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arxiv: 2511.20806 · v2 · pith:ZMCROMAEnew · submitted 2025-11-25 · 🌌 astro-ph.GA

Age and metallicity of low-mass galaxies: from their centres to their stellar halos

Pith reviewed 2026-05-17 04:34 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords low-mass galaxiesstellar halosmetallicity gradientsage profilesaccretion historymass-metallicity relationdwarf galaxies
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The pith

The timing of a dominant satellite's infall explains the scatter in metallicity of stellar halos around low-mass galaxies.

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

This paper examines how metallicity and age change from the centers of low-mass galaxies out to their stellar halos using a set of simulated systems. It reports negative metallicity gradients in every galaxy and shows that the scatter in the halo mass-metallicity relation is accounted for by when the galaxy's largest satellite fell in. Galaxies that accreted that satellite later end up with more metal-rich halos at the same accreted mass. The work also finds that radial age profiles frequently display a U shape produced by in-situ stars and by the redistribution of material during mergers. More massive halos tend to be older than less massive ones.

Core claim

The dispersion in the mass-metallicity relation of stellar halos in low-mass galaxies arises from the infall time of each galaxy's most dominant satellite: at fixed accreted halo mass, later-infall satellites produce more metal-rich stellar halos.

What carries the argument

The link between accreted stellar halo mass, the infall time of the dominant satellite, and the resulting average metallicity of the halo material.

If this is right

  • At the same accreted mass, halos assembled from later-accreted satellites are more metal-rich than those assembled from earlier-accreted satellites.
  • Radial age profiles in roughly two-thirds of the systems show a U shape whose inner and outer segments are set by in-situ star formation and by merger-driven redistribution of stars.
  • More massive stellar halos are older on average than less massive ones.
  • Metallicity gradients measured in dex per half-mass radius show no simple scaling with galaxy mass or accreted mass.

Where Pith is reading between the lines

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

  • If the timing-metallicity link holds in observations, halo metallicity could serve as an indirect clock for the last major accretion event in dwarfs too faint for direct satellite detection.
  • The lack of a universal gradient slope suggests that individual merger sequences, rather than global mass alone, set the final chemical profile in the low-mass regime.
  • Extending the same analysis to a wider mass range would test whether the same infall-time dependence persists or breaks down above 10^10 solar masses.

Load-bearing premise

The simulated formation histories and definitions of accreted versus in-situ stars match those of real low-mass galaxies.

What would settle it

A sample of observed low-mass galaxies with measured stellar halo metallicities and independent estimates of dominant-satellite infall times showing no relation between later infall and higher halo metallicity at fixed mass.

Figures

Figures reproduced from arXiv: 2511.20806 by Antonela Monachesi, Elisa A. Tau, Facundo A. G\'omez, Federico Marinacci, Freeke van de Voort, Rebekka Bieri, Robert J. J. Grand, R\"udiger Pakmor.

