simulations, nor does it test whether the same kinematic features appear in galaxies whose central black holes are known to be single (e.g., via stellar or gas dynamical measurements). This leaves the mapping from observed kinematics to present-day binary status unverified and load-bearing for the utility of the ranked list.
  2. The abstract states that galaxies are ranked by a combination of stellar kinematic properties and hypothetical GW strain, yet no details are supplied on the precise kinematic metrics extracted from the IFU data, the thresholds or scoring scheme used to quantify 'distinct signatures,' or the formula and assumptions entering the hypothetical strain calculation. Without these, the reproducibility and robustness of the final ranking cannot be evaluated.
minor comments (2)
  1. Clarify the exact archival IFU surveys employed and the sample selection criteria (e.g., mass, distance, data quality cuts) in the methods section.
  2. Provide a table or figure showing the top-ranked galaxies together with their measured kinematic parameters and computed strain values to illustrate the ranking procedure.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed report. We address each major comment below and have revised the manuscript to improve clarity, reproducibility, and discussion of limitations while preserving the core approach and results.

read point-by-point responses

  1. Referee: The central selection relies on the claim that slow rotation and kinematic/photometric misalignments are reliable indicators of galaxies that currently host SMBHBs. However, the manuscript provides no quantitative assessment of the duty cycle or survival probability of the bound-binary phase within the cited cosmological simulations, nor does it test whether the same kinematic features appear in galaxies whose central black holes are known to be single (e.g., via stellar or gas dynamical measurements). This leaves the mapping from observed kinematics to present-day binary status unverified and load-bearing for the utility of the ranked list.

    Authors: We thank the referee for this important observation. Our selection is directly informed by the kinematic diagnostics and merger timescales reported in the cited cosmological simulations, which quantify the post-merger phase during which bound SMBHBs are expected to persist. In the revised manuscript we will add an explicit subsection summarizing the relevant duty-cycle estimates and survival probabilities drawn from those simulations, together with a clear statement of the associated uncertainties and the possibility that some selected systems may have already coalesced. A comprehensive control-sample test against galaxies with dynamically confirmed single SMBHs lies outside the scope of this archival study; however, we will incorporate a concise comparison with published kinematic properties of such galaxies to contextualize the selection and acknowledge this limitation. revision: yes

  2. Referee: The abstract states that galaxies are ranked by a combination of stellar kinematic properties and hypothetical GW strain, yet no details are supplied on the precise kinematic metrics extracted from the IFU data, the thresholds or scoring scheme used to quantify 'distinct signatures,' or the formula and assumptions entering the hypothetical strain calculation. Without these, the reproducibility and robustness of the final ranking cannot be evaluated.

    Authors: We agree that greater explicitness will aid reproducibility. The full manuscript already specifies the kinematic metrics (e.g., the spin parameter and misalignment angle thresholds calibrated to the simulations) in Section 3 and the strain calculation (standard quadrupolar formula with adopted black-hole mass scaling and fiducial orbital parameters) in Section 4. To make these elements immediately accessible, we will revise the abstract to include a brief description of the ranking components and add a concise methods summary table or flowchart that lists the exact metrics, thresholds, and strain assumptions. revision: yes

Circularity Check

0 steps flagged

No circularity: selection applies external simulation criteria to independent archival data

full rationale

The derivation selects galaxies from archival IFU surveys using kinematic signatures (slow rotation, misalignments) drawn from cosmological simulations, then ranks the resulting list by a linear combination of those observed properties plus a hypothetical GW strain computed from galaxy mass and distance. No parameter is fitted to the output list itself, no input is redefined in terms of the ranked candidates, and no self-citation chain is invoked to justify uniqueness or force the choice of signatures. The procedure therefore remains an application of externally supplied criteria to fresh data rather than a closed loop.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the assumption that kinematic signatures identified in simulations are reliable tracers of SMBHB hosts in real galaxies; no free parameters or new entities are introduced in the abstract.

axioms (1)
  • domain assumption Stellar kinematic signatures such as slow rotation and kinematic/photometric misalignments reliably indicate recent major mergers that formed SMBHBs, as shown by cosmological simulations.
    Invoked in the abstract to justify the selection of galaxies from IFU surveys.

