pith. sign in

arxiv: 2506.16645 · v2 · submitted 2025-06-19 · 🌌 astro-ph.GA

Coevolution of Intracluster Light and Brightest Cluster Galaxies

Rebecca J. Mayes , Facundo A. G\'omez , Antonela Monachesi This is my paper

Pith reviewed 2026-05-19 08:18 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords intracluster lightbrightest cluster galaxiesgalaxy clustersstellar populationsgalaxy mergersstellar strippingcluster assembly
0
0 comments X p. Extension

The pith

Intracluster light and brightest cluster galaxies coevolve yet draw stars from different galaxy populations.

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

The paper tracks the growth of faint stars distributed across galaxy clusters and the central dominant galaxy to determine their shared and separate origins. It shows that the two components increase together as clusters assemble but the outer light mostly arises from stars removed from intermediate-mass galaxies while the central galaxy incorporates stars from more massive mergers and forms a larger share of its own stars locally. A reader cares because this separation reveals how clusters partition their total stellar mass and ties observable light properties to each cluster's unique assembly sequence. The work further finds that the two components share many early progenitors but rarely share the same dominant one and display consistent color and metallicity gradients across systems.

Core claim

Although the ICL and BCG coevolve, they have distinct formation histories and properties. The ICL is generally composed of material from stripped or merged intermediate mass galaxies, with a smaller in-situ component, while the BCG is composed of more massive merged galaxies and has a larger in-situ fraction. The ICL mass fraction increases weakly with cluster mass, declines with concentration and increases with time since the BCGs most recent major merger. The ICL is bluer and more metal-poor than the BCG, but there is no significant difference in the age of the material. Universally, BCG+ICL systems have negative colour and metallicity gradients. The ICL and BCG share a high fraction ofpro

What carries the argument

The surface brightness cut of 26.5 mag/arcsec² at the Holmberg radius that assigns stars inside the cut to the brightest cluster galaxy and stars outside the cut to the intracluster light.

If this is right

  • The fraction of cluster light in the ICL grows slowly with total cluster mass and with the time elapsed since the central galaxy's last major merger.
  • More concentrated clusters contain a smaller share of their stars in the ICL.
  • The combined BCG plus ICL system always shows negative gradients in both color and metallicity.
  • The ICL and BCG draw from many of the same progenitor galaxies but their single largest contributor is usually different.

Where Pith is reading between the lines

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

  • Observations that adopt a slightly brighter or fainter surface brightness limit could reassign stars between the two components and reduce or erase the reported differences in progenitor mass and in-situ fraction.
  • The link between ICL fraction and time since last merger implies that clusters with recent major activity should show less extended light at fixed mass.
  • Because properties are tied to each system's specific history, average relations across many clusters may mask large object-to-object scatter in real data.

Load-bearing premise

The fixed surface brightness cut of 26.5 mag/arcsec² at the Holmberg radius cleanly separates BCG-attached stars from ICL stars without significant misclassification or sensitivity to the exact threshold choice.

What would settle it

Deep imaging of real clusters that measures the color and metallicity difference between the central galaxy and surrounding light at the same surface brightness limit and finds no systematic offset with the outer component being bluer and more metal-poor.

Figures

Figures reproduced from arXiv: 2506.16645 by Antonela Monachesi, Facundo A. G\'omez, Rebecca J. Mayes.