Figure 2
Figure 2. Figure 2: Metallicity gradients of the galaxies of our sample computed when considering the metallicity profile of the galaxy within 4 Rh (blue), and the metallicity profile of the total stellar halo (pink) and the accreted stellar halo (green). by the number of particles made to these profiles. The values of the metallicity gradients of the galaxies in our sample range from −0.18 dex (Auriga 5) to −0.07 dex (Auriga… view at source ↗
Figure 1
Figure 1. Figure 1: Total median [Fe/H] (black dotted line) and accreted median [Fe/H] (pink dash-dotted line) profiles of the galaxies in our sample. In￾dividual [Fe/H] profiles for 6 galaxies of our sample are also shown, nor￾malised by their respective Rh and colour-coded by their stellar masses. In [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 3
Figure 3. Figure 3: Left panel: Metallicity gradient of the galaxies of our sample computed within 4 Rh (empty circles) and 10 Rh (filled circles), as a function of their stellar mass. Right panel: Metallicity gradients of the total stellar halo and the accreted stellar halo as a function of the galaxies’ stellar mass, represented with filled circles and empty triangles respectively. The arrow represents the value correspondi… view at source ↗
Figure 4
Figure 4. Figure 4: Median [Fe/H] of the accreted stellar halo of the galaxies as a function of their most dominant satellite’s infall time, colour-coded by these satellites’ stellar mass. 3.2. The metallicity of the accreted stellar halo We now explore the correlation between the most dominant con￾tributor’s infall time and the median metallicity of the stellar halo. This allows us to explore whether the infall time of these… view at source ↗
Figure 5
Figure 5. Figure 5: Left panel: median [Fe/H] of the stellar halos of the galaxies as a function of their masses. Right panel: median [Fe/H] of the accreted stellar halos of the galaxies as a function of their masses. Both panels are colour-coded by the mean infall look-back time of the significant progenitors of the stellar halos. We note a correlation between the metallicity of the accreted stellar halo and the infall time … view at source ↗
Figure 6
Figure 6. Figure 6: Total mean age profile (black dotted line) and accreted mean age profile (pink dash-dotted line) of all of the galaxies of our sample. Individual age profiles for 6 galaxies of our sample are also shown, nor￾malised by their respective Rh and colour-coded by the galaxies’ stellar masses. We note a prominent U-shape in the total mean of the age pro￾file of our galaxies, driven by the in situ stellar populat… view at source ↗
Figure 7
Figure 7. Figure 7: Left panel: Mean age of the total stellar halo as a function of the total stellar halo mass. Right panel: Mean age of the accreted stellar halo as a function of its mass. Both panels are colour-coded by the total stellar mass of the galaxies. We note a correlation in both panels, although they are inverted: more massive stellar halos are older than less massive ones, while more massive accreted stellar hal… view at source ↗
Figure 8
Figure 8. Figure 8: Age-metallicity relation of the galaxies in our sample, colour-coded by their accreted stellar mass. Left panel: Median [Fe/H] of the total stellar halo (in situ + accreted) as a function of its mean age. Right panel: Median [Fe/H] of the accreted stellar halo as a function of its mean age. We note a strong correlation between the median [Fe/H] and the mean age of the accreted stellar halo, such that the m… view at source ↗
Figure 9
Figure 9. Figure 9: Mean of the SFR/M∗(r) profile (black dotted line) of all the galaxies in our sample. The individual SFR/M∗(r) profiles the subsam￾ple of 6 galaxies are also shown, colour-coded by their stellar mass. The vertical dashed lines represent the radius at which the minimum age of the U-shaped age profiles in [PITH_FULL_IMAGE:figures/full_fig_p009_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: sSFR of the in situ stellar populations at different radial ranges, as a function of the age of the particles. The arrows represent the merger events that satisfy that the total peak mass of the satellite galaxy was at least 1 10 M200, considering the M200 of the host galaxy at the time at which the satellite crossed its R200 for the first time. They are colour-coded by the ratio between the Mpeak sat and… view at source ↗
read the original abstract

We aim to analyse the metallicity and the ages of the stellar halos of low-mass galaxies to better understand their formation history. We use 17 simulated low-mass galaxies from the Auriga Project ($\sim 3 \times 10^8 \, M_\odot \leq M_* \lesssim 2 \times 10^{10} \, M_\odot$). We study the metallicity and the ages of these galaxies and their stellar halos, as well as the relation between these two properties. We find that all galaxies have negative radial [Fe/H] gradients, and that the centres of less massive dwarfs are generally more metal poor than those of more massive dwarfs. We find no correlation between the metallicity gradients in dex/R$_h$ and intrinsic galaxy properties, such as stellar mass or accreted stellar mass, suggesting that these gradients are not a simple byproduct of galaxy evolution in the low-mass regime. We also find that the dispersion in the mass-metallicity relation found in the stellar halos of low-mass galaxies can be explained with the infall time of their most dominant satellite: at a fixed accreted stellar halo mass, dwarf galaxies that accreted this satellite at later times have more metal-rich accreted stellar halos. Regarding the ages of the analysed galaxies, we find a prominent U shape in the radial mean age profiles of $\sim 65\%$ of them, which is mainly driven by the in situ stellar material. This presence of a U shape in the age profiles is due to the combination of the cessation of recent star formation at large radial distances and the merger events these galaxies undergo, which redistribute the stellar material to their outer regions. When focusing on the ages of the stellar halos, we find that more massive ones are older than less massive ones. Our results show a wide variety in ages and metallicities of low-mass galaxies and their stellar halos, reflecting the complex and non-uniform evolutionary pathways these systems can follow.

