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arxiv: 2606.26252 · v1 · pith:K5ACOU2Onew · submitted 2026-06-24 · 🌌 astro-ph.GA

Cluster vs Field: Clear Evidence for a Morphology-Density Relation in All Environments at zsim1.6

Westley Brown , Adam Muzzin , Jasleen Matharu , Gillian Wilson , Julie B. Nantais , Ben Forrest , Ricardo Demarco , Allison Noble
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Tracy Webb
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Pith reviewed 2026-06-26 01:39 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords morphology-density relationhigh-redshift galaxiesgalaxy clustersSersic indexstellar massgalaxy environmentz~1.6disk and bulge galaxies
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The pith

A morphology-density relation already exists for galaxies in both clusters and the field at redshift 1.6.

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

The paper measures galaxy structure using Sersic index from rest-frame optical imaging in three clusters at z∼1.6 and in field galaxies from 3D-HST. It shows that the fraction of bulge-like galaxies rises and disk-like galaxies falls as local density increases in both environments. The same positive trend appears between median Sersic index and density. Stellar mass also correlates with Sersic index, though the mass at which most galaxies become bulge-like differs slightly between samples. A reader would care because the result indicates the relation forms early and does not depend on cluster-specific processes.

Core claim

In both the SpARCS cluster sample and the 3D-HST field sample at z∼1.6, the fraction of bulge-like galaxies increases and the fraction of disk-like galaxies decreases with rising local density. Median Sersic index shows a similar positive trend with density in both samples. The data indicate that the morphology-density relation is already established at this epoch and appears independent of whether galaxies sit in a cluster or the field.

What carries the argument

Sersic index measured in rest-frame R-band from F160W imaging, used to classify galaxies as disk-like, bulge-like or intermediate and to track how structure changes with local density from slit and grism spectroscopy.

Load-bearing premise

Local density measurements from slit and grism spectroscopy are comparably accurate and free of selection bias in the cluster and field samples.

What would settle it

A larger field sample at the same redshift showing no rise in median Sersic index with local density would falsify the claim that the morphology-density relation operates independently of global environment.

Figures

Figures reproduced from arXiv: 2606.26252 by Adam Muzzin, Allison Noble, Ben Forrest, Gillian Wilson, Jasleen Matharu, Julie B. Nantais, Ricardo Demarco, Tracy Webb, Westley Brown.