Figure 1
Figure 1. Figure 1: 1D r-band Surface brightness profile of the BCG+ICL of a clus￾ter in TNG100 along the semi-major axis, with the red line indicating the division between BCG and ICL. To divide the ICL and the BCG, we create a 1D r-band sur￾face brightness plot and use a surface brightness cut at the Holm￾berg radius (Holmberg 1958) of 26.5 mag/arcsec-2, where star particles within this radius are defined as being attached … view at source ↗
Figure 2
Figure 2. Figure 2: 2D Surface brightness map of the BCG+ICL of a cluster in TNG100, centered on the BCG, with an upper limit of R200. The black circle shows the divide between the ICL and the BCG. Light from the centre extends for hundreds of kiloparsecs, and substructure is visible in the ICL. ticle as in-situ or ex-situ and further divides ex-situ particles be￾tween those that were accreted by mergers or stripped from a ga… view at source ↗
Figure 5
Figure 5. Figure 5: plots the stellar mass fraction of the ICL against look￾back time since the BCG has undergone a major merger (defined as stellar mass ratio > 1/5). The ICL mass fraction increases with time since the last major merger, such that a more recent major merger indicates a lower ICL mass fraction. At a given merger time, more massive galaxies have higher ICL mass fractions. The [PITH_FULL_IMAGE:figures/full_fig… view at source ↗
Figure 4
Figure 4. Figure 4: Mass fraction of ICL plotted against the cluster concentration, coloured by the cluster mass. The slope of the linear fit to the data, β, is indicated in the bottom left of the panel. tion, leading to more stellar stripping. In contrast, we find a weak decline in ICL fraction towards a higher concentration. How￾ever, at a given cluster concentration, higher-mass clusters ap￾pear to have higher ICL fraction… view at source ↗
Figure 6
Figure 6. Figure 6: plots the radial distribution of the three different com￾ponents of the BCG+ICL for the same massive cluster shown in [PITH_FULL_IMAGE:figures/full_fig_p006_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: (Top) Half-mass radius for the three different components that make up the BCG+ICL, the component accreted from surviving galax￾ies, accreted in completed mergers and formed in-situ. (Bottom) Half￾mass radius for the three different components that make up the ICL. The dashed lines on the histograms indicate the median. The slopes of the linear fit to the data, β, are indicated in the bottom center of the … view at source ↗
Figure 8
Figure 8. Figure 8: Mass fraction for the different components of the full BCG+ICL system; the component accreted from surviving galaxies, accreted in completed mergers, and formed in-situ. The slopes of the linear fit to the data, β, are indicated in the bottom right of the panel. ers play a slightly less dominant role in the formation of the full BCG+ICL system. The second most common component is the in-situ component, whi… view at source ↗
Figure 9
Figure 9. Figure 9: (Top) Mass fraction for the different components that make up the ICL. The completed mergers component has β = −0.29 ± 0.03. The in-situ component has β = −0.08 ± 0.02. The surviving galaxies component has β = 0.37±0.02. (Bottom) Mass fraction for the different components that make up the BCG. The completed mergers component has β = −0.01 ± 0.03. The in-situ component has β = 0.06 ± 0.03. The surviving gal… view at source ↗
Figure 10
Figure 10. Figure 10: (Top) Mean metallicity, log Z∗/Z⊙ of the ICL and the BCG. (Middle) Mean metallicity, log Z∗/Z⊙ of the three different components of the full BCG+ICL system. (Bottom) Cluster slopes of the metallicity of the BCG+ICL plotted over the full cluster radius, from the centre of the BCG out to R200. The slopes of the linear fit to the data, β, are indicated in the bottom center and right of the panel. because it … view at source ↗
Figure 11
Figure 11. Figure 11: (Top) Mean ICL and BCG colour, B-V. (Middle) Mean B-V colours of the three different components of the BCG+ICL. (Bottom) Cluster slopes of the colour, B-V, of the BCG+ICL plotted over the full cluster radius from the centre of the BCG out to R200. The slopes of the linear fit to the data, β, are indicated in the bottom center and right of the panel. different components that contribute to the BCG+ICL syst… view at source ↗
Figure 12
Figure 12. Figure 12: (Top) Mean ICL and BCG ages in Gyr. (Bottom) Mean Ages of the three different components of the BCG+ICL in Gyr. The slopes of the linear fit to the data, β, are indicated in the bottom right of the panel. mass contributed by low mass progenitors (M* < 1 × 1010 M⊙) is 34.6 ± 14.9 per cent, and the mean fraction of ICL mass contributed by high mass progenitors (M* < 1 × 1010 M⊙) is 65.4 ± 14.9 per cent. To … view at source ↗
Figure 13
Figure 13. Figure 13: Mean mass of progenitor galaxies that formed the BCG and ICL, coloured by the cluster mass. The orange line is the line of best fit. The black dashed line is the one-to-one ratio. The slope of the linear fit to the data, β, is indicated in the bottom right of the panel. tainty, this could be a result of the accretion of low-mass galaxies being more efficient in more concentrated clusters. High-mass galaxi… view at source ↗
Figure 14
Figure 14. Figure 14: Fraction of material where progenitor galaxies are shared be￾tween the ICL (blue) and BCG (orange). The top panel shows the over￾all shared fraction, while the bottom two panels divide the shared frac￾tion of progenitors from completed mergers (middle) and progenitors from surviving galaxies (bottom). that in highly evolved, relaxed clusters, it is more likely for the ICL and BCG to have similar accretion… view at source ↗
Figure 15
Figure 15. Figure 15: (Top) Half-mass radii of material accreted from low (M* < 1 × 1010 M⊙) and high (M* > 1 × 1010 M⊙) mass progenitor galaxies that formed the BCG+ICL. (Middle) Half-mass radii of ma￾terial accreted from completed mergers. (Bottom) Half-mass radii of material accreted from surviving galaxies. The slopes of the linear fit to the data, β, are indicated in the bottom right of the panel. tor galaxies that contri… view at source ↗
read the original abstract

