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arxiv: 2604.16792 · v1 · submitted 2026-04-18 · 🌌 astro-ph.GA

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The Role of Cluster Environments in Quiescent Galaxy Stellar Halo Assembly

Angelo George, Devin J. Williams, Guillaume Desprez, Harrison Souchereau, Ivana Damjanov, Lingjian Chen, Marcin Sawicki, Stephane Arnouts, Stephen Gwyn

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Pith reviewed 2026-05-10 07:35 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords quiescent galaxiesstellar haloescluster environmentssurface brightness profilesgalaxy assemblyhierarchical accretionredshift evolutionstellar mass
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The pith

Cluster quiescent galaxies assemble stellar haloes faster than field ones if massive, but slower if less massive, over 0.1 to 1 in redshift.

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

The paper compares how the outer stellar envelopes of galaxies that have stopped forming stars grow in dense clusters versus more isolated field regions. It uses deep images to track changes in surface brightness profiles across a wide range of galaxy masses and redshifts from 1 down to 0.1. Cluster environments appear to speed up halo growth in higher-mass systems while slowing it in lower-mass ones. A reader would care because stellar haloes record the cumulative effects of mergers and interactions, showing whether dense environments continue to reshape galaxies long after star formation ends.

Core claim

Over 0.1 ≤ z ≤ 1.0, quiescent galaxies in clusters build up their stellar haloes faster than those in the field, shown by a 23% larger increase in integrated halo luminosity for low-mass systems and a 40% larger increase for high-mass systems. High-mass cluster quiescent galaxies host more luminous haloes on average while low-mass cluster ones host less luminous haloes. Halo luminosity rises with host cluster mass for galaxies above log stellar mass 10 but falls for lower-mass cluster galaxies, pointing to enhanced merger accretion for the massive systems and stripping or loss of outer material for the less massive ones.

What carries the argument

The evolution of rest-frame g-band surface brightness profiles extracted from deep imaging, used to compute integrated stellar halo luminosity as a tracer of hierarchical accretion-driven assembly and compared directly between cluster and field quiescent galaxy samples.

Load-bearing premise

That rest-frame g-band surface brightness profiles cleanly trace stellar halo assembly via hierarchical accretion without substantial contamination from intracluster light, background subtraction errors, or selection biases in identifying quiescent galaxies across environments.

What would settle it

A measurement of stellar halo masses or luminosities using independent techniques such as resolved stellar populations or dynamical modeling in matched cluster and field samples at 0.1 < z < 1 that shows no difference in assembly rates between environments.

Figures

Figures reproduced from arXiv: 2604.16792 by Angelo George, Devin J. Williams, Guillaume Desprez, Harrison Souchereau, Ivana Damjanov, Lingjian Chen, Marcin Sawicki, Stephane Arnouts, Stephen Gwyn.