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 analyzes metallicity and age properties of 17 low-mass galaxies (stellar masses ~3e8 to 2e10 solar masses) and their stellar halos drawn from the Auriga Project simulations. It reports negative radial [Fe/H] gradients in all systems with no correlation to galaxy properties such as stellar or accreted mass; attributes scatter in the halo mass-metallicity relation to the infall time of the most dominant satellite (later infall yielding more metal-rich halos at fixed accreted mass); identifies U-shaped radial age profiles in ~65% of galaxies driven primarily by in-situ stars due to cessation of outer star formation and merger redistribution; and finds more massive halos to be older overall.

Significance. If the empirical relations hold under scrutiny, the work would add to understanding of low-mass galaxy assembly by connecting halo metallicity dispersion directly to a single merger event's timing and by documenting the prevalence of U-shaped age profiles. The simulation framework permits clean separation of in-situ versus accreted material, which is a strength for tracing formation pathways that observations alone cannot easily resolve.

major comments (2)
  1. [Abstract / Results on stellar halo metallicity] The central result on halo metallicity dispersion (abstract) is based on a sample of only 17 galaxies. The claim that infall time of the most dominant satellite explains the scatter at fixed accreted stellar halo mass requires explicit quantification of the correlation strength (e.g., Spearman coefficient or regression slope with uncertainties) plus robustness tests against sample definition, outlier removal, or alternative dominance criteria; with N=17 the statistical leverage is modest and the attribution could be sensitive to these choices.
  2. [Methods (sample and halo definitions)] The identification of the 'most dominant satellite', the precise definition of its infall time from the merger tree, and the tagging of accreted versus in-situ stars are load-bearing for the main claim yet receive no methodological detail in the abstract or summary. Without these, it is impossible to assess whether satellite mass at infall, orbital parameters, or secondary mergers could confound the reported trend.
minor comments (2)
  1. [Abstract] The ~65% fraction of galaxies showing U-shaped age profiles should be stated as an exact count (e.g., 11/17) together with the quantitative criterion used to identify the U-shape.
  2. [Abstract / Results on metallicity gradients] Clarify whether the reported negative [Fe/H] gradients are measured in dex per R_h or in physical units, and confirm that the lack of correlation with galaxy properties is shown in a dedicated figure or table.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed report. We address each major comment below and have revised the manuscript to incorporate additional quantitative measures and methodological clarifications where appropriate.

read point-by-point responses
  1. Referee: The central result on halo metallicity dispersion (abstract) is based on a sample of only 17 galaxies. The claim that infall time of the most dominant satellite explains the scatter at fixed accreted stellar halo mass requires explicit quantification of the correlation strength (e.g., Spearman coefficient or regression slope with uncertainties) plus robustness tests against sample definition, outlier removal, or alternative dominance criteria; with N=17 the statistical leverage is modest and the attribution could be sensitive to these choices.

    Authors: We acknowledge the modest sample size, which is a limitation of the high-resolution Auriga suite for low-mass galaxies. In the revised manuscript we will explicitly report the Spearman rank correlation coefficient (with p-value) between halo [Fe/H] and dominant-satellite infall time at fixed accreted mass. We will also add robustness tests that include outlier removal and an alternative dominance definition based on satellite mass at infall. While N=17 inherently limits statistical power, the trend remains visible across the sample and aligns with the physical expectation that later-accreted satellites retain higher metallicity. revision: yes

  2. Referee: The identification of the 'most dominant satellite', the precise definition of its infall time from the merger tree, and the tagging of accreted versus in-situ stars are load-bearing for the main claim yet receive no methodological detail in the abstract or summary. Without these, it is impossible to assess whether satellite mass at infall, orbital parameters, or secondary mergers could confound the reported trend.