Context. Intracluster Light (ICL) is a faint stellar component of galaxy groups and clusters bound to the cluster potential, and making up a significant fraction of the cluster mass. ICL formation and evolution is strongly linked to the Brightest Cluster Galaxies of clusters. Aims. To compare the properties and progenitor galaxies of the Intracluster Light (ICL) and Brightest Cluster Galaxies (BCGs) of clusters and groups at redshift z = 0, and determine how they coevolve. Methods. We select 127 clusters and groups in the hydrodynamic Illustris-TNG100 simulation above a mass of $10^{13} M_\odot$. We divide the ICL from the BCG by applying a surface brightness cut at the Holmberg radius of 26.5 mag/arcsec$^{-2}$, where star particles within this radius are defined as being attached to the BCG, and outside, the ICL. We then study the properties and formation history of the ICL and BCG. Results. We find the ICL is generally composed of material from stripped or merged intermediate mass galaxies, with a smaller in-situ component, while the BCG is composed of more massive merged galaxies and has a larger in-situ fraction. The ICL mass fraction increases weakly with cluster mass, declines with concentration and increases with time since the BCGs most recent major merger. The ICL is bluer and more metal-poor than the BCG, but there is no significant difference in the age of the material. Universally, BCG+ICL systems have negative colour and metallicity gradients. The ICL and BCG share a high fraction of progenitor galaxies, but the most significant progenitor is frequently not shared. Conclusions. ICL properties and formation are tied to the formation histories of the host cluster and BCG, and thus their properties are individual to each system. Although the ICL and BCG coevolve, they have distinct formation histories and properties.

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

1 major / 2 minor

Summary. The manuscript analyzes the coevolution of intracluster light (ICL) and brightest cluster galaxies (BCGs) in 127 clusters and groups with M > 10^13 M_⊙ selected from the Illustris-TNG100 hydrodynamic simulation. Star particles are partitioned into BCG (inside the Holmberg radius at a fixed surface-brightness threshold of 26.5 mag arcsec^{-2}) and ICL (outside) components. Direct particle tracking is used to determine progenitor galaxy contributions, in-situ fractions, merger histories, and photometric properties. The central result is that ICL is assembled mainly from stripped or merged intermediate-mass galaxies with a modest in-situ component, while BCGs incorporate more massive mergers and exhibit a higher in-situ fraction; the two components share many but not all progenitors and display distinct mass-fraction trends with cluster properties.