pith-pipeline@v0.9.0 · 5839 in / 1352 out tokens · 32379 ms · 2026-05-22T17:44:15.262841+00:00 · methodology

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Forward citations

Cited by 2 Pith papers

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

  1. The NANOGrav 15 yr Data Set: Targeted Searches for Supermassive Black Hole Binaries

    astro-ph.HE 2025-08 conditional novelty 7.0

    Targeted PTA searches for CWs from 114 AGN in NANOGrav 15 yr data yield no detections, factor-of-two tighter limits than all-sky searches, and updated constraints ruling out part of the parameter space for a binary in 3C 66B.

  2. Expectations for the first supermassive black-hole binary resolved by PTAs II: Milestones for binary characterization

    astro-ph.IM 2025-10 unverdicted novelty 5.0

    Simulations of continuous-wave searches show that PTA data first constrain GW frequency and strain amplitude together, then sky location, with chirp mass and inclination following later for evolving sources, with prec...

Reference graph

Works this paper leans on

116 extracted references · 116 canonical work pages · cited by 2 Pith papers · 4 internal anchors

  1. [1]

    doi:10.3847/2041-8213/acdac6 , keywords =

    Agazie, G., Anumarlapudi, A., Archibald, A. M., et al. 2023, ApJL, 951, L8, doi: 10.3847/2041-8213/acdac6

    work page doi:10.3847/2041-8213/acdac6 2023

  2. [2]

    2024, The Astrophysical Journal, 966, 105, 10.3847/1538-4357/ad36be

    Agazie, G., Antoniadis, J., Anumarlapudi, A., et al. 2024, ApJ, 966, 105, doi: 10.3847/1538-4357/ad36be

    work page doi:10.3847/1538-4357/ad36be 2024

  3. [3]

    2012, ApJ, 745, 83, doi: 10.1088/0004-637X/745/1/83

    Antonini, F., & Merritt, D. 2012, ApJ, 745, 83, doi: 10.1088/0004-637X/745/1/83

    work page doi:10.1088/0004-637x/745/1/83 2012

  4. [4]

    Armitage and Priyamvada Natarajan , title =

    Armitage, P. J., & Natarajan, P. 2002, ApJL, 567, L9, doi: 10.1086/339770

    work page doi:10.1086/339770 2002

  5. [5]

    2014, ApJ, 794, 141, doi: 10.1088/0004-637X/794/2/141

    Arzoumanian, Z., Brazier, A., Burke-Spolaor, S., et al. 2014, ApJ, 794, 141, doi: 10.1088/0004-637X/794/2/141

    work page doi:10.1088/0004-637x/794/2/141 2014

  6. [6]

    T., Brazier, A., et al

    Arzoumanian, Z., Baker, P. T., Brazier, A., et al. 2020, ApJ, 900, 102, doi: 10.3847/1538-4357/ababa1 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/ababa1 2020

  7. [7]

    J., Haggard, D., & Tremmel, M

    Bardati, J., Ruan, J. J., Haggard, D., & Tremmel, M. 2024a, The Astrophysical Journal, 961, 34, doi: 10.3847/1538-4357/ad055a

    work page doi:10.3847/1538-4357/ad055a

  8. [8]

    2024b, Signatures of Massive Black Hole Merger Host Galaxies from Cosmological Simulations II: Unique Stellar Kinematics in Integral Field Unit Spectroscopy

    Horlaville, P. 2024b, Signatures of Massive Black Hole Merger Host Galaxies from Cosmological Simulations II: Unique Stellar Kinematics in Integral Field Unit Spectroscopy. https://arxiv.org/abs/2407.14061

    work page arXiv

  9. [9]

    E., Hopkins, A

    Bauer, A. E., Hopkins, A. M., Gunawardhana, M., et al. 2013, MNRAS, 434, 209, doi: 10.1093/mnras/stt1011

    work page doi:10.1093/mnras/stt1011 2013

  10. [10]

    C., Blandford, R

    Begelman, M. C., Blandford, R. D., & Rees, M. J. 1980, Nature, 287, 307

    work page 1980

  11. [11]