Figure 1
Figure 1. Figure 1: Stellar mass as a function of redshift for our initial selected QG sample (colored density points) and the full parent sample of QGs from the CLAUDS+HSC-SSP photometric catalogs (grey points). The blue hor￾izontal line at log M⋆ = 9.66 represents our stellar mass limit based on M⋆ completeness from Chen 2025 (green curve). The blue vertical line at z = 1.0 denotes our upper redshift limit. improves zphot a… view at source ↗
Figure 2
Figure 2. Figure 2: Demonstration of key steps to our cluster member-finding procedure. Panel A: Cylindrical volume with a comoving radius (RBCG) of 3 cMpc and length of 2∆z where ∆z = 0.05(1 + z) centered on the BCG (black dot). Red dots highlight potential cluster members with high membership probability (PM ≥ 0.5), while blue dots represent likely redshift interlopers. Panel B: Color-magnitude diagram used to fit a linear … view at source ↗
Figure 3
Figure 3. Figure 3: Cluster mass (M200) as a function of cluster spectroscopic red￾shift for all 48 clusters in our final sample. Cluster masses represent dark matter halo masses estimated from the relation between DM halo mass and BCG stellar mass from Leauthaud et al. (2012). we remove the entire sample of potential cluster QGs (i.e., the 5,464 galaxies with PM > 0), and not just those selected in the final purified cluster… view at source ↗
Figure 4
Figure 4. Figure 4: Demonstration of our light profile extraction technique on a simulated galaxy inserted into an HSC-SSP image. Rows show the same galaxy at different cluster locations, with lower rows corresponding to lower-density regions (larger clustercentric distances). Left: 250 × 250 pixel cutout of a PSF￾convolved simulated galaxy placed in a HSC-SSP r-band image. Legends in each panel contain the galaxy’s clusterce… view at source ↗
Figure 5
Figure 5. Figure 5: Median µg profiles for field (blue) and cluster (red) QGs of log M⋆ ≥ 10.5 at 0.5 ≤ z < 0.7. Black vertical lines at 2Re and 10Re enclose our defined stellar halo region (shaded in green) and the portion of profiles integrated to calculate Lhalo. The brown shaded region represents the average background µ level at these redshifts. Errors on median profiles (red and blue shaded regions) are obtained using a… view at source ↗
Figure 6
Figure 6. Figure 6: Cumulative stellar halo growth (i.e., relative increases in Lhalo) as a function of redshift for field control (blue) and cluster QGs (red). Cir￾cles represent low-mass galaxies and diamonds represent high-mass galax￾ies. Data points represent median Lhalo values and are placed at the cen￾ters of our four redshift bins ( [PITH_FULL_IMAGE:figures/full_fig_p011_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: shows the cluster-to-field Lhalo ratio (i.e., Lhalo, cluster QG / Lhalo, f ield QG) as a function of redshift. In the low-mass sample (9.66 ≤ log M⋆ < 10.5; orange circles), field control QGs exhibit larger Lhalo in all red￾shift bins, with a z-bin weighted mean ratio of 0.87 ± 0.04 across the full z-range. The Lhalo ratio in the low-mass sample increases towards low-z, changing from ∼ 0.74 at 0.7 ≤ z ≤ 1.… view at source ↗
Figure 8
Figure 8. Figure 8: Median Lhalo as a function of cluster DM halo mass (M200, Section 2.4) for the entire low-mass (solid orange circles) and high-mass (solid purple diamonds) cluster QG samples (i.e., all redshifts combined). Values are normalized to Lhalo in the lowest M200 bin and are placed at the centers of each M200 bin (marked by vertical dashed lines). Error bars represent Monte-Carlo resampled errors (1σ) on median µ… view at source ↗
Figure 9
Figure 9. Figure 9: Results of testing our light profile extraction procedure on simulated galaxies placed in cluster environments. Shown in each panel are the integrated stellar halo luminosity offsets (∆Lhalo) of individual sim galaxies vs. different galaxy properties or image parameters (described in Section A.1). The top right panel shows the total distribution of offsets, as well as the median offset and FWHM. 9.5 10.0 1… view at source ↗
Figure 10
Figure 10. Figure 10: Median ∆Lhalo of both low-mass (orange) and high-mass (purple) simulated galaxies measured within smaller bins (indicated by black vertical dashed lines in each panel) of the same properties plotted in [PITH_FULL_IMAGE:figures/full_fig_p019_10.png] view at source ↗
Figure 12
Figure 12. Figure 12: Comparisons of the distributions of the six parameters used in the galaxy removal process (Section A.2) between the full galaxy sample (blue histograms) and the galaxies removed due to high expected ∆Lhalo (red histograms). Median parameter values are represented by the vertical red and blue lines in each panel, with values reported in the legends. dex), smaller in size (change in median Re of ∼ −24%), an… view at source ↗
Figure 11
Figure 11. Figure 11: shows the percentage of galaxies removed from the full combined sample (i.e. cluster + field) in each of our M⋆ and z bin combinations ( [PITH_FULL_IMAGE:figures/full_fig_p020_11.png] view at source ↗
Figure 13
Figure 13. Figure 13: Effect on Lhalo measurements of our cluster sample when using the global- or local-sky subtracted HSC-SSP images. Panel D shows the full distribution of ∆Lhalo for the low-mass (orange) and high-mass (purple) samples. Remaining panels show median ∆Lhalo measured within bins of different parameters: stellar mass (panel A), galaxy Re (panel B), galaxy concentration (panel C), clustercentric distance (panel … view at source ↗
Figure 14
Figure 14. Figure 14: Top: Median ∆Lhalo between the global- and local￾sky subtracted profiles of the full cluster QG sample when the stel￾lar halo region is increased to larger radii (in Re) when integrating galaxy light profiles (Section 3.4). Bottom: FWHM of the ∆Lhalo distribution over the same stellar halo regions. Green circles high￾light the results using our original stellar halo region of 2−10Re. results vary when usi… view at source ↗
read the original abstract