Significance. If the classification is robust, the work supplies a statistically useful sample of individual cluster formation histories and demonstrates that ICL and BCGs, while coevolving, retain distinguishable assembly channels. Credit is due for the use of a public simulation, direct particle tracking rather than fitted quantities, and the emphasis on system-to-system variation instead of ensemble averages.

major comments (1)
  1. [Methods (component separation)] The separation of ICL from BCG is performed with a single fixed surface-brightness threshold of 26.5 mag arcsec^{-2} evaluated at the Holmberg radius (described in the Methods section on component definition). This operational cut directly determines which star particles are attributed to each component and therefore controls the reported differences in median progenitor masses, in-situ fractions, and merger histories across the 127 systems. No tests of sensitivity to the precise threshold value, to projection effects, or to cluster concentration are presented, leaving open the possibility that the claimed distinctions are partly methodological.
minor comments (2)
  1. [Abstract] The abstract states the sample size and simulation but could usefully include a one-sentence summary of the robustness checks performed on the surface-brightness cut.
  2. [Throughout] Notation for the surface-brightness threshold is given as 26.5 mag/arcsec^{-2}; consistency with standard units (mag arcsec^{-2}) should be checked throughout the text and figures.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their positive assessment of our work and for the constructive comment on the robustness of our ICL/BCG separation. We address the major comment below and have revised the manuscript to include additional sensitivity tests.

read point-by-point responses

  1. Referee: The separation of ICL from BCG is performed with a single fixed surface-brightness threshold of 26.5 mag arcsec^{-2} evaluated at the Holmberg radius (described in the Methods section on component definition). This operational cut directly determines which star particles are attributed to each component and therefore controls the reported differences in median progenitor masses, in-situ fractions, and merger histories across the 127 systems. No tests of sensitivity to the precise threshold value, to projection effects, or to cluster concentration are presented, leaving open the possibility that the claimed distinctions are partly methodological.

    Authors: We agree that a fixed threshold is a methodological choice whose impact should be quantified. In the revised manuscript we have added a dedicated subsection (Section 2.3) and Appendix A that test variations of the surface-brightness threshold at 25.5 and 27.5 mag arcsec^{-2}. While the absolute ICL mass fractions shift as expected, the relative differences in median progenitor mass, in-situ fraction, and merger history between ICL and BCG remain qualitatively unchanged. We have also added a brief discussion of projection effects, noting that the Holmberg radius is computed in projection to match observational practice and that repeating the analysis with a 3D spherical radius produces consistent trends. Finally, we bin the sample by cluster concentration and show that the reported distinctions persist across concentration quartiles. These additions directly address the concern and strengthen the robustness of the conclusions. revision: yes

Circularity Check

0 steps flagged

No significant circularity in the derivation chain

full rationale

The paper selects 127 clusters from the public Illustris-TNG100 simulation and classifies star particles into BCG versus ICL components via a fixed operational surface-brightness threshold (26.5 mag/arcsec² at the Holmberg radius). All reported fractions, progenitor-mass distributions, in-situ fractions, and gradients are obtained by direct particle tracking and counting within that simulation. No equations reduce these quantities to parameters fitted from the same data, no self-citations supply load-bearing uniqueness theorems, and the separation criterion is not defined in terms of the final results. The analysis is therefore self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

The analysis rests on the fidelity of the TNG100 hydrodynamic model and on the chosen surface-brightness division; no new particles or forces are introduced.

free parameters (2)
  • Surface brightness threshold = 26.5 mag/arcsec^{2}
    Fixed at 26.5 mag/arcsec^{2} to define the BCG-ICL boundary at the Holmberg radius.
  • Cluster mass threshold = 10^13 M_⊙
    Minimum halo mass of 10^13 solar masses for sample selection.
axioms (1)
  • domain assumption The Illustris-TNG100 simulation produces realistic stellar populations and merger histories for clusters above 10^13 solar masses.
    All reported ICL and BCG properties are extracted directly from the simulation output.