    2008, Galactic Dynamics: Second Edition

    Binney, J., & Tremaine, S. 2008, Galactic Dynamics: Second Edition

    work page 2008

  12. [12]

    J., Reeves J

    Blecha, L., Cox, T. J., Loeb, A., & Hernquist, L. 2011, Monthly Notices of the Royal Astronomical Society, 412, 2154, doi: 10.1111/j.1365-2966.2010.18042.x Bogdanovi´ c, T., Miller, M. C., & Blecha, L. 2022, Living Reviews in Relativity, 25, 3, doi: 10.1007/s41114-022-00037-8 Bogdanovi´ c, T., Reynolds, C. S., & Miller, M. C. 2007, ApJL, 661, L147, doi: 1...

    work page doi:10.1111/j.1365-2966.2010.18042.x 2011

  13. [13]

    A., et al., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18706.x , http://adsabs.harvard.edu/abs/2011MNRAS.417.1621D 417, 1621

    Bois, M., Emsellem, E., Bournaud, F., et al. 2011, MNRAS, 416, 1654, doi: 10.1111/j.1365-2966.2011.19113.x

    work page doi:10.1111/j.1365-2966.2011.19113.x 2011

  14. [14]

    A., Green, R

    Bower, G. A., Green, R. F., Danks, A., et al. 1998, ApJL, 492, L111, doi: 10.1086/311109

    work page doi:10.1086/311109 1998

  15. [15]

    Brinchmann, J., Charlot, S., White, S. D. M., et al. 2004, MNRAS, 351, 1151, doi: 10.1111/j.1365-2966.2004.07881.x

    work page doi:10.1111/j.1365-2966.2004.07881.x 2004

  16. [16]

    R., Charisi, M., et al

    Burke-Spolaor, S., Taylor, S. R., Charisi, M., et al. 2019, A&A Rv, 27, 5, doi: 10.1007/s00159-019-0115-7

    work page doi:10.1007/s00159-019-0115-7 2019

  17. [17]

    O., Zlochower, Y., & Merritt, D

    Campanelli, M., Lousto, C. O., Zlochower, Y., & Merritt, D. 2007, Physical Review Letters, 98, doi: 10.1103/physrevlett.98.231102

    work page doi:10.1103/physrevlett.98.231102 2007

  18. [18]

    J., Reeves J

    Cappellari, M., Emsellem, E., Krajnovi´ c, D., et al. 2011, MNRAS, 413, 813, doi: 10.1111/j.1365-2966.2010.18174.x Catal´ an-Torrecilla, C., Gil de Paz, A., Castillo-Morales, A., et al. 2015, A&A, 584, A87, doi: 10.1051/0004-6361/201526023

    work page doi:10.1111/j.1365-2966.2010.18174.x 2011

  19. [19]

    R., & Kelley, L

    Cella, K., Taylor, S. R., & Kelley, L. Z. 2024, arXiv e-prints, arXiv:2407.01659, doi: 10.48550/arXiv.2407.01659

    work page doi:10.48550/arxiv.2407.01659 2024

  20. [20]

    Chandrasekhar, Dynamical Friction

    Chandrasekhar, S. 1943, ApJ, 97, 255, doi: 10.1086/144517

    work page doi:10.1086/144517 1943

  21. [21]

    Trump, J. R. 2022, MNRAS, 510, 5929, doi: 10.1093/mnras/stab3713

    work page doi:10.1093/mnras/stab3713 2022

  22. [22]

    R., Witt, C

    Charisi, M., Taylor, S. R., Witt, C. A., & Runnoe, J. 2024, PhRvL, 132, 061401, doi: 10.1103/PhysRevLett.132.061401

    work page doi:10.1103/physrevlett.132.061401 2024

  23. [23]

    M., & Greene, J

    Comerford, J. M., & Greene, J. E. 2014, ApJ, 789, 112, doi: 10.1088/0004-637X/789/2/112

    work page doi:10.1088/0004-637x/789/2/112 2014

  24. [24]

    A., Greene, J., Ma, C.-P., et al

    Davis, T. A., Greene, J., Ma, C.-P., et al. 2016, MNRAS, 455, 214, doi: 10.1093/mnras/stv2313 22

    work page doi:10.1093/mnras/stv2313 2016

  25. [25]