Figure 1
Figure 1. Figure 1: Examples of grism spectra and grizli outputs for two different cluster galaxies. The leftmost panels show the extracted 2D grism spectra from two orients (top and middle), as well as the residual of both with the galaxy continuum and contamination removed (bottom). Object IDs are given in the upper right of the top panel. Numbers in the upper left of the top and middle panels denote the orient of each gris… view at source ↗
Figure 2
Figure 2. Figure 2: Histograms showing the number density of galaxies from each cluster catalog as a function of F160W magnitude. Solid red lines show a power law fit to the histogram data. We use the difference between the power law fit and the histogram data to determine the 80 percent magnitude limit for each cluster. The magnitude limits are shown as dashed blue lines. the spectroscopic redshift of the brightest cluster g… view at source ↗
Figure 3
Figure 3. Figure 3: Most galaxies in our clusters are well-fit with a single S´ersic profile—however, we note that there are a few galaxies where the residuals display a sharp peak in the center and/or a thin ring around the core. We do not comment on the origin of these features, nor do we attempt to modify our fits to specifically accommodate this small subset of objects. We remove any galaxies from our cluster member sam￾p… view at source ↗
Figure 4
Figure 4. Figure 4: The binned morphology-density relation in cluster galaxies (left) and field galaxies (right) at z ∼ 1.6. The fraction of bulge-like galaxies are shown as yellow squares, intermediate galaxies as green triangles, and disk-like galaxies as purple circles. Error bars represent the 68 percent credible interval. The number of galaxies in each bin is underplotted as a grey histogram, following the right-hand y-a… view at source ↗
Figure 5
Figure 5. Figure 5: The morphology-density relation in cluster galaxies (left) and field galaxies (right) at z ∼ 1.6, plotted using a fixed-width box kernel as described in Section 4.1. The fraction of bulge-like galaxies is shown as a yellow line with square symbols, intermediate galaxies as a green line with triangles, and disk-like galaxies as a purple line with circles. Symbols are placed along each line showing the close… view at source ↗
Figure 6
Figure 6. Figure 6: The fraction of bulge-like, intermediate, and disk-like galaxies as a function of projected local galaxy density, ΣN , in both the cluster (red) and field sample (cyan). Thin lines and shaded regions show the data plotted using a fixed-width box kernel. Thick lines show the best-fit linear trendlines for cluster galaxies (solid red) and field galaxies (dashed cyan). Parameters for each trendline are given … view at source ↗
Figure 7
Figure 7. Figure 7: Median S´ersic index as a function of projected local galaxy density, ΣN , for cluster galaxies (solid red) and field galaxies (solid cyan), plotted using a fixed-width box kernel. Shaded regions show the 95% confidence interval from bootstrapping. Horizontal dotted lines indicate n = 1.5 and n = 2.5. The upper panel shows the number of field galaxies (light grey) and cluster galaxies (darker grey) in each… view at source ↗
Figure 8
Figure 8. Figure 8: The binned morphology-density relation in the unified sample at z ∼ 1.6. The plot is shown as in [PITH_FULL_IMAGE:figures/full_fig_p014_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: The morphology-density relation in the unified sample at z ∼ 1.6, plotted using a fixed-width box kernel. The plot is shown as in [PITH_FULL_IMAGE:figures/full_fig_p014_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: The morphology-mass relation in cluster galaxies (left) and field galaxies (right) at z ∼ 1.6, plotted using a fixed￾width box kernel as described in Section 4.2. The fraction of bulge-like galaxies is shown as a yellow line with square symbols, intermediate galaxies as a green line with triangles, and disk-like galaxies as a purple line with circles. Symbols are placed along each line showing the closest… view at source ↗
Figure 11
Figure 11. Figure 11: The fraction of bulge-like, intermediate, and disk-like galaxies as a function of galaxy stellar mass, log(M∗/M⊙), in both the cluster (red) and field sample (cyan). Thin lines and shaded regions show the data plotted using a fixed-width box kernel. Thick lines show the best-fit trendlines for cluster galaxies (solid red) and field galaxies (dashed cyan). Parameters for each trendline are given in [PITH_… view at source ↗
Figure 12
Figure 12. Figure 12: Median S´ersic index as a function of galaxy stellar mass for cluster galaxies (solid red) and field galaxies (solid cyan), plotted using a fixed-width box kernel. Shaded regions show the 95% confidence interval from bootstrap￾ping. Horizontal dotted lines indicate n = 1.5 and n = 2.5. The upper panel shows the number of field galaxies (light grey) and cluster galaxies (darker grey) in each bin as a stack… view at source ↗
Figure 13
Figure 13. Figure 13: Left: Median stellar mass as a function of projected local galaxy density, ΣN . Right: Median local density as a function of galaxy stellar mass, log(M∗/M⊙). Trends in cluster galaxies are shown in red, while field galaxies are shown in cyan, plotted using fixed-width box kernels. Shaded regions show the 95% confidence interval from bootstrapping. Upper panels show the number of field galaxies (light grey… view at source ↗
read the original abstract

We explore the relationship between galaxy structure, stellar mass, and local galaxy density in three SpARCS clusters at $z\sim1.6$ and compare with field galaxies from the 3D-HST survey. Our cluster and field data include: 1) unprecedented multiband photometry, allowing for accurate stellar mass estimates; 2) extensive slit and grism spectroscopy targeting both star-forming and quiescent galaxies, allowing for high-accuracy local density measurements; and 3) deep imaging in F160W, allowing for accurate rest-frame optical morphologies. Using S\'ersic index measured in rest-frame R-band, we classify galaxies as disk-like, bulge-like, and intermediate. Our sample includes 111 cluster galaxies and 458 field galaxies with reliable S\'ersic measurements. We find that a morphology-density relation is already in-place in both cluster and field galaxies at $z\sim1.6$, such that as local density increases, the fraction of bulge-like galaxies increases and disk-like galaxies decreases. Both samples show similar positive trends between median S\'ersic index and local density. Additionally, we find a general positive relationship between S\'ersic index and stellar mass. The majority of galaxies remain disk-like until reaching stellar masses above $10^{10.25} M_\odot$ in the cluster or $10^{10.8} M_\odot$ in the field, however, we cannot conclude whether the differences in stellar mass trends are significant. Overall, our results show clear morphology-density and morphology-mass relations in place at $z\sim1.6$ and oppose the idea that cluster-specific processes are solely responsible the morphology-density relation. Our data further suggest that the morphology-density relation may be independent of global environment at this epoch.