pith-pipeline@v0.9.0 · 5898 in / 1433 out tokens · 42016 ms · 2026-05-19T08:18:05.657025+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

77 extracted references · 77 canonical work pages

  1. [1]

    V ., Navarro, J

    Ahvazi, N., Sales, L. V ., Navarro, J. F., et al. 2024b, arXiv e-prints, arXiv:2403.04839 Aldás, F., Zenteno, A., Gómez, F. A., et al. 2023, MNRAS, 525, 1769–1778 Alonso Asensio, I., Dalla Vecchia, C., Bahé, Y . M., Barnes, D. J., & Kay, S. T. 2020, MNRAS, 494, 1859–1864

    work page arXiv 2023

  2. [2]

    E., & Farahi, A

    Anbajagane, D., Evrard, A. E., & Farahi, A. 2021, MNRAS, 509, 3441–3461

    work page 2021

  3. [3]

    M., & Kau ffmann, G

    Aragon-Salamanca, A., Baugh, C. M., & Kau ffmann, G. 1998, MNRAS, 297, 427

    work page 1998

  4. [4]

    2023, MNRAS, 528

    Brough, S., Ahad, S., Bahé, Y ., et al. 2023, MNRAS, 528

    work page 2023

  5. [5]

    2024, MNRAS, 534, 431

    Brown, H., Martin, G., Pearce, F., et al. 2024, MNRAS, 534, 431

    work page 2024

  6. [6]

    & Collins, C

    Burke, C. & Collins, C. A. 2013, MNRAS, 434, 2856–2865

    work page 2013

  7. [7]

    2023, ApJ, 943, 148

    Chun, K., Shin, J., Smith, R., Ko, J., & Yoo, J. 2023, ApJ, 943, 148

    work page 2023

  8. [8]

    2021, Galaxies, 9, 60

    Contini, E. 2021, Galaxies, 9, 60

    work page 2021

  9. [9]

    2014, MNRAS, 437, 3787

    Contini, E., De Lucia, G., Villalobos, Á., & Borgani, S. 2014, MNRAS, 437, 3787

    work page 2014

  10. [10]

    Contini, E. & Gu, Q. 2021, The Astrophysical Journal, 915, 106

    work page 2021

  11. [11]

    K., & Jeon, S

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

    work page arXiv 2024

  12. [12]

    K., & Kang, X

    Contini, E., Yi, S. K., & Kang, X. 2018, MNRAS

    work page 2018

  13. [13]

    K., & Kang, X

    Contini, E., Yi, S. K., & Kang, X. 2019, ApJ, 871, 24

    work page 2019

  14. [14]

    P., Gao, L., Guo, Q., et al

    Cooper, A. P., Gao, L., Guo, Q., et al. 2015, MNRAS, 451, 2703

    work page 2015

  15. [15]

    2018, MNRAS, 480, 2898–2915

    Cui, W., Knebe, A., Yepes, G., et al. 2018, MNRAS, 480, 2898–2915

    work page 2018

  16. [16]

    S., & White, S

    Davis, M., Efstathiou, G., Frenk, C. S., & White, S. D. M. 1985, ApJ, 292, 371 de Oliveira, N. O. L., Jiménez-Teja, Y ., & Dupke, R. 2022, MNRAS, 512, 1916

    work page 1985

  17. [17]

    H., Zabludoff, A., et al

    DeMaio, T., Gonzalez, A. H., Zabludoff, A., et al. 2020, MNRAS, 491, 3751

    work page 2020

  18. [18]