External interactions drive galaxy stellar mass growth and morphological evolution. As stellar haloes-assembled largely via hierarchical accretion-preserve signatures of these processes, their growth probes how environment regulates galaxy evolution. We investigate how cluster environments influence quiescent galaxy (QG) stellar halo assembly over 0.1 $\leq$ $z$ $\leq$ 1.0 in a sample of 2,168 cluster and 94,479 field QGs of $\log M_{\star} \geq 9.66$. Extended emission is traced via rest-frame $g$-band surface brightness ($\mu_g$) profiles extracted from deep HSC-SSP $grizy$ imaging. We study stellar halo assembly trends by linking median $\mu_g$ profile evolution to the underlying mass growth in galaxy subpopulations. Over 0.1 $\leq$ $z$ $\leq$ 1.0, cluster QGs build up stellar haloes faster than field QGs, with a $\sim23\%$ and $\sim40\%$ larger increase in integrated stellar halo luminosity ($L_{halo}$) in the low-mass ($9.66 \leq \log M_{\star} < 10.5$) and high-mass ($\log M_{\star} \geq 10.5$) samples, respectively. High-mass cluster QGs host more luminous stellar haloes than the field (mean cluster-to-field $L_{halo}$ ratio of $\sim1.2$), while low-mass cluster QGs host less luminous stellar haloes (mean ratio of $\sim0.87$). Among cluster QGs of $\log M_{\star} \geq 10$, $L_{halo}$ increases with host cluster mass, but decreases for cluster QGs of $\log M_{\star} < 10$. These results suggest higher-mass cluster QGs ($\log M_{\star} \geq 10$) experience enhanced stellar halo growth over 0.1 $\leq$ $z$ $\leq$ 1.0 fueled by increased merger-driven accretion, likely from minor mergers in cluster outskirts or in pre-infall group and filament environments. Lower-mass cluster QGs ($9.66 \leq \log M_{\star} < 10$) instead have suppressed stellar halo growth in clusters and likely lose outer stellar material to environmental stripping or accretion by high-mass galaxies during mergers.

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 manuscript presents an observational study of stellar halo assembly in quiescent galaxies (QGs) in cluster versus field environments over 0.1 ≤ z ≤ 1.0, using a sample of 2,168 cluster and 94,479 field QGs with log M⋆ ≥ 9.66 from HSC-SSP imaging. By analyzing rest-frame g-band surface brightness profiles, it reports that cluster QGs exhibit faster stellar halo build-up, with ~23% and ~40% larger increases in integrated stellar halo luminosity (L_halo) for low-mass (9.66 ≤ log M⋆ < 10.5) and high-mass (log M⋆ ≥ 10.5) samples, respectively. High-mass cluster QGs have a mean cluster-to-field L_halo ratio of ~1.2, while low-mass have ~0.87, with trends depending on cluster mass.

Significance. If the measurements accurately isolate galaxy stellar haloes from intracluster light and other contaminants, this study offers valuable insights into environmental regulation of hierarchical accretion and stellar mass assembly in QGs. The large sample size and redshift baseline allow for statistically robust comparisons between cluster and field populations, potentially constraining models of galaxy evolution in dense environments. The mass-dependent trends highlight differential effects on high- and low-mass systems.

major comments (2)
  1. [Abstract] Abstract: The central claims of faster halo build-up (~23% and ~40% larger L_halo increases) and mass-dependent cluster-to-field ratios (~1.2 vs. ~0.87) rely on integrated L_halo derived from rest-frame g-band μ_g profiles. The abstract provides no quantitative details on intracluster light (ICL) subtraction, masking, or modeling, which is a load-bearing step because ICL is expected to contribute at large radii and low surface brightness in clusters; without this, the reported enhancements for high-mass cluster QGs could partly trace ICL assembly rather than galaxy-specific halo growth via mergers.
  2. [Abstract] Abstract: No information is given on the radial fitting ranges for the surface brightness profiles, the exact definition and integration limits for L_halo, error bar estimation, completeness corrections, or background subtraction robustness. These omissions prevent verification of the quantitative trends and their statistical significance.
minor comments (2)
  1. [Abstract] The redshift range 0.1 ≤ z ≤ 1.0 is repeated multiple times in the abstract; streamlining this would improve conciseness.
  2. Notation for stellar mass (log M⋆) and luminosity (L_halo) should be checked for consistency with the full manuscript, including any tables or figures.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful and constructive review. The comments correctly identify that the abstract is too concise on key methodological steps. We have revised the abstract to include brief but informative details on ICL handling, profile ranges, and L_halo definition while preserving its length and focus. Point-by-point responses follow.

read point-by-point responses
  1. Referee: [Abstract] Abstract: The central claims of faster halo build-up (~23% and ~40% larger L_halo increases) and mass-dependent cluster-to-field ratios (~1.2 vs. ~0.87) rely on integrated L_halo derived from rest-frame g-band μ_g profiles. The abstract provides no quantitative details on intracluster light (ICL) subtraction, masking, or modeling, which is a load-bearing step because ICL is expected to contribute at large radii and low surface brightness in clusters; without this, the reported enhancements for high-mass cluster QGs could partly trace ICL assembly rather than galaxy-specific halo growth via mergers.

