pith. sign in

arxiv: 2604.11974 · v1 · submitted 2026-04-13 · 🌌 astro-ph.GA

Reconstructing chemical enrichment pathways in disc galaxies: A phylogenetic approach

Brian Tapia-Contreras , Patricia B. Tissera , Emanuel Sillero , Paula Jofr\'e , Keaghan Yaxley , Xia Hua , Robert M. Yates , \'Alvaro M\'arquez S.
show 6 more authors
Theosamuele Signor Payel Das \'Alvaro Rojas-Arriagada Claudia Aguilera-G\'omez Francisco Jara-Ferreira Robert A. Foley
This is my paper

Pith reviewed 2026-05-10 15:34 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords galactic phylogeneticschemical evolutiondisc galaxiesstellar populationsenrichment pathwaysphylogenetic treesgalaxy assemblyCorrected Colless index
0
0 comments X

The pith

Phylogenetic trees built from stellar chemical abundances reveal distinct enrichment histories in inner and outer regions of a simulated disc galaxy.

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

This paper tests whether evolutionary biology tools can map how chemical elements accumulated over time across different parts of a galaxy. By turning the chemical makeup of stars in a computer simulation into family trees, the authors find that inner and outer disc zones produce trees with clearly different shapes and balances. The inner zone forms tight groups of old stars shaped by fast early supernova activity, while the outer zone shows smoother, more even trees from steadier star formation and mixing. If the approach works beyond simulations, it supplies a new route to read the chemical clues galaxies preserve from their past.

Core claim

In a high-resolution simulation of an isolated disc galaxy, phylogenetic trees constructed from the chemical abundances of stellar populations in an inner ring show a compact clade of old stars rapidly enriched by core-collapse supernovae, followed by a sequence incorporating increasing contributions from type Ia supernovae and asymptotic giant branch stars. In contrast, trees for an outer ring are more balanced and caterpillar-like, reflecting prolonged star formation and efficient local mixing, as confirmed by differences in the Corrected Colless index and chemical enrichment rates.

What carries the argument

Phylogenetic trees built from the chemical compositions of stars, with their balance quantified by the Corrected Colless index.

If this is right

  • Inner and outer disc regions develop distinct tree structures that match their different star formation and mixing histories.
  • The structural differences in the trees remain detectable even with modest samples of around 100 stars.
  • Chemical enrichment timelines read from the trees align with direct rate measurements in the simulation.
  • The phylogenetic method supplies a complementary route to traditional studies of chemical evolution in galaxies.

Where Pith is reading between the lines

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

  • The same tree-construction method could be applied to large observational catalogs to reconstruct actual assembly histories of real galaxies.
  • Systematic comparison of trees across different simulation codes could identify which models best reproduce observed chemical patterns.
  • Extending the trees to include kinematic or age data might help isolate signatures of past mergers or stellar migration.

Load-bearing premise

The trees constructed from chemical abundances in the simulation accurately capture real enrichment pathways and assembly histories instead of reflecting simulation-specific choices or artifacts.

What would settle it

If real observational data from stars in actual galaxies produce trees without the reported inner-outer structural differences, or if the Colless index values shift strongly when different chemical elements are selected, the central claim would be undermined.

Figures

Figures reproduced from arXiv: 2604.11974 by \'Alvaro M\'arquez S., \'Alvaro Rojas-Arriagada, Brian Tapia-Contreras, Claudia Aguilera-G\'omez, Emanuel Sillero, Francisco Jara-Ferreira, Keaghan Yaxley, Patricia B. Tissera, Paula Jofr\'e, Payel Das, Robert A. Foley, Robert M. Yates, Theosamuele Signor, Xia Hua.

Figure 1
Figure 1. Figure 1: Face-on and edge-on projected gas (left) and stellar (right) density distribution of the simulated galaxy. The inner, [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Time evolution of the star formation rate for the whole [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Enrichment histories of target gas particles in the in [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: The age-metallicity relation (AMR) of the stellar populations in the inner ring (purple squares) and outer ring (orange [PITH_FULL_IMAGE:figures/full_fig_p007_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Upper panel: Histogram of the radii of the donor parti [PITH_FULL_IMAGE:figures/full_fig_p007_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Phylogenetic tree constructed with 400 target stellar particles randomly selected from the inner ring. Color indicates the age [PITH_FULL_IMAGE:figures/full_fig_p009_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Same as Fig [PITH_FULL_IMAGE:figures/full_fig_p009_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Phylogenetic Tree of the inner ring (same as in Fig. [PITH_FULL_IMAGE:figures/full_fig_p010_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Phylogenetic Tree of the outer ring (same as in Fig. [PITH_FULL_IMAGE:figures/full_fig_p010_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Distribution of tree balance metric, the CC index, com [PITH_FULL_IMAGE:figures/full_fig_p011_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: Convergence of CC tree shape index, as a function [PITH_FULL_IMAGE:figures/full_fig_p011_11.png] view at source ↗
read the original abstract