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 claims that a morphology-density relation is already in place at z∼1.6 in both SpARCS cluster and 3D-HST field galaxies, with the fraction of bulge-like galaxies (high Sérsic index) increasing and disk-like galaxies decreasing as local density increases; similar positive trends between median Sérsic index and local density in both samples suggest the relation may be independent of global environment. The analysis uses 111 cluster and 458 field galaxies with reliable Sérsic measurements from F160W imaging, stellar masses from multiband photometry, and local densities from slit/grism spectroscopy.

Significance. If the local density estimates prove comparable, the result would indicate that the morphology-density relation is established by z∼1.6 across environments and is not driven solely by cluster-specific processes. The consistent use of rest-frame optical morphologies and stellar mass estimates across samples is a methodological strength supporting the observational comparison.

major comments (2)
  1. [Methods (local density estimation)] § on local density measurements (Methods): The claim that the morphology-density relation is independent of global environment requires the local density metric to be comparably accurate and free of differential bias between the SpARCS slit-spectroscopy sample and the 3D-HST grism-spectroscopy sample. The manuscript provides no explicit tests (e.g., mock catalogs or cross-method comparisons) showing that the chosen estimator (projected nearest-neighbor or fixed-aperture surface density) yields consistent results given the differing redshift precision, line-of-sight contamination, and selection completeness of the two spectroscopic techniques.
  2. [Results (morphology-density trends)] Results (trends and figures): The reported similarity in Sérsic-index vs. density trends between cluster and field is presented without error bars on the binned medians or fractions, without sample completeness corrections as a function of density, and without robustness checks against alternative density definitions. These omissions make it impossible to evaluate whether the observed trends are statistically significant or could arise from measurement systematics.
minor comments (1)
  1. [Abstract] Abstract: The stellar-mass thresholds at which galaxies remain disk-like (10^{10.25} M_⊙ in clusters vs. 10^{10.8} M_⊙ in the field) are stated without any assessment of whether the difference is significant given the respective sample sizes and mass distributions.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments, which highlight important aspects of our analysis that require clarification and strengthening. We address each major comment below and will incorporate the suggested improvements in a revised manuscript.

read point-by-point responses

  1. Referee: [Methods (local density estimation)] § on local density measurements (Methods): The claim that the morphology-density relation is independent of global environment requires the local density metric to be comparably accurate and free of differential bias between the SpARCS slit-spectroscopy sample and the 3D-HST grism-spectroscopy sample. The manuscript provides no explicit tests (e.g., mock catalogs or cross-method comparisons) showing that the chosen estimator (projected nearest-neighbor or fixed-aperture surface density) yields consistent results given the differing redshift precision, line-of-sight contamination, and selection completeness of the two spectroscopic techniques.

    Authors: We agree that explicit validation is needed to support the claim of independence from global environment. In the revised manuscript we will add a dedicated subsection (or appendix) presenting mock-catalog tests that incorporate the measured redshift precision, line-of-sight contamination rates, and selection completeness of both the slit and grism samples. These tests will quantify any differential bias in the adopted nearest-neighbor density estimator and demonstrate that the metric remains comparable across the two datasets. revision: yes

  2. Referee: [Results (morphology-density trends)] Results (trends and figures): The reported similarity in Sérsic-index vs. density trends between cluster and field is presented without error bars on the binned medians or fractions, without sample completeness corrections as a function of density, and without robustness checks against alternative density definitions. These omissions make it impossible to evaluate whether the observed trends are statistically significant or could arise from measurement systematics.

    Authors: We accept that the current presentation lacks these elements. In the revision we will (i) add bootstrap-derived error bars to all binned medians and fractions in the relevant figures, (ii) include a quantitative assessment of sample completeness versus local density for both the cluster and field samples, and (iii) perform and report robustness checks using an alternative fixed-aperture surface-density estimator. These additions will allow a direct evaluation of statistical significance and potential systematics. revision: yes

Circularity Check

0 steps flagged

No circularity: purely observational comparison of measured quantities

full rationale

The paper reports direct observational trends between measured Sersic index (morphology) and local density (from spectroscopy) in two independent samples. No equations, fitted parameters, or derivations are presented that reduce the reported morphology-density relation to inputs by construction. No self-citation chains, uniqueness theorems, or ansatzes are invoked as load-bearing steps. The central claim rests on empirical comparison of data points, which is self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