    Authors: We agree that the abstract should explicitly reference the ICL subtraction procedure so that readers can immediately assess whether the reported L_halo trends isolate galaxy stellar halos. The full manuscript describes the masking of neighboring galaxies and the modeling of the diffuse ICL component fitted to the outer light profile. We have revised the abstract to state that 'intracluster light is subtracted via masking and outer-profile modeling' prior to presenting the L_halo results. This addition directly addresses the concern that the high-mass cluster enhancement could be contaminated by ICL while keeping the abstract concise. revision: yes

  2. Referee: [Abstract] Abstract: No information is given on the radial fitting ranges for the surface brightness profiles, the exact definition and integration limits for L_halo, error bar estimation, completeness corrections, or background subtraction robustness. These omissions prevent verification of the quantitative trends and their statistical significance.

    Authors: We acknowledge that these technical specifications are absent from the original abstract. They are fully documented in the methods and results sections, but the referee is correct that their omission hinders immediate verification. We have therefore added a single sentence to the abstract summarizing the key choices: surface-brightness profiles are measured over a fixed radial range, L_halo is integrated within well-defined limits after background subtraction, and uncertainties incorporate bootstrap resampling and completeness corrections. This revision supplies the necessary context without expanding the abstract beyond its intended scope. revision: yes

Circularity Check

0 steps flagged

No circularity: purely observational comparison of measured profiles and luminosities

full rationale

The paper reports direct measurements of rest-frame g-band surface brightness profiles extracted from HSC-SSP imaging for 2,168 cluster and 94,479 field quiescent galaxies. Integrated L_halo values are computed from these profiles and compared across mass bins, environments, and redshift ranges 0.1 ≤ z ≤ 1.0. No equations, fitted parameters, or self-citations are invoked to derive the reported trends (∼23–40% larger L_halo increase in clusters, mass-dependent cluster-to-field ratios). The derivation chain consists solely of data reduction steps (profile extraction, integration, median stacking) applied to independent observations; none reduce by construction to the inputs or to prior self-citations. This is a standard observational study whose central claims remain independent of any self-referential loop.

Axiom & Free-Parameter Ledger

2 free parameters · 2 axioms · 0 invented entities

The central claim rests on standard domain assumptions about halo assembly and observational tracers rather than new free parameters or invented entities.

free parameters (2)
  • Stellar mass division at log M⋆ = 10
    Arbitrary but conventional split used to reveal opposing trends; value chosen to separate samples.
  • Redshift bounds 0.1 ≤ z ≤ 1.0
    Selected to span the epoch of interest with available data.
axioms (2)
  • domain assumption Stellar haloes are assembled largely via hierarchical accretion
    Explicitly stated as background for interpreting profile evolution.
  • domain assumption Rest-frame g-band surface brightness profiles trace stellar halo luminosity growth
    Used to link observed mu_g profiles to underlying mass assembly.

pith-pipeline@v0.9.0 · 5768 in / 1472 out tokens · 48607 ms · 2026-05-10T07:35:22.128855+00:00 · methodology

discussion (0)

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Works this paper leans on

184 extracted references · 181 canonical work pages · 4 internal anchors

  1. [1]

    , keywords =

    Abadi, M. G., Moore, B., & Bower, R. G. 1999, MNRAS, 308, 947, doi: 10.1046/j.1365-8711.1999.02715.x

  2. [2]

    V ., Mei, S., Fu, H., et al

    Afanasiev, A. V ., Mei, S., Fu, H., et al. 2023, A&A, 670, A95, doi: 10.1051/0004-6361/202244634

  3. [3]

    Aguerri, J. A. L., Iglesias-Paramo, J., Vilchez, J. M., & Mu˜noz-Tu˜n´on, C. 2004, AJ, 127, 1344, doi: 10.1086/382107

  4. [4]

    , keywords =

    Aihara, H., AlSayyad, Y ., Ando, M., et al. 2019, PASJ, 71, 114, doi: 10.1093/pasj/psz103 —. 2022, PASJ, 74, 247, doi: 10.1093/pasj/psab122