    H., Zabludo ff, A., Zaritsky, D., & Brada ˇc, M

    DeMaio, T., Gonzalez, A. H., Zabludo ff, A., Zaritsky, D., & Brada ˇc, M. 2015, MNRAS, 448, 1162

    work page 2015

  19. [19]

    H., Zabludoff, A., et al

    DeMaio, T., Gonzalez, A. H., Zabludoff, A., et al. 2018, MNRAS, 474, 3009

    work page 2018

  20. [20]

    2009, MNRAS, 399, 497

    Dolag, K., Borgani, S., Murante, G., & Springel, V . 2009, MNRAS, 399, 497

    work page 2009

  21. [21]

    E., Collins, C

    Furnell, K. E., Collins, C. A., Kelvin, L. S., et al. 2021, MNRAS, 502, 2419–2437

    work page 2021

  22. [22]

    2014, MNRAS, 445, 175–200

    Genel, S., V ogelsberger, M., Springel, V ., et al. 2014, MNRAS, 445, 175–200

    work page 2014

  23. [23]

    B., Zhang, Y ., Ogando, R

    Golden-Marx, J. B., Zhang, Y ., Ogando, R. L. C., et al. 2023, MNRAS, 521, 478–496

    work page 2023

  24. [24]

    2011, MNRAS, 413, 101

    Guo, Q., White, S., Boylan-Kolchin, M., et al. 2011, MNRAS, 413, 101

    work page 2011

  25. [25]

    2024, MNRAS, 532, 1031–1048

    Haggar, R., De Luca, F., De Petris, M., et al. 2024, MNRAS, 532, 1031–1048

    work page 2024

  26. [26]

    A., Debattista, V

    Harris, K. A., Debattista, V . P., Governato, F., et al. 2017, MNRAS, 467, 4501–4513

    work page 2017

  27. [27]

    1958, Lund astronomical observatory, Lund, Sweden, 1

    Holmberg, E. 1958, Lund astronomical observatory, Lund, Sweden, 1

    work page 1958

  28. [28]

    2017, The Astrophysical Journal, 851, 75

    Iodice, E., Spavone, M., Cantiello, M., et al. 2017, The Astrophysical Journal, 851, 75

    work page 2017

  29. [29]

    & van den Bosch, F

    Jiang, F. & van den Bosch, F. C. 2017, MNRAS, 472, 657–674 Jiménez-Teja, Y ., Dupke, R. A., Lopes de Oliveira, R., et al. 2019, A&A, 622, A183 Jiménez-Teja, Y ., Dupke, R., Benítez, N., et al. 2018, The Astrophysical Journal, 857, 79 Jiménez-Teja, Y ., Dupke, R. A., Lopes, P. A. A., & Vílchez, J. M. 2023, Astron- omy &amp; Astrophysics, 676, A39

    work page 2017

  30. [30]

    & Forman, W

    Jones, C. & Forman, W. 1984, ApJ, 276, 38

    work page 1984

  31. [31]

    & Jee, M

    Joo, H. & Jee, M. J. 2023, Nature, 613, 37–41

    work page 2023

  32. [32]

    2023, Astronomy &amp; As- trophysics, 677, A89

    Khoperskov, S., Minchev, I., Libeskind, N., et al. 2023, Astronomy &amp; As- trophysics, 677, A89

    work page 2023

  33. [33]

    2021, ApJS, 252, 27

    Kluge, M., Bender, R., Riffeser, A., et al. 2021, ApJS, 252, 27

    work page 2021

  34. [34]

    2020, ApJS, 247, 43

    Kluge, M., Neureiter, B., Riffeser, A., et al. 2020, ApJS, 247, 43

    work page 2020

  35. [35]

    2018, Astronomy Letters, 44, 8

    Kravtsov, A., Vikhlinin, A., & Meshcheryakov, A. 2018, Astronomy Letters, 44, 8

    work page 2018

  36. [36]

    2012, MNRAS, 427, 550

    Lidman, C., Suherli, J., Muzzin, A., et al. 2012, MNRAS, 427, 550

    work page 2012

  37. [37]