Observational study; central claim rests on standard assumptions about photometric redshifts, stellar population synthesis models for mass estimates, and the validity of Sersic index as a morphology proxy. No free parameters or invented entities are introduced in the abstract.

axioms (2)
  • domain assumption Sersic index measured in rest-frame R-band reliably classifies galaxies as disk-like or bulge-like
    Invoked when defining the morphology categories used for the density trends.
  • domain assumption Local density estimates from spectroscopy are unbiased between cluster and field samples
    Required for the direct cluster-field comparison.

pith-pipeline@v0.9.1-grok · 5888 in / 1313 out tokens · 23451 ms · 2026-06-26T01:39:47.554891+00:00 · methodology

discussion (0)

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Works this paper leans on

77 extracted references · 76 canonical work pages · 3 internal anchors

  1. [1]

    G., van den Bergh, S., & Nair, P

    Abraham, R. G., van den Bergh, S., & Nair, P. 2003, ApJ, 588, 218, doi: 10.1086/373919

    work page doi:10.1086/373919 2003

  2. [2]

    L., Muzzin, A., Bah´ e, Y

    Ahad, S. L., Muzzin, A., Bah´ e, Y. M., & Hoekstra, H. 2024, MNRAS, 528, 6329, doi: 10.1093/mnras/stae341

    work page doi:10.1093/mnras/stae341 2024

  3. [3]

    and Navarro, Julio F

    Balogh, M. L., Navarro, J. F., & Morris, S. L. 2000, ApJ, 540, 113, doi: 10.1086/309323

    work page doi:10.1086/309323 2000

  4. [4]

    , keywords =

    Bamford, S. P., Nichol, R. C., Baldry, I. K., et al. 2009, MNRAS, 393, 1324, doi: 10.1111/j.1365-2966.2008.14252.x

    work page doi:10.1111/j.1365-2966.2008.14252.x 2009

  5. [5]

    M., et al

    Bassett, R., Papovich, C., Lotz, J. M., et al. 2013, ApJ, 770, 58, doi: 10.1088/0004-637X/770/1/58

    work page doi:10.1088/0004-637x/770/1/58 2013

  6. [6]

    Bekki, K., & Couch, W. J. 2011, MNRAS, 415, 1783, doi: 10.1111/j.1365-2966.2011.18821.x

    work page doi:10.1111/j.1365-2966.2011.18821.x 2011

  7. [7]

    F., van der Wel , A., Papovich , C., et al

    Bell, E. F., van der Wel, A., Papovich, C., et al. 2012, ApJ, 753, 167, doi: 10.1088/0004-637X/753/2/167

    work page doi:10.1088/0004-637x/753/2/167 2012

  8. [8]

    , keywords =

    Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393, doi: 10.1051/aas:1996164

    work page doi:10.1051/aas:1996164 1996

  9. [9]

    Bluck, A. F. L., Bottrell, C., Teimoorinia, H., et al. 2019, MNRAS, 485, 666, doi: 10.1093/mnras/stz363

    work page doi:10.1093/mnras/stz363 2019

  10. [10]

    doi:10.5281/zenodo.8370018 , version =

    Brammer, G. 2023, grizli, 1.9.11, Zenodo, doi: 10.5281/zenodo.8370018 22

    work page doi:10.5281/zenodo.8370018 2023

  11. [11]

    EAZY: A Fast, Public Photometric Redshift Code

    Brammer, G. B., van Dokkum, P. G., & Coppi, P. 2008, ApJ, 686, 1503, doi: 10.1086/591786

    work page internal anchor Pith review doi:10.1086/591786 2008

  12. [12]

    and van Dokkum, Pieter G

    Brammer, G. B., van Dokkum, P. G., Franx, M., et al. 2012, ApJS, 200, 13, doi: 10.1088/0067-0049/200/2/13

    work page doi:10.1088/0067-0049/200/2/13 2012

  13. [13]

    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

  14. [14]

    J., & H¨ außler, B

    Buitrago, F., Trujillo, I., Conselice, C. J., & H¨ außler, B. 2013, MNRAS, 428, 1460, doi: 10.1093/mnras/sts124

    work page doi:10.1093/mnras/sts124 2013

  15. [15]