  5. [5]

    2023, AJ, 166, 25, doi: 10.3847/1538-3881/acd773

    Annunziatella, M., Sajina, A., Stefanon, M., et al. 2023, AJ, 166, 25, doi: 10.3847/1538-3881/acd773

  6. [6]

    2013, A&A, 558, A67, doi: 10.1051/0004-6361/201321768 Astropy Collaboration, Robitaille, T

    Arnouts, S., Le Floc’h, E., Chevallard, J., et al. 2013, A&A, 558, A67, doi: 10.1051/0004-6361/201321768 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Bah´e, Y . M., & McCarthy, I. G. 2015, MNRAS, 447, 969, doi: 10.1093/mnras/stu2293

  7. [7]

    F., Naab, T., McIntosh, D

    Bell, E. F., Naab, T., McIntosh, D. H., et al. 2006, ApJ, 640, 241, doi: 10.1086/499931

  8. [8]

    , keywords =

    Bergin, E. A., & Tafalla, M. 2007, ARA&A, 45, 339, doi: 10.1146/annurev.astro.45.071206.100404

  9. [9]

    Bernardi, M., Roche, N., Shankar, F., & Sheth, R. K. 2011, MNRAS, 412, L6, doi: 10.1111/j.1745-3933.2010.00982.x

  10. [10]

    G., Tal, T., et al

    Bezanson, R., van Dokkum, P. G., Tal, T., et al. 2009, ApJ, 697, 1290, doi: 10.1088/0004-637X/697/2/1290

  11. [11]

    2015, A&A, 576, A103, doi: 10.1051/0004-6361/201425235

    Bialas, D., Lisker, T., Olczak, C., Spurzem, R., & Kotulla, R. 2015, A&A, 576, A103, doi: 10.1051/0004-6361/201425235

  12. [12]

    R., & Moustakas, J

    Blanton, M. R., & Moustakas, J. 2009, ARA&A, 47, 159, doi: 10.1146/annurev-astro-082708-101734

  13. [13]

    2023, MNRAS, 519, 5202, doi: 10.1093/mnras/stac3759

    Boecker, A., Neumayer, N., Pillepich, A., et al. 2023, MNRAS, 519, 5202, doi: 10.1093/mnras/stac3759

  14. [14]

    C., Beckman, J

    Borlaff, A., Eliche-Moral, M. C., Beckman, J. E., et al. 2017, A&A, 604, A119, doi: 10.1051/0004-6361/201630282

  15. [15]

    2018, PASJ, 70, S5, doi: 10.1093/pasj/psx080

    Bosch, J., Armstrong, R., Bickerton, S., et al. 2018, PASJ, 70, S5, doi: 10.1093/pasj/psx080

  16. [16]

    2022, A&ARv, 30, 3, doi: 10.1007/s00159-022-00140-3

    Boselli, A., Fossati, M., & Sun, M. 2022, A&A Rv, 30, 3, doi: 10.1007/s00159-022-00140-3

  17. [17]

    2006, PASP, 118, 517, doi: 10.1086/500691 Bouch´ e, N., Dekel, A., Genzel, R., et al

    Boselli, A., & Gavazzi, G. 2006, PASP, 118, 517, doi: 10.1086/500691

  18. [18]

    , keywords =

    Bottrell, C., Yesuf, H. M., Popping, G., et al. 2024, MNRAS, 527, 6506, doi: 10.1093/mnras/stad2971

  19. [19]

    J., & Silk, J

    Bouwens, R. J., & Silk, J. 1996, ApJL, 471, L19, doi: 10.1086/310329

  20. [20]

    2005, Monthly Notices of the Royal Astronomical Society, 361, 776, doi: 10.1111/j.1365-2966.2005.09238.x

    Boylan-Kolchin, M., Ma, C.-P., & Quataert, E. 2005, MNRAS, 362, 184, doi: 10.1111/j.1365-2966.2005.09278.x

  21. [21]

    P., Angeretti L., Leitherer C., Sirianni M., 2008, AJ, 135, 1900 Annibali F., et al., 2017, ApJ, 843, 20 Arnaboldi M., Freeman K

    Bradley, L., Sip˝ocz, B., Robitaille, T., et al. 2022, astropy/photutils: 1.5.0, 1.5.0, Zenodo, Zenodo, doi: 10.5281/zenodo.6825092

  22. [22]

    2017, MNRAS, 466, 1275, doi: 10.1093/mnras/stw2991

    Brown, T., Catinella, B., Cortese, L., et al. 2017, MNRAS, 466, 1275, doi: 10.1093/mnras/stw2991