    Authors: The full definitions are provided in Section 2 of the manuscript: the dominant satellite is the merger contributing the largest fraction of accreted stellar mass; infall time is the first snapshot in which the satellite crosses the main halo's virial radius; accreted stars are tagged as those formed outside the main progenitor. To improve accessibility we will add a concise summary of these procedures to the abstract and methods overview. We have additionally verified that the dominant satellite accounts for the majority of accreted mass in each system and that including secondary mergers does not remove the reported trend. revision: yes

Circularity Check

0 steps flagged

No circularity: empirical correlations extracted directly from Auriga simulation outputs

full rationale

The paper analyzes 17 Auriga Project galaxies to report observed trends such as negative radial [Fe/H] gradients, U-shaped age profiles driven by in-situ material, and the dispersion in accreted stellar halo mass-metallicity relation being linked to dominant satellite infall time at fixed mass. These are direct measurements and correlations from the simulation data (stellar tagging, merger trees, radial profiles), not quantities obtained by fitting parameters to a subset and relabeling the fit as a prediction, nor by self-definitional loops or load-bearing self-citations that reduce the central claim to its own inputs. The derivation chain consists of post-processing simulation outputs against external benchmarks (observed gradients, mass-metallicity scatter), rendering the results self-contained without reduction to fitted inputs or ansatzes imported via citation.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The analysis rests on the fidelity of the Auriga hydrodynamical simulations and on standard definitions of stellar halo boundaries and in-situ versus accreted stars. No new free parameters or invented entities are introduced in the reported results.

axioms (2)
  • domain assumption Auriga simulations accurately capture the chemical enrichment and dynamical evolution of low-mass galaxies
    All reported gradients, U-shapes, and infall-time correlations are extracted from these simulations.
  • domain assumption Stellar halos can be cleanly separated from the main galaxy body using standard radial and kinematic criteria
    The mass-metallicity and age results for halos depend on this separation.

pith-pipeline@v0.9.0 · 5701 in / 1443 out tokens · 39482 ms · 2026-05-17T04:34:29.951801+00:00 · methodology

discussion (0)

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Works this paper leans on

82 extracted references · 82 canonical work pages

  1. [1]

    2001, AJ, 122, 2524

    Aparicio, A., Carrera, R., & Martínez-Delgado, D. 2001, AJ, 122, 2524

  2. [2]

    L., van Zee, L., Dale, D

    Barnes, K. L., van Zee, L., Dale, D. A., et al. 2014, ApJ, 789, 126

  3. [3]

    2011, MNRAS, 411, 1013

    Battaglia, G., Tolstoy, E., Helmi, A., et al. 2011, MNRAS, 411, 1013

  4. [4]

    2006, A&A, 459, 423

    Battaglia, G., Tolstoy, E., Helmi, A., et al. 2006, A&A, 459, 423

  5. [5]

    W., Koposov, S

    Belokurov, V ., Erkal, D., Evans, N. W., Koposov, S. E., & Deason, A. J. 2018, MNRAS, 478, 611 Benítez-Llambay, A., Navarro, J. F., Abadi, M. G., et al. 2016, MNRAS, 456, 1185

  6. [6]

    L., Cassisi, S., et al

    Bettinelli, M., Hidalgo, S. L., Cassisi, S., et al. 2019, MNRAS, 487, 5862

  7. [7]

    M., Beaton, R., Chiba, M., et al

    Brown, T. M., Beaton, R., Chiba, M., et al. 2008, ApJ, 685, L121 Cano-Díaz, M., Rodríguez-Puebla, A., Robleto-Orús, A. C., et al. 2025, AJ, 170, 27

  8. [8]

    2001, ApJ, 554, 1044

    Chiappini, C., Matteucci, F., & Romano, D. 2001, ApJ, 554, 1044

  9. [9]

    P., Zaritsky, D., et al

    Conroy, C., Naidu, R. P., Zaritsky, D., et al. 2019, ApJ, 887, 237

  10. [10]

    P., Cole, S., Frenk, C

    Cooper, A. P., Cole, S., Frenk, C. S., et al. 2010, MNRAS, 406, 744

  11. [11]

    2025, A&A, 700, A57

    Corbelli, E., Elmegreen, B., Ellison, S., & Bianchi, S. 2025, A&A, 700, A57

  12. [12]

    A., Cohen, S

    Dale, D. A., Cohen, S. A., Johnson, L. C., et al. 2009, ApJ, 703, 517

  13. [13]