    , keywords =

    Calvi, R., Poggianti, B. M., Fasano, G., & Vulcani, B. 2012, MNRAS, 419, L14, doi: 10.1111/j.1745-3933.2011.01168.x10.1086/122140

    work page doi:10.1111/j.1745-3933.2011.01168.x10.1086/122140 2012

  16. [16]

    2007, ApJS, 172, 270, doi: 10.1086/516591

    Cassata, P., Guzzo, L., Franceschini, A., et al. 2007, ApJS, 172, 270, doi: 10.1086/516591

    work page doi:10.1086/516591 2007

  17. [17]

    2007, ApJ, 671, 1497, doi: 10.1086/521595

    Castellano, M., Salimbeni, S., Trevese, D., et al. 2007, ApJ, 671, 1497, doi: 10.1086/521595

    work page doi:10.1086/521595 2007

  18. [18]

    J., Lidman, C., et al

    Cerulo, P., Couch, W. J., Lidman, C., et al. 2017, MNRAS, 472, 254, doi: 10.1093/mnras/stx1687

    work page doi:10.1093/mnras/stx1687 2017

  19. [19]

    2014, ApJL, 782, L3, doi: 10.1088/2041-8205/782/1/L3

    Chiang, Y.-K., Overzier, R., & Gebhardt, K. 2014, ApJL, 782, L3, doi: 10.1088/2041-8205/782/1/L3

    work page doi:10.1088/2041-8205/782/1/l3 2014

  20. [20]

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

    work page doi:10.1086/375001 2003

  21. [21]

    C., Newman, J

    Cooper, M. C., Newman, J. A., Madgwick, D. S., et al. 2005, ApJ, 634, 833, doi: 10.1086/432868

    work page doi:10.1086/432868 2005

  22. [22]

    J., Noble, A

    Cramer, W. J., Noble, A. G., Massingill, K., et al. 2023, ApJ, 944, 213, doi: 10.3847/1538-4357/acae96

    work page doi:10.3847/1538-4357/acae96 2023

  23. [23]

    J., Noble, A

    Cramer, W. J., Noble, A. G., Rudnick, G., et al. 2024, ApJ, 975, 144, doi: 10.3847/1538-4357/ad7798 de Vaucouleurs, G. 1961, ApJS, 5, 233, doi: 10.1086/190056

    work page doi:10.3847/1538-4357/ad7798 2024

  24. [24]

    G., Webb, T

    Delahaye, A. G., Webb, T. M. A., Nantais, J., et al. 2017, ApJ, 843, 126, doi: 10.3847/1538-4357/aa756a

    work page doi:10.3847/1538-4357/aa756a 2017

  25. [25]

    and Davis, Marc , month = feb, year =

    Djorgovski, S., & Davis, M. 1987, ApJ, 313, 59, doi: 10.1086/164948 D’Onofrio, M., Marziani, P., & Buson, L. 2015, Frontiers in Astronomy and Space Sciences, 2, 4, doi: 10.3389/fspas.2015.00004

    work page doi:10.1086/164948 1987

  26. [26]

    , keywords =

    Dressler, A. 1980, ApJ, 236, 351, doi: 10.1086/157753

    work page doi:10.1086/157753 1980

  27. [27]

    Euclid Quick Data Release (Q1): The evolution of the passive-density and morphology-density relations between $z=0.25$ and $z=1$

    Dressler, A., Oemler, Augustus, J., Couch, W. J., et al. 1997, ApJ, 490, 577, doi: 10.1086/304890 Euclid Collaboration, Cleland, C., Mei, S., et al. 2025, arXiv e-prints, arXiv:2503.15313, doi: 10.48550/arXiv.2503.15313

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1086/304890 1997

  28. [28]

    M., Couch, W

    Fasano, G., Poggianti, B. M., Couch, W. J., et al. 2000, ApJ, 542, 673, doi: 10.1086/317047

    work page doi:10.1086/317047 2000

  29. [29]

    M., Bettoni, D., et al

    Fasano, G., Poggianti, B. M., Bettoni, D., et al. 2015, MNRAS, 449, 3927, doi: 10.1093/mnras/stv500

    work page doi:10.1093/mnras/stv500 2015

  30. [30]

    Freeman, K. C. 1970, ApJ, 160, 811, doi: 10.1086/150474

    work page doi:10.1086/150474 1970

  31. [31]