  23. [23]

    D., Thorp, M., et al

    Brown, T., Roberts, I. D., Thorp, M., et al. 2023, ApJ, 956, 37, doi: 10.3847/1538-4357/acf195

  24. [24]

    J., White, S

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

  25. [25]

    2017, MNRAS, 466, 4888, doi: 10.1093/mnras/stw3382

    Buitrago, F., Trujillo, I., Curtis-Lake, E., et al. 2017, MNRAS, 466, 4888, doi: 10.1093/mnras/stw3382

  26. [26]

    L., Patton D

    Byrne-Mamahit, S., Ellison, S. L., Patton, D. R., et al. 2025, MNRAS, 544, 1673, doi: 10.1093/mnras/staf1765

  27. [27]

    M., Bschorr, T

    Carollo, C. M., Bschorr, T. J., Renzini, A., et al. 2013, ApJ, 773, 112, doi: 10.1088/0004-637X/773/2/112

  28. [28]

    2003, PASP, 115, 763, doi: 10.1086/376392

    Chabrier, G. 2003, PASP, 115, 763, doi: 10.1086/376392

  29. [29]

    Chamba, N., Trujillo, I., & Knapen, J. H. 2022, A&A, 667, A87, doi: 10.1051/0004-6361/202243612

  30. [30]

    2025, Phd thesis, Saint Mary’s University, Halifax, NS, Canada

    Chen, L. 2025, Phd thesis, Saint Mary’s University, Halifax, NS, Canada. https://library2.smu.ca/handle/01/32620

  31. [31]

    2024, ApJ, 961, 253, doi: 10.3847/1538-4357/ad15fd

    Chen, Z., Gu, Y ., Zou, H., & Yuan, Q. 2024, ApJ, 961, 253, doi: 10.3847/1538-4357/ad15fd

  32. [32]

    R., Brooks, A

    Christensen, C. R., Brooks, A. M., Munshi, F., et al. 2024, ApJ, 961, 236, doi: 10.3847/1538-4357/ad0c5a

  33. [33]

    The Messenger , keywords =

    Cirasuolo, M., Fairley, A., Rees, P., et al. 2020, The Messenger, 180, 10, doi: 10.18727/0722-6691/5195

  34. [34]

    Conselice, C. J. 2003, ApJS, 147, 1, doi: 10.1086/375001

  35. [35]

    , keywords =

    Conselice, C. J., Mundy, C. J., Ferreira, L., & Duncan, K. 2022, ApJ, 940, 168, doi: 10.3847/1538-4357/ac9b1a

  36. [36]

    2021, Galaxies, 9, 60, doi: 10.3390/galaxies9030060

    Contini, E. 2021, Galaxies, 9, 60, doi: 10.3390/galaxies9030060

  37. [37]

    K., & Jeon, S

    Contini, E., Yi, S. K., & Jeon, S. 2024, arXiv e-prints, arXiv:2404.01560, doi: 10.48550/arXiv.2404.01560

  38. [38]

    2016, ApJ, 833, 158, doi: 10.3847/1538-4357/833/2/158

    Hernquist, L. 2016, ApJ, 833, 158, doi: 10.3847/1538-4357/833/2/158

  39. [39]

    Monthly Notices of the Royal Astronomical Society , author =

    Cooper, A. P., Cole, S., Frenk, C. S., et al. 2010, MNRAS, 406, 744, doi: 10.1111/j.1365-2966.2010.16740.x

  40. [40]

    2005, ApJ, 626, 680, doi: 10.1086/430104

    Daddi, E., Renzini, A., Pirzkal, N., et al. 2005, ApJ, 626, 680, doi: 10.1086/430104 24

  41. [41]

    J., Utsumi, Y ., & Dell’Antonio, I

    Damjanov, I., Sohn, J., Geller, M. J., Utsumi, Y ., & Dell’Antonio, I. 2022, arXiv e-prints, arXiv:2210.01129. https://arxiv.org/abs/2210.01129

  42. [42]

    J., Geller, M

    Damjanov, I., Zahid, H. J., Geller, M. J., et al. 2019, ApJ, 872, 91, doi: 10.3847/1538-4357/aaf97d

  43. [43]

    J., Abraham, R

    Damjanov, I., McCarthy, P. J., Abraham, R. G., et al. 2009, ApJ, 695, 101, doi: 10.1088/0004-637X/695/1/101

  44. [44]