    2020, MNRAS, 493, 5195

    Das, P., Hawkins, K., & Jofré, P. 2020, MNRAS, 493, 5195

  14. [14]

    P., Roškar, R., & Loebman, S

    Debattista, V . P., Roškar, R., & Loebman, S. R. 2017, in Astrophysics and Space Science Library, V ol. 434, Outskirts of Galaxies, ed. J. H. Knapen, J. C. Lee, & A. Gil de Paz, 77 del Pino, A., Aparicio, A., & Hidalgo, S. L. 2015, MNRAS, 454, 3996 D’Souza, R. & Bell, E. F. 2018, Nature Astronomy, 2, 737

  15. [15]

    2016, ApJ, 820, 131 Ferré-Mateu, A., Durré, M., Forbes, D

    El-Badry, K., Wetzel, A., Geha, M., et al. 2016, ApJ, 820, 131 Ferré-Mateu, A., Durré, M., Forbes, D. A., et al. 2021, MNRAS, 503, 5455

  16. [16]

    D., et al

    Fitts, A., Boylan-Kolchin, M., Elbert, O. D., et al. 2017, MNRAS, 471, 3547

  17. [17]

    S., Johnston, K

    Font, A. S., Johnston, K. V ., Bullock, J. S., & Robertson, B. E. 2006, ApJ, 646, 886

  18. [18]

    Fragkoudi, F., Grand, R. J. J., Pakmor, R., et al. 2025, MNRAS, 538, 1587

  19. [19]

    B., Meschin, I

    Gallart, C., Stetson, P. B., Meschin, I. P., Pont, F., & Hardy, E. 2008, ApJ, 682, L89

  20. [20]

    D., Monachesi, A., Gómez, F

    Gargiulo, I. D., Monachesi, A., Gómez, F. A., et al. 2019, MNRAS, 489, 5742

  21. [21]

    M., Kalirai, J

    Gilbert, K. M., Kalirai, J. S., Guhathakurta, P., et al. 2014, ApJ, 796, 76 González Delgado, R. M., García-Benito, R., Pérez, E., et al. 2015, A&A, 581, A103

  22. [22]

    B., Monachesi, A., et al

    Gonzalez-Jara, J., Tissera, P. B., Monachesi, A., et al. 2025, A&A, 693, A282

  23. [23]

    Grand, R. J. J., Fragkoudi, F., Gómez, F. A., et al. 2024, MNRAS, 532, 1814

  24. [24]

    Grand, R. J. J., Gómez, F. A., Marinacci, F., et al. 2017, MNRAS, 467, 179

  25. [25]

    Grand, R. J. J., Springel, V ., Gómez, F. A., et al. 2016, MNRAS, 459, 199

  26. [26]

    S., Bullock, J

    Graus, A. S., Bullock, J. S., Fitts, A., et al. 2019, MNRAS, 490, 1186

  27. [27]

    F., et al

    Harmsen, B., Monachesi, A., Bell, E. F., et al. 2017, MNRAS, 466, 1491

  28. [28]

    2008, A&A Rev., 15, 145

    Helmi, A. 2008, A&A Rev., 15, 145

  29. [29]

    2020, ARA&A, 58, 205

    Helmi, A. 2020, ARA&A, 58, 205

  30. [30]

    R., Sestito, F., et al

    Jensen, J., Hayes, C. R., Sestito, F., et al. 2024, MNRAS, 527, 4209 Jofré, P. & Weiss, A. 2011, A&A, 533, A59

  31. [31]

    2023, A&A, 679, A83

    Kang, X., Kudritzki, R.-P., & Zhang, F. 2023, A&A, 679, A83

  32. [32]

    Kepner, J. V . 1999, ApJ, 520, 59

  33. [33]

    N., Cohen, J

    Kirby, E. N., Cohen, J. G., Guhathakurta, P., et al. 2013, ApJ, 779, 102

  34. [34]

    A., Bresolin, F., Hosek, Jr., M

    Kudritzki, R.-P., Urbaneja, M. A., Bresolin, F., Hosek, Jr., M. W., & Przybilla, N. 2014, ApJ, 788, 56

  35. [35]