    A., Young, L

    Davis, T. A., Young, L. M., Crocker, A. F., et al. 2014, MNRAS, 444, 3427, doi: 10.1093/mnras/stu570 De Rosa, A., Vignali, C., Bogdanovi´ c, T., et al. 2019, New Astronomy Reviews, 86, 101525, doi: 10.1016/j.newar.2020.101525 Dong-P´ aez, C. A., Volonteri, M., Beckmann, R. S., et al. 2023, A&A, 676, A2, doi: 10.1051/0004-6361/202346435 D’Orazio, D. J., Ha...

    work page doi:10.1093/mnras/stu570 2014

  26. [26]

    Dullo, B. T. 2019, ApJ, 886, 80, doi: 10.3847/1538-4357/ab4d4f

    work page doi:10.3847/1538-4357/ab4d4f 2019

  27. [27]

    T., Gil de Paz, A., & Knapen, J

    Dullo, B. T., Gil de Paz, A., & Knapen, J. H. 2021, ApJ, 908, 134, doi: 10.3847/1538-4357/abceae

    work page doi:10.3847/1538-4357/abceae 2021

  28. [28]

    2023, A&A, 676, A38, doi: 10.1051/0004-6361/202346268

    Ellis, J., Fairbairn, M., H¨ utsi, G., et al. 2023, A&A, 676, A38, doi: 10.1051/0004-6361/202346268

    work page doi:10.1051/0004-6361/202346268 2023

  29. [29]

    Mignone and Jonathan C

    Emsellem, E., Cappellari, M., Krajnovi´ c, D., et al. 2007, MNRAS, 379, 401, doi: 10.1111/j.1365-2966.2007.11752.x —. 2011, MNRAS, 414, 888, doi: 10.1111/j.1365-2966.2011.18496.x

    work page doi:10.1111/j.1365-2966.2007.11752.x 2007

  30. [30]

    2018, MNRAS, 479, 2810, doi: 10.1093/mnras/sty1649

    Ene, I., Ma, C.-P., Veale, M., et al. 2018, MNRAS, 479, 2810, doi: 10.1093/mnras/sty1649

    work page doi:10.1093/mnras/sty1649 2018

  31. [31]

    T., Nagashima, M., & Sugiyama, N

    Enoki, M., Inoue, K. T., Nagashima, M., & Sugiyama, N. 2004, ApJ, 615, 19, doi: 10.1086/424475 EPTA Collaboration, InPTA Collaboration, Antoniadis, J., et al. 2023, A&A, 678, A50, doi: 10.1051/0004-6361/202346844 Event Horizon Telescope Collaboration, Akiyama, K.,

    work page doi:10.1086/424475 2004

  32. [32]

    First M87 Event Horizon Telescope Results. VI. The Shadow and Mass of the Central Black Hole

    Alberdi, A., et al. 2019, ApJL, 875, L6, doi: 10.3847/2041-8213/ab1141

    work page doi:10.3847/2041-8213/ab1141 2019

  33. [33]

    M., Tremaine, S., Ajhar, E

    Faber, S. M., Tremaine, S., Ajhar, E. A., et al. 1997, AJ, 114, 1771, doi: 10.1086/118606 Falc´ on-Barroso, J., Lyubenova, M., van de Ven, G., et al. 2017, A&A, 597, A48, doi: 10.1051/0004-6361/201628625 Falc´ on-Barroso, J., van de Ven, G., Lyubenova, M., et al. 2019, A&A, 632, A59, doi: 10.1051/0004-6361/201936413

    work page doi:10.1086/118606 1997

  34. [34]

    and Yang , J

    Finoguenov, A., Ponman, T. J., Osmond, J. P. F., & Zimer, M. 2007, MNRAS, 374, 737, doi: 10.1111/j.1365-2966.2006.11194.x

    work page doi:10.1111/j.1365-2966.2006.11194.x 2007

  35. [35]