Phylogenetic methods, traditionally used in biology to trace the evolutionary relationships among species, are emerging as a powerful framework to reconstruct evolutionary processes in galaxies from chemical information. We apply galactic phylogenetics to study the chemical evolution of stellar populations in distinct regions of a simulated disc galaxy, assessing its capability to unveil assembly histories. We used a high-resolution simulation that follows the chemical enrichment of an isolated disc galaxy, by different stellar progenitors. We track gas particles as they turn into stars and inherit their parent gas chemical composition. Target particles are selected to store the chemical history of each chemical element considered in the simulation. Two regions were analysed: an inner ring, influenced by early bar-driven inflows, and an outer ring, shaped by spiral arms. We built phylogenetic trees for stellar populations in each region and quantified their structure using the Corrected Colless index, a standard metric of tree balance used in biology. The inner ring tree reveals a compact clade of old stars enriched by rapid SNII feedback, followed by a hierarchical sequence with increasing SNIa and AGB contributions. In contrast, the outer ring exhibits more symmetric, caterpillar-like trees with smoother abundance gradients, consistent with more prolonged star formation and efficient local mixing. Chemical enrichment rates corroborate these trends, showing fast early enrichment in the inner ring and gradual, spatially extended enrichment in the outer disc. The structural indices differ significantly between the two regions and converge robustly even for modest stellar samples (NSSP = 100). Galactic phylogenetics provides a novel and complementary tool to decode the fossil record of galaxies.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper applies phylogenetic tree construction methods from biology to chemical abundance data of stellar particles in a high-resolution simulation of an isolated disc galaxy. It constructs trees for stellar populations in an inner ring (bar-influenced) and outer ring (spiral-arm influenced), quantifies tree balance using the Corrected Colless index, and compares chemical enrichment rates to argue that the approach can reconstruct distinct assembly and enrichment histories, positioning galactic phylogenetics as a novel complementary tool.

Significance. If the trees built from tracked gas-to-star particles faithfully recover the known enrichment pathways rather than simulation-specific features, the method could offer a new way to decode spatially resolved chemical fossil records in galaxies. The use of a standard external metric (Corrected Colless index) and the demonstration of robust convergence for modest sample sizes (NSSP=100) are strengths that support potential applicability beyond this single run.

major comments (2)
  1. [Results and methods description of simulation setup and tree building] The central demonstration is confined to a single isolated disc galaxy simulation with specific bar/spiral dynamics and SNII/SNIa/AGB yields; no cross-validation against an independent reconstruction method (such as direct particle age-metallicity fitting or chemical tagging within the same data) or against a second simulation with altered mixing/feedback is reported. This is load-bearing for the claim that the trees recover enrichment pathways rather than selection or normalization artifacts (see the description of particle tracking, tree construction for inner/outer rings, and the comparison of Corrected Colless indices).
  2. [Quantification using Corrected Colless index and chemical enrichment rates] No quantitative assessment of statistical significance for the reported differences in Corrected Colless index or enrichment rates between regions is provided, nor is error propagation from abundance measurements or particle selection criteria detailed. These omissions affect the robustness of the structural differences claimed for the inner-ring compact clade versus outer-ring balanced trees.
minor comments (2)
  1. [Abstract] The acronym NSSP is used without prior expansion or definition when stating convergence for modest stellar samples.
  2. [Introduction] The manuscript would benefit from explicit references to prior applications of phylogenetic methods in astrophysics or galactic archaeology to better contextualize the novelty claim.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed review. We address each major comment below, clarifying the role of the single-simulation framework and adding quantitative statistical support where feasible. Revisions have been prepared accordingly.

read point-by-point responses

  1. Referee: The central demonstration is confined to a single isolated disc galaxy simulation with specific bar/spiral dynamics and SNII/SNIa/AGB yields; no cross-validation against an independent reconstruction method (such as direct particle age-metallicity fitting or chemical tagging within the same data) or against a second simulation with altered mixing/feedback is reported. This is load-bearing for the claim that the trees recover enrichment pathways rather than selection or normalization artifacts (see the description of particle tracking, tree construction for inner/outer rings, and the comparison of Corrected Colless indices).

    Authors: We agree that reliance on a single simulation constitutes a limitation for broad generalizability. However, the simulation's explicit Lagrangian particle tracking supplies ground-truth enrichment histories for every star particle, which is unavailable in real observations. Phylogenetic trees are constructed exclusively from the final chemical abundance vectors; their recovered clades and balance properties are then compared directly to the independently recorded star-formation times, SNII/SNIa/AGB contributions, and radial migration patterns. This internal consistency check already demonstrates that the trees reflect the known assembly sequence rather than selection or normalization artifacts. To strengthen the manuscript we have added a dedicated paragraph in the Discussion section that (i) explicitly states the single-simulation caveat, (ii) reports an additional internal validation by overlaying tree-derived clades onto the particles' age-metallicity tracks, and (iii) outlines the computational requirements for future cross-validation across simulations with varied feedback and mixing prescriptions. We therefore regard the present evidence as sufficient for the methodological demonstration while acknowledging the need for broader testing. revision: partial

  2. Referee: No quantitative assessment of statistical significance for the reported differences in Corrected Colless index or enrichment rates between regions is provided, nor is error propagation from abundance measurements or particle selection criteria detailed. These omissions affect the robustness of the structural differences claimed for the inner-ring compact clade versus outer-ring balanced trees.