    A., Gazak, Z., et al

    Kudritzki, R.-P., Urbaneja, M. A., Gazak, Z., et al. 2012, ApJ, 747, 15

  36. [36]

    2025, AJ, 170, 173

    Kunder, A., Prudil, Z., Monachesi, A., et al. 2025, AJ, 170, 173

  37. [37]

    Larson, R. B. 1976, MNRAS, 176, 31

  38. [38]

    A., Brooks, A

    Leaman, R., Venn, K. A., Brooks, A. M., et al. 2013, ApJ, 767, 131

  39. [39]

    & Cooper, A

    Liao, L.-W. & Cooper, A. P. 2023, MNRAS, 518, 3999

  40. [40]

    2023, MNRAS, 525, 3086 López, P

    Longeard, N., Jablonka, P., Battaglia, G., et al. 2023, MNRAS, 525, 3086 López, P. D., Fragkoudi, F., Cora, S. A., et al. 2025, MNRAS, 540, 2031 Martínez-Vázquez, C. E., Monelli, M., Cassisi, S., et al. 2021, MNRAS, 508, 1064

  41. [41]

    2003, The Chemical Evolution of the Galaxy, V ol

    Matteucci, F. 2003, The Chemical Evolution of the Galaxy, V ol. 253

  42. [42]

    2006, MNRAS, 369, 1021

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

  43. [43]

    2014, MNRAS, 438, 1067

    Meschin, I., Gallart, C., Aparicio, A., et al. 2014, MNRAS, 438, 1067

  44. [44]

    A., Grand, R

    Monachesi, A., Gómez, F. A., Grand, R. J. J., et al. 2019, MNRAS, 485, 2589

  45. [45]

    C., Lauer, T

    Monachesi, A., Trager, S. C., Lauer, T. R., et al. 2012, ApJ, 745, 97

  46. [46]

    M., Pizzella, A., et al

    Morelli, L., Corsini, E. M., Pizzella, A., et al. 2015, MNRAS, 452, 1128

  47. [47]

    2018, MNRAS, 480, 4455 Muñoz, C., Monachesi, A., Nidever, D

    Mostoghiu, R., Di Cintio, A., Knebe, A., et al. 2018, MNRAS, 480, 4455 Muñoz, C., Monachesi, A., Nidever, D. L., et al. 2023, A&A, 680, A79

  48. [48]

    F., Frenk, C

    Navarro, J. F., Frenk, C. S., & White, S. D. M. 1997, ApJ, 490, 493 Oñorbe, J., Boylan-Kolchin, M., Bullock, J. S., et al. 2015, MNRAS, 454, 2092

  49. [49]

    2022, MNRAS, 516, 197

    Ortega-Martinez, S., Obreja, A., Dominguez-Tenreiro, R., et al. 2022, MNRAS, 516, 197

  50. [50]

    2014, ApJ, 783, L20

    Pakmor, R., Marinacci, F., & Springel, V . 2014, ApJ, 783, L20

  51. [51]

    2023, A&A, 673, A147

    Pessa, I., Schinnerer, E., Sanchez-Blazquez, P., et al. 2023, A&A, 673, A147

  52. [52]

    2020, MNRAS, 495, 3387

    Peterken, T., Merrifield, M., Aragón-Salamanca, A., et al. 2020, MNRAS, 495, 3387

  53. [53]

    Pinna, F., Walo-Martín, D., Grand, R. J. J., et al. 2024, A&A, 683, A236 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2014, A&A, 571, A16

  54. [54]

    L., Brooks, A

    Riggs, C. L., Brooks, A. M., Munshi, F., et al. 2024, ApJ, 977, 20 Roškar, R., Debattista, V . P., Quinn, T. R., Stinson, G. S., & Wadsley, J. 2008a, ApJ, 684, L79 Roškar, R., Debattista, V . P., Stinson, G. S., et al. 2008b, ApJ, 675, L65

  55. [55]

    2019, ApJ, 878, 1 Sánchez-Blázquez, P., Courty, S., Gibson, B

    Sacchi, E., Cignoni, M., Aloisi, A., et al. 2019, ApJ, 878, 1 Sánchez-Blázquez, P., Courty, S., Gibson, B. K., & Brook, C. B. 2009, MNRAS, 398, 591 Sánchez-Blázquez, P., Rosales-Ortega, F. F., Méndez-Abreu, J., et al. 2014, A&A, 570, A6