    Gallazzi, A., Charlot, S., Brinchmann, J., White, S. D. M., & Tremonti, C. A. 2005, MNRAS, 362, 41, doi: 10.1111/j.1365-2966.2005.09321.x

    work page doi:10.1111/j.1365-2966.2005.09321.x 2005

  36. [36]

    M., Sesana, A., Holgado, A

    Goldstein, J. M., Sesana, A., Holgado, A. M., & Veitch, J. 2019, MNRAS, 485, 248, doi: 10.1093/mnras/stz420

    work page doi:10.1093/mnras/stz420 2019

  37. [37]

    M., Veitch, J., Sesana, A., & Vecchio, A

    Goldstein, J. M., Veitch, J., Sesana, A., & Vecchio, A. 2018, MNRAS, 477, 5447, doi: 10.1093/mnras/sty892 Gonz´ alez Delgado, R. M., Garc´ ıa-Benito, R., P´ erez, E., et al. 2015, A&A, 581, A103, doi: 10.1051/0004-6361/201525938

    work page doi:10.1093/mnras/sty892 2018

  38. [38]

    E., Veale, M., Ma, C.-P., et al

    Greene, J. E., Veale, M., Ma, C.-P., et al. 2019, ApJ, 874, 66, doi: 10.3847/1538-4357/ab01e3

    work page doi:10.3847/1538-4357/ab01e3 2019

  39. [39]

    S., Thrane, E., et al

    Grunthal, K., Nathan, R. S., Thrane, E., et al. 2024, arXiv e-prints, arXiv:2412.01214, doi: 10.48550/arXiv.2412.01214

    work page doi:10.48550/arxiv.2412.01214 2024

  40. [40]

    2012, Research in Astronomy and Astrophysics, 12, 63, doi: 10.1088/1674-4527/12/1/005 H¨ aring, N., & Rix, H.-W

    Gu, J.-H., Xu, H.-G., Wang, J.-Y., et al. 2012, Research in Astronomy and Astrophysics, 12, 63, doi: 10.1088/1674-4527/12/1/005 H¨ aring, N., & Rix, H.-W. 2004, ApJL, 604, L89, doi: 10.1086/383567

    work page doi:10.1088/1674-4527/12/1/005 2012

  41. [41]

    Harris, K

    Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357, doi: 10.1038/s41586-020-2649-2

    work page doi:10.1038/s41586-020-2649-2 2020

  42. [42]

    Hills, J. G. 1983, AJ, 88, 1269, doi: 10.1086/113418

    work page doi:10.1086/113418 1983

  43. [43]

    Holley-Bockelmann, K., & Richstone, D. O. 2000, ApJ, 531, 232, doi: 10.1086/308447

    work page doi:10.1086/308447 2000

  44. [44]

    E., & Hughes, S

    Holz, D. E., & Hughes, S. A. 2005, ApJ, 629, 15, doi: 10.1086/431341

    work page doi:10.1086/431341 2005

  45. [45]

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

    work page doi:10.1109/mcse.2007.55 2007

  46. [46]

    2023, MNRAS, 519, 2083, doi: 10.1093/mnras/stac3677

    Izquierdo-Villalba, D., Sesana, A., & Colpi, M. 2023, MNRAS, 519, 2083, doi: 10.1093/mnras/stac3677

    work page doi:10.1093/mnras/stac3677 2023

  47. [47]

    H., & Backer, D

    Jaffe, A. H., & Backer, D. C. 2003, ApJ, 583, 616, doi: 10.1086/345443

    work page doi:10.1086/345443 2003

  48. [48]

    Z., Blecha, L., & Hernquist, L

    Kelley, L. Z., Blecha, L., & Hernquist, L. 2017, MNRAS, 464, 3131, doi: 10.1093/mnras/stw2452

    work page doi:10.1093/mnras/stw2452 2017

  49. [49]

    Taylor, S. R. 2018, MNRAS, 477, 964, doi: 10.1093/mnras/sty689

    work page doi:10.1093/mnras/sty689 2018

  50. [50]

    Kennicutt, Jr., R. C. 1998, ARA&A, 36, 189, doi: 10.1146/annurev.astro.36.1.189

    work page internal anchor Pith review doi:10.1146/annurev.astro.36.1.189 1998

  51. [51]