    , keywords =

    Goto, T., Yamauchi, C., Fujita, Y., et al. 2003, MNRAS, 346, 601, doi: 10.1046/j.1365-2966.2003.07114.x

    work page doi:10.1046/j.1365-2966.2003.07114.x 2003

  32. [32]

    , archivePrefix = "arXiv", eprint =

    Grogin, N. A., Kocevski, D. D., Faber, S. M., et al. 2011, ApJS, 197, 35, doi: 10.1088/0067-0049/197/2/35

    work page doi:10.1088/0067-0049/197/2/35 2011

  33. [33]

    and Gott, III, J

    Gunn, J. E., & Gott, III, J. R. 1972, ApJ, 176, 1, doi: 10.1086/151605

    work page doi:10.1086/151605 1972

  34. [34]

    M., Johnson, H

    Harrison, C. M., Johnson, H. L., Swinbank, A. M., et al. 2017, MNRAS, 467, 1965, doi: 10.1093/mnras/stx217

    work page doi:10.1093/mnras/stx217 2017

  35. [35]

    2021, ApJ, 912, 87, doi: 10.3847/1538-4357/abed4d

    Hayden, B., Rubin, D., Boone, K., et al. 2021, ApJ, 912, 87, doi: 10.3847/1538-4357/abed4d

    work page doi:10.3847/1538-4357/abed4d 2021

  36. [36]

    2010, ApJ, 711, 192, doi: 10.1088/0004-637X/711/1/192

    Rudnick, G. 2010, ApJ, 711, 192, doi: 10.1088/0004-637X/711/1/192

    work page doi:10.1088/0004-637x/711/1/192 2010

  37. [37]

    , keywords =

    Kauffmann, G., Heckman, T. M., White, S. D. M., et al. 2003, MNRAS, 341, 54, doi: 10.1046/j.1365-8711.2003.06292.x

    work page doi:10.1046/j.1365-8711.2003.06292.x 2003

  38. [38]

    , archivePrefix = "arXiv", eprint =

    Kawinwanichakij, L., Papovich, C., Quadri, R. F., et al. 2017, ApJ, 847, 134, doi: 10.3847/1538-4357/aa8b75

    work page doi:10.3847/1538-4357/aa8b75 2017

  39. [39]

    , archivePrefix = "arXiv", eprint =

    Koekemoer, A. M., Faber, S. M., Ferguson, H. C., et al. 2011, ApJS, 197, 36, doi: 10.1088/0067-0049/197/2/36

    work page doi:10.1088/0067-0049/197/2/36 2011

  40. [40]

    G., Labb´ e, I., et al

    Kriek, M., van Dokkum, P. G., Labb´ e, I., et al. 2009, ApJ, 700, 221, doi: 10.1088/0004-637X/700/1/221

    work page doi:10.1088/0004-637x/700/1/221 2009

  41. [41]

    B., Tinsley, B

    Larson, R. B., Tinsley, B. M., & Caldwell, C. N. 1980, ApJ, 237, 692, doi: 10.1086/157917

    work page doi:10.1086/157917 1980

  42. [42]

    , keywords =

    Lidman, C., Suherli, J., Muzzin, A., et al. 2012, MNRAS, 427, 550, doi: 10.1111/j.1365-2966.2012.21984.x

    work page doi:10.1111/j.1365-2966.2012.21984.x 2012

  43. [43]

    A New Non-Parametric Approach to Galaxy Morphological Classification

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

    work page Pith review doi:10.1086/421849 2004

  44. [44]

    G., F¨ orster Schreiber, N

    Marchesini, D., van Dokkum, P. G., F¨ orster Schreiber, N. M., et al. 2009, ApJ, 701, 1765, doi: 10.1088/0004-637X/701/2/1765

    work page doi:10.1088/0004-637x/701/2/1765 2009

  45. [45]

    B., et al

    Matharu, J., Muzzin, A., Brammer, G. B., et al. 2019, MNRAS, 484, 595, doi: 10.1093/mnras/sty3465

    work page doi:10.1093/mnras/sty3465 2019

  46. [46]

    A., Holden, B

    Mei, S., Stanford, S. A., Holden, B. P., et al. 2012, ApJ, 754, 141, doi: 10.1088/0004-637X/754/2/141

    work page doi:10.1088/0004-637x/754/2/141 2012

  47. [47]

    and Amodeo, Stefania and Afanasiev, Anton V

    Mei, S., Hatch, N. A., Amodeo, S., et al. 2023, A&A, 670, A58, doi: 10.1051/0004-6361/202243551

    work page doi:10.1051/0004-6361/202243551 2023

  48. [48]