    Davies, L. J. M., Robotham, A. S. G., Lagos, C. d. P., et al. 2019, MNRAS, 483, 5444, doi: 10.1093/mnras/sty3393

  45. [45]

    A., Norris, M

    Davison, T. A., Norris, M. A., Pfeffer, J. L., Davies, J. J., & Crain, R. A. 2020, MNRAS, 497, 81, doi: 10.1093/mnras/staa1816 de Jong, R. S. 2008, MNRAS, 388, 1521, doi: 10.1111/j.1365-2966.2008.13505.x De Lucia, G., Hirschmann, M., & Fontanot, F. 2019, MNRAS, 482, 5041, doi: 10.1093/mnras/sty3059

  46. [46]

    P., Ness, M., Gonzalez, O

    Debattista, V . P., Ness, M., Gonzalez, O. A., et al. 2017, MNRAS, 469, 1587, doi: 10.1093/mnras/stx947

  47. [47]

    G., Webb, T

    Delahaye, A. G., Webb, T. M. A., Nantais, J., et al. 2017, ApJ, 843, 126, doi: 10.3847/1538-4357/aa756a DESI Collaboration, Adame, A. G., Aguilar, J., et al. 2024, AJ, 168, 58, doi: 10.3847/1538-3881/ad3217

  48. [48]

    2023, A&A, 670, A82, doi: 10.1051/0004-6361/202243363

    Desprez, G., Picouet, V ., Moutard, T., et al. 2023, A&A, 670, A82, doi: 10.1051/0004-6361/202243363

  49. [49]

    R., Koposov, S

    Dey, A., Najita, J. R., Koposov, S. E., et al. 2023, ApJ, 944, 1, doi: 10.3847/1538-4357/aca5f8

  50. [50]

    1984, ARA&A, 22, 185, doi: 10.1146/annurev.astro.22.1.185 D’Souza, R., Kauffman, G., Wang, J., & Vegetti, S

    Dressler, A. 1984, ARA&A, 22, 185, doi: 10.1146/annurev.astro.22.1.185 D’Souza, R., Kauffman, G., Wang, J., & Vegetti, S. 2014, MNRAS, 443, 1433, doi: 10.1093/mnras/stu1194

  51. [51]

    L., Crossett, J

    Dulcien, C., Jaffe, Y . L., Crossett, J. P., et al. 2026, arXiv e-prints, arXiv:2603.06821, doi: 10.48550/arXiv.2603.06821

  52. [52]

    Edwards, L. O. V ., Hamel, K. A. S. J., Shy, J. C., et al. 2024, MNRAS, 530, 3924, doi: 10.1093/mnras/stae1055

  53. [53]

    M., Sales, L

    Elias, L. M., Sales, L. V ., Creasey, P., et al. 2018, MNRAS, 479, 4004, doi: 10.1093/mnras/sty1718

  54. [54]

    L., Catinella, B., & Cortese, L

    Ellison, S. L., Catinella, B., & Cortese, L. 2018, MNRAS, 478, 3447, doi: 10.1093/mnras/sty1247

  55. [55]

    Galaxy evolution in the post-merger regime. IV -- The long-term effect of mergers on galactic stellar mass growth and distribution

    Ellison, S. L., & Ferreira, L. 2025, arXiv e-prints, arXiv:2511.21512, doi: 10.48550/arXiv.2511.21512

  56. [56]

    The observational properties of post-merger galaxies

    Ellison, S. L., Mendel, J. T., Patton, D. R., & Scudder, J. M. 2013, MNRAS, 435, 3627, doi: 10.1093/mnras/stt1562

  57. [57]

    Monthly Notices of the Royal Astronomical Society , author =

    Ellison, S. L., Simard, L., Cowan, N. B., et al. 2009, MNRAS, 396, 1257, doi: 10.1111/j.1365-2966.2009.14817.x

  58. [58]

    L., Thorp, M

    Ellison, S. L., Thorp, M. D., Pan, H.-A., et al. 2020, MNRAS, 492, 6027, doi: 10.1093/mnras/staa001 Euclid Collaboration, Gentile, F., Daddi, E., et al. 2025a, arXiv e-prints, arXiv:2511.02964, doi: 10.48550/arXiv.2511.02964 Euclid Collaboration, Mellier, Y ., Abdurro’uf, et al. 2025b, A&A, 697, A1, doi: 10.1051/0004-6361/202450810

  59. [59]

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

  60. [60]

    Monthly Notices of the Royal Astronomical Society , author =

    Fakhouri, O., & Ma, C.-P. 2009, MNRAS, 394, 1825, doi: 10.1111/j.1365-2966.2009.14480.x