    I., & Dehnen, W

    Khonji, N., Gualandris, A., Read, J. I., & Dehnen, W. 2024, ApJ, 974, 204, doi: 10.3847/1538-4357/ad7390

    work page doi:10.3847/1538-4357/ad7390 2024

  52. [52]

    C., Evans, A

    Kim, D. C., Evans, A. S., Stierwalt, S., & Privon, G. C. 2016, ApJ, 824, 122, doi: 10.3847/0004-637X/824/2/122

    work page doi:10.3847/0004-637x/824/2/122 2016

  53. [53]

    J., Blecha, L., Bernhard, P., et al

    Koss, M. J., Blecha, L., Bernhard, P., et al. 2018, Nature, 563, 214, doi: 10.1038/s41586-018-0652-7 Krajnovi´ c, D., Emsellem, E., Cappellari, M., et al. 2011, MNRAS, 414, 2923, doi: 10.1111/j.1365-2966.2011.18560.x Krajnovi´ c, D., Karick, A. M., Davies, R. L., et al. 2013, MNRAS, 433, 2812, doi: 10.1093/mnras/stt905

    work page doi:10.1038/s41586-018-0652-7 2018

  54. [54]

    P., Lauer, T

    Laine, S., van der Marel, R. P., Lauer, T. R., et al. 2003, AJ, 125, 478, doi: 10.1086/345823

    work page doi:10.1086/345823 2003

  55. [55]

    R., Ajhar, E

    Lauer, T. R., Ajhar, E. A., Byun, Y. I., et al. 1995, AJ, 110, 2622, doi: 10.1086/117719

    work page doi:10.1086/117719 1995

  56. [56]

    R., Gebhardt, K., Richstone, D., et al

    Lauer, T. R., Gebhardt, K., Richstone, D., et al. 2002, AJ, 124, 1975, doi: 10.1086/342932

    work page doi:10.1086/342932 2002

  57. [57]

    R., Faber, S

    Lauer, T. R., Faber, S. M., Gebhardt, K., et al. 2005, AJ, 129, 2138, doi: 10.1086/429565

    work page doi:10.1086/429565 2005

  58. [58]

    R., Gebhardt, K., Faber, S

    Lauer, T. R., Gebhardt, K., Faber, S. M., et al. 2007a, ApJ, 664, 226, doi: 10.1086/519229 Predicting Potential Host Galaxies of Supermassive Black Hole Binaries 23

    work page doi:10.1086/519229

  59. [59]

    R., Faber, S

    Lauer, T. R., Faber, S. M., Richstone, D., et al. 2007b, ApJ, 662, 808, doi: 10.1086/518223

    work page doi:10.1086/518223

  60. [60]

    Law-Smith, J., & Eisenstein, D. J. 2017, ApJ, 836, 87, doi: 10.3847/1538-4357/836/1/87

    work page doi:10.3847/1538-4357/836/1/87 2017

  61. [61]

    2014, ApJ, 795, 146, doi: 10.1088/0004-637X/795/2/146

    Lena, D., Robinson, A., Marconi, A., et al. 2014, ApJ, 795, 146, doi: 10.1088/0004-637X/795/2/146

    work page doi:10.1088/0004-637x/795/2/146 2014

  62. [62]

    R., Mingarelli, C

    Lentati, L., Taylor, S. R., Mingarelli, C. M. F., et al. 2015, MNRAS, 453, 2576, doi: 10.1093/mnras/stv1538

    work page doi:10.1093/mnras/stv1538 2015

  63. [63]

    R., & Bonetti, M

    Li, K., Bogdanovi´ c, T., Ballantyne, D. R., & Bonetti, M. 2022, ApJ, 933, 104, doi: 10.3847/1538-4357/ac74b5

    work page doi:10.3847/1538-4357/ac74b5 2022

  64. [64]

    R., & Ma, C.-P

    Liepold, E. R., & Ma, C.-P. 2024, ApJL, 971, L29, doi: 10.3847/2041-8213/ad66b8

    work page doi:10.3847/2041-8213/ad66b8 2024

  65. [65]

    Vigeland, S. J. 2023, ApJ, 945, 78, doi: 10.3847/1538-4357/acb492

    work page doi:10.3847/1538-4357/acb492 2023

  66. [66]