    C., & Hernquist, L

    Mihos, J. C., & Hernquist, L. 1994, ApJL, 431, L9, doi: 10.1086/187460

    work page doi:10.1086/187460 1994

  49. [49]

    and Brammer, Gabriel B

    Momcheva, I. G., Brammer, G. B., van Dokkum, P. G., et al. 2016, ApJS, 225, 27, doi: 10.3847/0067-0049/225/2/27

    work page doi:10.3847/0067-0049/225/2/27 2016

  50. [50]

    Nature , volume =

    Moore, B., Katz, N., Lake, G., Dressler, A., & Oemler, A. 1996, Nature, 379, 613, doi: 10.1038/379613a0

    work page doi:10.1038/379613a0 1996

  51. [51]

    2013, ApJ, 767, 39, doi: 10.1088/0004-637X/767/1/39

    Muzzin, A., Wilson, G., Demarco, R., et al. 2013, ApJ, 767, 39, doi: 10.1088/0004-637X/767/1/39

    work page doi:10.1088/0004-637x/767/1/39 2013

  52. [52]

    Muzzin, A., Wilson, G., Yee, H. K. C., et al. 2009, ApJ, 698, 1934, doi: 10.1088/0004-637X/698/2/1934 —. 2012, ApJ, 746, 188, doi: 10.1088/0004-637X/746/2/188

    work page doi:10.1088/0004-637x/698/2/1934 2009

  53. [53]

    2020, MNRAS, 499, 3061, doi: 10.1093/mnras/staa2872

    Nantais, J., Wilson, G., Muzzin, A., et al. 2020, MNRAS, 499, 3061, doi: 10.1093/mnras/staa2872

    work page doi:10.1093/mnras/staa2872 2020

  54. [54]

    B., van der Burg, R

    Nantais, J. B., van der Burg, R. F. J., Lidman, C., et al. 2016, A&A, 592, A161, doi: 10.1051/0004-6361/201628663 23

    work page doi:10.1051/0004-6361/201628663 2016

  55. [55]

    B., Muzzin, A., van der Burg, R

    Nantais, J. B., Muzzin, A., van der Burg, R. F. J., et al. 2017, MNRAS, 465, L104, doi: 10.1093/mnrasl/slw224

    work page doi:10.1093/mnrasl/slw224 2017

  56. [56]

    G., McDonald, M., Muzzin, A., et al

    Noble, A. G., McDonald, M., Muzzin, A., et al. 2017, ApJL, 842, L21, doi: 10.3847/2041-8213/aa77f3

    work page doi:10.3847/2041-8213/aa77f3 2017

  57. [57]

    G., Muzzin, A., McDonald, M., et al

    Noble, A. G., Muzzin, A., McDonald, M., et al. 2019, ApJ, 870, 56, doi: 10.3847/1538-4357/aaf1c6

    work page doi:10.3847/1538-4357/aaf1c6 2019

  58. [58]

    Y., Ho, L

    Peng, C. Y., Ho, L. C., Impey, C. D., & Rix, H.-W. 2002, AJ, 124, 266, doi: 10.1086/340952 —. 2010a, AJ, 139, 2097, doi: 10.1088/0004-6256/139/6/2097

    work page internal anchor Pith review doi:10.1086/340952 2002

  59. [59]

    J., Kovaˇ c, K., et al

    Peng, Y.-j., Lilly, S. J., Kovaˇ c, K., et al. 2010b, ApJ, 721, 193, doi: 10.1088/0004-637X/721/1/193 P´ erez-Mill´ an, D., Fritz, J., Gonz´ alez-L´ opezlira, R. A., et al. 2023, MNRAS, 521, 1292, doi: 10.1093/mnras/stad542

    work page doi:10.1088/0004-637x/721/1/193 2023

  60. [60]

    Postman, M., & Geller, M. J. 1984, ApJ, 281, 95, doi: 10.1086/162078

    work page doi:10.1086/162078 1984

  61. [61]

    Postman, M., Franx, M., Cross, N. J. G., et al. 2005, ApJ, 623, 721, doi: 10.1086/428881

    work page doi:10.1086/428881 2005

  62. [62]