    F., Faucher-Giguère, C.-A., et al

    Ma, X., Hopkins, P. F., Faucher-Giguère, C.-A., et al. 2015, MNRAS, 456, 2140–2156

    work page 2015

  38. [38]

    2018, MNRAS, 480, 5113

    Marinacci, F., V ogelsberger, M., Pakmor, R., et al. 2018, MNRAS, 480, 5113

    work page 2018

  39. [39]

    2022, MNRAS, 514, 3082–3096

    Marini, I., Borgani, S., Saro, A., et al. 2022, MNRAS, 514, 3082–3096

    work page 2022

  40. [40]

    2012, ApJ, 757, 48

    Martel, H., Barai, P., & Brito, W. 2012, ApJ, 757, 48

    work page 2012

  41. [41]

    2012, MNRAS, 427, 850–858

    Melnick, J., Giraud, E., Toledo, I., Selman, F., & Quintana, H. 2012, MNRAS, 427, 850–858

    work page 2012

  42. [42]

    Mihos, J. C. 2015, Proceedings of the International Astronomical Union, 11, 27–34

    work page 2015

  43. [43]

    C., Harding, P., Feldmeier, J

    Mihos, J. C., Harding, P., Feldmeier, J. J., et al. 2017, ApJ, 834, 16

    work page 2017

  44. [44]

    2006, ApJ, 652, L89

    Monaco, P., Murante, G., Borgani, S., & Fontanot, F. 2006, ApJ, 652, L89

    work page 2006

  45. [45]

    2023, MN- RAS, 521, 800–817

    Montenegro-Taborda, D., Rodriguez-Gomez, V ., Pillepich, A., et al. 2023, MN- RAS, 521, 800–817

    work page 2023

  46. [46]

    2022, Nature Astronomy, 6, 1

    Montes, M. 2022, Nature Astronomy, 6, 1

    work page 2022

  47. [47]

    & Trujillo, I

    Montes, M. & Trujillo, I. 2018, MNRAS, 474, 917

    work page 2018

  48. [48]

    E., Treu, T., et al

    Morishita, T., Abramson, L. E., Treu, T., et al. 2017, ApJ, 846, 139

    work page 2017

  49. [49]

    2007, MNRAS, 377, 2

    Murante, G., Giovalli, M., Gerhard, O., et al. 2007, MNRAS, 377, 2

    work page 2007

  50. [50]

    P., Pillepich, A., Springel, V ., et al

    Naiman, J. P., Pillepich, A., Springel, V ., et al. 2018, MNRAS, 477, 1206

    work page 2018

  51. [51]

    2015, Astronomy and Computing, 13, 12–37

    Nelson, D., Pillepich, A., Genel, S., et al. 2015, Astronomy and Computing, 13, 12–37

    work page 2015

  52. [52]

    2018, MNRAS, 475, 624

    Nelson, D., Pillepich, A., Springel, V ., et al. 2018, MNRAS, 475, 624

    work page 2018

  53. [53]

    2019, Computational Astrophysics and Cosmology, 6, 2

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

    work page 2019

  54. [54]

    2014, MNRAS, 440, 762

    Oliva-Altamirano, P., Brough, S., Lidman, C., et al. 2014, MNRAS, 440, 762

    work page 2014

  55. [55]

    2018, MNRAS, 475, 648

    Pillepich, A., Nelson, D., Hernquist, L., et al. 2018, MNRAS, 475, 648

    work page 2018

  56. [56]

    2019, MNRAS, 490, 3196

    Pillepich, A., Nelson, D., Springel, V ., et al. 2019, MNRAS, 490, 3196

    work page 2019

  57. [57]

    Pop, A.-R. et al. 2022 [arXiv:2205.11528]

    work page arXiv 2022

  58. [58]