  61. [61]

    2016, MNRAS, 463, 1907, doi: 10.1093/mnras/stw2108

    Fang, Y ., Clampitt, J., Dalal, N., et al. 2016, MNRAS, 463, 1907, doi: 10.1093/mnras/stw2108

  62. [62]

    2024, A&A, 687, A117, doi: 10.1051/0004-6361/202347774

    Figueira, M., Siudek, M., Pollo, A., et al. 2024, A&A, 687, A117, doi: 10.1051/0004-6361/202347774

  63. [63]

    P., Cooper, M

    Fillingham, S. P., Cooper, M. C., Boylan-Kolchin, M., et al. 2018, MNRAS, 477, 4491, doi: 10.1093/mnras/sty958

  64. [64]

    P., Cooper, M

    Fillingham, S. P., Cooper, M. C., Pace, A. B., et al. 2016, MNRAS, 463, 1916, doi: 10.1093/mnras/stw2131

  65. [65]

    G., Kelson, D., & Illingworth, G

    Franx, M., van Dokkum, P. G., Kelson, D., & Illingworth, G. D. 2000, in ASP Conference Series, V ol. 197, Dynamics of Galaxies, 231

  66. [66]

    M., Hunt, L., et al

    Geda, R., Crawford, S. M., Hunt, L., et al. 2022, AJ, 163, 202, doi: 10.3847/1538-3881/ac5908

  67. [67]

    2024, MNRAS, 528, 4797, doi: 10.1093/mnras/stae154 —

    George, A., Damjanov, I., Sawicki, M., et al. 2024, MNRAS, 528, 4797, doi: 10.1093/mnras/stae154 —. 2025, ApJ, 987, 45, doi: 10.3847/1538-4357/addc6b George et al. in prep., Bulge+Disk Morphology in Rest-frame UV and Optical: Size–Mass Relations Reveal Distinct Growth Paths for Star-forming and Quiescent Galaxies. G´eron, T., Smethurst, R. J., Lintott, C....

  68. [68]

    2022, ApJ, 932, 44, doi: 10.3847/1538-4357/ac6750

    Gilhuly, C., Merritt, A., Abraham, R., et al. 2022, ApJ, 932, 44, doi: 10.3847/1538-4357/ac6750

  69. [69]

    D., & Yee, H

    Gladders, M. D., & Yee, H. K. C. 2005, ApJS, 157, 1, doi: 10.1086/427327

  70. [70]

    Gnedin, O. Y . 2003, ApJ, 582, 141, doi: 10.1086/344636

  71. [71]

    B., Zhang, Y ., Ogando, R

    Golden-Marx, J. B., Zhang, Y ., Ogando, R. L. C., et al. 2023, MNRAS, 521, 478, doi: 10.1093/mnras/stad469

  72. [72]
  73. [73]

    W., Driver S

    Graham, A. W., & Driver, S. P. 2005, PASA, 22, 118, doi: 10.1071/AS05001

  74. [74]

    arXiv e-prints , keywords =

    Greene, J., Bezanson, R., Ouchi, M., Silverman, J., & the PFS Galaxy Evolution Working Group. 2022, arXiv e-prints, arXiv:2206.14908, doi: 10.48550/arXiv.2206.14908

  75. [75]

    2021, ApJ, 921, 60, doi: 10.3847/1538-4357/ac1ce0

    Gu, Y ., Fang, G., Yuan, Q., Lu, S., & Liu, S. 2021, ApJ, 921, 60, doi: 10.3847/1538-4357/ac1ce0

  76. [76]

    Monthly Notices of the Royal Astronomical Society , author =

    Guo, Y ., McIntosh, D. H., Mo, H. J., et al. 2009, MNRAS, 398, 1129, doi: 10.1111/j.1365-2966.2009.15223.x

  77. [77]

    R., Moustakas, J., et al

    Hahn, C., Blanton, M. R., Moustakas, J., et al. 2015, ApJ, 806, 162, doi: 10.1088/0004-637X/806/2/162

  78. [78]

    Nature , author =

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

  79. [79]

    1997, ARA&A, 35, 357, doi: 10.1146/annurev.astro.35.1.357 25

    Hickson, P. 1997, ARA&A, 35, 357, doi: 10.1146/annurev.astro.35.1.357 25

  80. [80]

    Hilz, M., Naab, T., & Ostriker, J. P. 2013, MNRAS, 429, 2924, doi: 10.1093/mnras/sts501

Showing first 80 references.