    2020, ApJ, 899, 85, doi: 10.3847/1538-4357/aba42f

    Sazonova, E., Alatalo, K., Lotz, J., et al. 2020, ApJ, 899, 85, doi: 10.3847/1538-4357/aba42f

    work page doi:10.3847/1538-4357/aba42f 2020

  63. [63]

    Sersic, J. L. 1968, Atlas de Galaxias Australes

    1968

  64. [64]

    McConnachie, A. W. 2011, ApJS, 196, 11, doi: 10.1088/0067-0049/196/1/11

    work page doi:10.1088/0067-0049/196/1/11 2011

  65. [65]

    Skelton , author K

    Skelton, R. E., Whitaker, K. E., Momcheva, I. G., et al. 2014, ApJS, 214, 24, doi: 10.1088/0067-0049/214/2/24

    work page doi:10.1088/0067-0049/214/2/24 2014

  66. [66]

    2005, ApJ, 620, 78, doi: 10.1086/426930

    Dressler, A. 2005, ApJ, 620, 78, doi: 10.1086/426930

    work page doi:10.1086/426930 2005

  67. [67]

    , eprint =

    Strateva, I., Ivezi´ c,ˇZ., Knapp, G. R., et al. 2001, AJ, 122, 1861, doi: 10.1086/323301

    work page doi:10.1086/323301 2001

  68. [68]

    J., et al

    Strazzullo, V., Pannella, M., Mohr, J. J., et al. 2023, A&A, 669, A131, doi: 10.1051/0004-6361/202245268

    work page doi:10.1051/0004-6361/202245268 2023

  69. [69]

    2014, ApJ, 789, 164, doi: 10.1088/0004-637X/789/2/164

    Tal, T., Dekel, A., Oesch, P., et al. 2014, ApJ, 789, 164, doi: 10.1088/0004-637X/789/2/164

    work page doi:10.1088/0004-637x/789/2/164 2014

  70. [70]

    Tasca, L. A. M., Kneib, J. P., Iovino, A., et al. 2009, A&A, 503, 379, doi: 10.1051/0004-6361/200912213 van der Burg, R. F. J., Muzzin, A., Hoekstra, H., et al. 2013, A&A, 557, A15, doi: 10.1051/0004-6361/201321237 van der Wel, A. 2008, ApJL, 675, L13, doi: 10.1086/529432 van der Wel, A., Bell, E. F., H¨ aussler, B., et al. 2012, ApJS, 203, 24, doi: 10.10...

    work page doi:10.1051/0004-6361/200912213 2009

  71. [71]

    , keywords =

    Vulcani, B., Poggianti, B. M., Arag´ on-Salamanca, A., et al. 2011, MNRAS, 412, 246, doi: 10.1111/j.1365-2966.2010.17904.x

    work page doi:10.1111/j.1365-2966.2010.17904.x 2011

  72. [72]

    M., Gullieuszik, M., et al

    Vulcani, B., Poggianti, B. M., Gullieuszik, M., et al. 2023, ApJ, 949, 73, doi: 10.3847/1538-4357/acc5e2

    work page doi:10.3847/1538-4357/acc5e2 2023

  73. [73]

    J., Chen, S., et al

    Wang, H., Mo, H. J., Chen, S., et al. 2018, ApJ, 852, 31, doi: 10.3847/1538-4357/aa9e01

    work page doi:10.3847/1538-4357/aa9e01 2018

  74. [74]

    R., Tinker, J

    Wetzel, A. R., Tinker, J. L., Conroy, C., & van den Bosch, F. C. 2013, MNRAS, 432, 336, doi: 10.1093/mnras/stt469

    work page doi:10.1093/mnras/stt469 2013

  75. [75]

    C., & Gilmore, D

    Whitmore, B. C., & Gilmore, D. M. 1991, ApJ, 367, 64, doi: 10.1086/169602

    work page doi:10.1086/169602 1991

  76. [76]

    C., Gilmore, D

    Whitmore, B. C., Gilmore, D. M., & Jones, C. 1993, ApJ, 407, 489, doi: 10.1086/172531

    work page doi:10.1086/172531 1993

  77. [77]

    Wilson, G., Muzzin, A., Yee, H. K. C., et al. 2009, ApJ, 698, 1943, doi: 10.1088/0004-637X/698/2/1943

    work page doi:10.1088/0004-637x/698/2/1943 2009