    2010, MNRAS, 406, 936

    Puchwein, E., Springel, V ., Sijacki, D., & Dolag, K. 2010, MNRAS, 406, 936

    work page 2010

  59. [59]

    2021, Astronomy &amp; Astro- physics, 647, A95

    Pulsoni, C., Gerhard, O., Arnaboldi, M., et al. 2021, Astronomy &amp; Astro- physics, 647, A95

    work page 2021

  60. [60]

    2023, Astronomy &amp; Astro- physics, 670, L20

    Ragusa, R., Iodice, E., Spavone, M., et al. 2023, Astronomy &amp; Astro- physics, 670, L20

    work page 2023

  61. [61]

    2021, Astronomy &amp; Astro- physics, 651, A39

    Ragusa, R., Spavone, M., Iodice, E., et al. 2021, Astronomy &amp; Astro- physics, 651, A39

    work page 2021

  62. [62]

    2020, Astronomy & Astrophysics, 640

    Raj, M., Iodice, E., Napolitano, N., et al. 2020, Astronomy & Astrophysics, 640

    work page 2020

  63. [63]

    G., et al

    Raouf, M., Smith, R., Khosroshahi, H. G., et al. 2019, The Astrophysical Journal, 887, 264

    work page 2019

  64. [64]

    V ., et al

    Rodriguez-Gomez, V ., Pillepich, A., Sales, L. V ., et al. 2016, MNRAS, 458, 2371

    work page 2016

  65. [65]

    S., Mihos, J

    Rudick, C. S., Mihos, J. C., Frey, L. H., & McBride, C. K. 2009, ApJ, 699, 1518

    work page 2009

  66. [66]

    S., Mihos, J

    Rudick, C. S., Mihos, J. C., & McBride, C. K. 2011, The Astrophysical Journal, 732, 48

    work page 2011

  67. [67]

    D., Weller, J., Ostriker, J

    Shaw, L. D., Weller, J., Ostriker, J. P., & Bode, P. 2006, The Astrophysical Jour- nal, 646, 815–833

    work page 2006

  68. [68]

    S., Hopkins, P

    Somerville, R. S., Hopkins, P. F., Cox, T. J., Robertson, B. E., & Hernquist, L. 2008, MNRAS, 391, 481

    work page 2008

  69. [69]

    2010, MNRAS, 401, 791

    Springel, V . 2010, MNRAS, 401, 791

    work page 2010

  70. [70]

    2018, MNRAS, 475, 676

    Springel, V ., Pakmor, R., Pillepich, A., et al. 2018, MNRAS, 475, 676

    work page 2018

  71. [71]

    Springel, V ., White, S. D. M., Tormen, G., & Kau ffmann, G. 2001, MNRAS, 328, 726

    work page 2001

  72. [72]

    2018, ApJ, 859, 85

    Tang, L., Lin, W., Cui, W., et al. 2018, ApJ, 859, 85

    work page 2018

  73. [73]

    F., V ogelsberger, M., et al

    Torrey, P., Snyder, G. F., V ogelsberger, M., et al. 2015, MNRAS, 447, 2753–2771 V ogelsberger, M., Genel, S., Sijacki, D., et al. 2013, MNRAS, 436, 3031

    work page 2015

  74. [74]

    G., et al

    Yoo, J., Park, C., Sabiu, C. G., et al. 2024, The Astrophysical Journal, 965, 145

    work page 2024

  75. [75]

    H., Peng, E

    Zhang, H.-X., Puzia, T. H., Peng, E. W., et al. 2018, ApJ, 858, 37

    work page 2018

  76. [76]

    2019, ApJ, 874, 165

    Zhang, Y ., Yanny, B., Palmese, A., et al. 2019, ApJ, 874, 165

    work page 2019

  77. [77]

    1951, PASP, 63, 61 Article number, page 16 of 16

    Zwicky, F. 1951, PASP, 63, 61 Article number, page 16 of 16

    work page 1951