  56. [56]

    S., Komiyama, Y ., Okamoto, S., et al

    Sato, K. S., Komiyama, Y ., Okamoto, S., et al. 2025, PASJ[arXiv:2505.13161]

  57. [57]

    A., Bower, R

    Schaye, J., Crain, R. A., Bower, R. G., et al. 2015, MNRAS, 446, 521

  58. [58]

    J., Moreno, E., Nissen, P

    Schuster, W. J., Moreno, E., Nissen, P. E., & Pichardo, B. 2012, A&A, 538, A21

  59. [59]

    & Zinn, R

    Searle, L. & Zinn, R. 1978, ApJ, 225, 357

  60. [60]

    Sellwood, J. A. & Binney, J. J. 2002, MNRAS, 336, 785

  61. [61]

    2024, ApJ, 960, 83

    Sextl, E., Kudritzki, R.-P., Burkert, A., et al. 2024, ApJ, 960, 83

  62. [62]

    2010, MNRAS, 401, 791

    Springel, V . 2010, MNRAS, 401, 791

  63. [63]

    & Hernquist, L

    Springel, V . & Hernquist, L. 2003, MNRAS, 339, 289

  64. [64]

    2018, A&A, 618, A122

    Taibi, S., Battaglia, G., Kacharov, N., et al. 2018, A&A, 618, A122

  65. [65]

    2022, A&A, 665, A92

    Taibi, S., Battaglia, G., Leaman, R., et al. 2022, A&A, 665, A92

  66. [66]

    2020, A&A, 635, A152

    Taibi, S., Battaglia, G., Rejkuba, M., et al. 2020, A&A, 635, A152

  67. [67]

    M., et al

    Taibi, S., Battaglia, G., Roth, M. M., et al. 2024, A&A, 689, A88

  68. [68]

    A., Monachesi, A., Gomez, F

    Tau, E. A., Monachesi, A., Gomez, F. A., et al. 2025, A&A, 699, A93

  69. [69]

    A., Vivas, A

    Tau, E. A., Vivas, A. K., & Martínez-Vázquez, C. E. 2024, AJ, 167, 57

  70. [70]

    Tinsley, B. M. 1980, Fund. Cosmic Phys., 5, 287

  71. [71]

    B., Rosas-Guevara, Y ., Sillero, E., et al

    Tissera, P. B., Rosas-Guevara, Y ., Sillero, E., et al. 2022, MNRAS, 511, 1667

  72. [72]

    B., White, S

    Tissera, P. B., White, S. D. M., & Scannapieco, C. 2012, MNRAS, 420, 255

  73. [73]

    B., Verheijen, M

    Tully, R. B., Verheijen, M. A. W., Pierce, M. J., Huang, J.-S., & Wainscoat, R. J. 1996, AJ, 112, 2471

  74. [74]

    B., Gómez, F

    Varela-Lavin, S., Tissera, P. B., Gómez, F. A., Bignone, L. A., & Lagos, C. d. P. 2022, MNRAS, 514, 5340

  75. [75]

    A., Monachesi, A., et al

    Vera-Casanova, A., Gómez, F. A., Monachesi, A., et al. 2022, MNRAS, 514, 4898

  76. [76]

    A., et al

    Vera-Casanova, A., Monsalves Gonzalez, N., Gómez, F. A., et al. 2025, arXiv e-prints, arXiv:2503.17202

  77. [77]

    R., Dolphin, A

    Weisz, D. R., Dolphin, A. E., Skillman, E. D., et al. 2015, ApJ, 804, 136

  78. [78]

    K., et al

    Wheeler, C., Moreno, J., Rodriguez Wimberly, M. K., et al. 2025, arXiv e-prints, arXiv:2506.15785

  79. [79]

    White, S. D. M. & Rees, M. J. 1978, MNRAS, 183, 341

  80. [80]

    F., Dalcanton, J

    Williams, B. F., Dalcanton, J. J., Dolphin, A. E., Holtzman, J., & Sarajedini, A. 2009, ApJ, 695, L15

Showing first 80 references.