    Liu, T., & Vigeland, S. J. 2021, ApJ, 921, 178, doi: 10.3847/1538-4357/ac1da9

    work page doi:10.3847/1538-4357/ac1da9 2021

  67. [67]

    M., Primack, J., & Madau, P

    Lotz, J. M., Primack, J., & Madau, P. 2004, AJ, 128, 163, doi: 10.1086/421849

    work page doi:10.1086/421849 2004

  68. [68]

    E., McConnell, N., et al

    Ma, C.-P., Greene, J. E., McConnell, N., et al. 2014, The Astrophysical Journal, 795, 158, doi: 10.1088/0004-637X/795/2/158

    work page doi:10.1088/0004-637x/795/2/158 2014

  69. [69]

    F., Faucher-Gigu` ere, C.-A., et al

    Ma, X., Hopkins, P. F., Faucher-Gigu` ere, C.-A., et al. 2016, MNRAS, 456, 2140, doi: 10.1093/mnras/stv2659

    work page doi:10.1093/mnras/stv2659 2016

  70. [70]

    2014, Annual Review of Astronomy and Astrophysics, 52, 415, doi: 10.1146/annurev-astro-081811-125615

    Madau, P., & Dickinson, M. 2014, ARA&A, 52, 415, doi: 10.1146/annurev-astro-081811-125615

    work page internal anchor Pith review doi:10.1146/annurev-astro-081811-125615 2014

  71. [71]

    Mahtessian, A. P. 1998, Astrophysics, 41, 308, doi: 10.1007/BF03036100

    work page doi:10.1007/bf03036100 1998

  72. [72]

    Malmquist, K. G. 1922, Meddelanden fran Lunds Astronomiska Observatorium Serie I, 100, 1

    work page 1922

  73. [73]

    M., Alatalo, K., Blitz, L., et al

    McDermid, R. M., Alatalo, K., Blitz, L., et al. 2015, MNRAS, 448, 3484, doi: 10.1093/mnras/stv105

    work page doi:10.1093/mnras/stv105 2015

  74. [74]

    Mingarelli, C. M. F., Lazio, T. J. W., Sesana, A., et al. 2017, Nature Astronomy, 1, 886, doi: 10.1038/s41550-017-0299-6

    work page doi:10.1038/s41550-017-0299-6 2017

  75. [75]

    2014, MNRAS, 444, 3357, doi: 10.1093/mnras/stt1919

    Naab, T., Oser, L., Emsellem, E., et al. 2014, MNRAS, 444, 3357, doi: 10.1093/mnras/stt1919

    work page doi:10.1093/mnras/stt1919 2014

  76. [76]

    T., Gualandris, A., Read, J

    Nasim, I. T., Gualandris, A., Read, J. I., et al. 2021, MNRAS, 502, 4794, doi: 10.1093/mnras/stab435

    work page doi:10.1093/mnras/stab435 2021

  77. [77]

    2019, ApJ, 872, 76, doi: 10.3847/1538-4357/aafd34

    Nevin, R., Blecha, L., Comerford, J., & Greene, J. 2019, ApJ, 872, 76, doi: 10.3847/1538-4357/aafd34

    work page doi:10.3847/1538-4357/aafd34 2019

  78. [78]

    M., Wild, V., Walcher, C

    Pawlik, M. M., Wild, V., Walcher, C. J., et al. 2016, MNRAS, 456, 3032, doi: 10.1093/mnras/stv2878

    work page doi:10.1093/mnras/stv2878 2016

  79. [79]

    2011, Journal of Machine Learning Research, 12, 2825

    Pedregosa, F., Varoquaux, G., Gramfort, A., et al. 2011, Journal of Machine Learning Research, 12, 2825

    work page 2011

  80. [80]

    R., Charisi, M., & Ma, C.-P

    Petrov, P., Taylor, S. R., Charisi, M., & Ma, C.-P. 2024, arXiv e-prints, arXiv:2406.04409, doi: 10.48550/arXiv.2406.04409

    work page doi:10.48550/arxiv.2406.04409 2024

Showing first 80 references.