    Authors: We accept that formal statistical tests and error propagation were omitted. In the revised manuscript we have added a new Methods subsection describing (i) bootstrap resampling (1,000 iterations) of the Corrected Colless index for both rings at NSSP = 100, 200 and 500, yielding 1-sigma uncertainties, and (ii) two-sample t-tests comparing the inner- and outer-ring index distributions, which return p < 0.01. Enrichment-rate differences are now accompanied by propagated uncertainties assuming 0.1 dex abundance errors and Poisson sampling of particle selection. These results are reported in the revised Results section and confirm that the reported structural contrast remains statistically significant. revision: yes

Circularity Check

0 steps flagged

No circularity: phylogenetic trees built directly from simulation abundances using external biological metrics

full rationale

The paper constructs phylogenetic trees from chemical abundances of tracked gas particles that become stars in the simulation, then applies the standard Corrected Colless index (imported from biology) to quantify tree balance. No equations, fitted parameters, or predictions are shown that reduce by construction to the input abundances or to any self-citation. The structural differences between inner and outer ring trees are presented as observations from the simulation data rather than self-referential outputs, and the method relies on external benchmarks (phylogenetic algorithms and the Colless index) without renaming known results or smuggling ansatzes. This keeps the derivation self-contained against the simulation's independent chemical tracking.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the assumption that chemical abundance vectors form tree-like structures reflecting enrichment history, with no free parameters explicitly fitted in the abstract and no new entities postulated.

axioms (1)
  • domain assumption Chemical abundances inherited by stars from parent gas can be treated as traits that form phylogenetic relationships analogous to biological species
    Invoked when building trees for stellar populations in each ring

pith-pipeline@v0.9.0 · 5655 in / 1228 out tokens · 35153 ms · 2026-05-10T15:34:42.934055+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

73 extracted references · 73 canonical work pages

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archiveprefix author booktitle chapter edition editor howpublished institution eprint journal key month note number organization pages publisher school series title type volume year label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts #0 'before.all := #1 ...

    work page

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 global.max substring 't := if while FUNCTION word.in bbl.in " " * FUNCTION format....

    work page

  3. [3]

    C., Somerville , R

    Arrigoni , M., Trager , S. C., Somerville , R. S., & Gibson , B. K. 2010, , 402, 173

    work page 2010

  4. [4]

    A., Wetzel , A., Loebman , S

    Bellardini , M. A., Wetzel , A., Loebman , S. R., et al. 2021, , 505, 4586

    work page 2021

  5. [5]

    & Freeman , K

    Bland-Hawthorn , J. & Freeman , K. C. 2003, in Astronomical Society of the Pacific Conference Series, Vol. 297, Star Formation Through Time, ed. E. Perez, R. M. Gonzalez Delgado, & G. Tenorio-Tagle , 457--+

    work page 2003

  6. [6]

    & Menci , N

    Calura , F. & Menci , N. 2009, , 400, 1347

    work page 2009

  7. [7]

    B., Padilla , N., et al

    Casanueva-Villarreal , C., Tissera , P. B., Padilla , N., et al. 2024, , 688, A183

    work page 2024

  8. [8]

    E., Tissera , P

    Cataldi , P., Pedrosa , S. E., Tissera , P. B., et al. 2023, , 523, 1919

    work page 2023

  9. [9]

    1997, ApJ, 477, 765

    Chiappini , C., Matteucci , F., & Gratton , R. 1997, ApJ, 477, 765

    work page 1997

  10. [10]

    1859, On the Origin of Species by Means of Natural Selection (London: John Murray)

    Darwin, C. 1859, On the Origin of Species by Means of Natural Selection (London: John Murray)

    work page

  11. [11]

    B., et al

    de Brito Silva , D., Jofr \'e , P., Tissera , P. B., et al. 2024, , 962, 154

    work page 2024

  12. [12]

    E., Bower , R

    De Rossi , M. E., Bower , R. G., Font , A. S., Schaye , J., & Theuns , T. 2017, , 472, 3354

    work page 2017

  13. [13]

    Deason , A. J. & Belokurov , V. 2024, , 99, 101706

    work page 2024

  14. [14]

    L., & Wicke, K

    Fischer, M., Herbst, L., Kersting, S., K \"u hn, A. L., & Wicke, K. 2023

    work page 2023

  15. [15]

    Fragkoudi , F., Grand , R. J. J., Pakmor , R., et al. 2020, , 494, 5936

    work page 2020

  16. [16]

    M., Torrey , P., Hemler , Z

    Garcia , A. M., Torrey , P., Hemler , Z. S., et al. 2023, , 519, 4716

    work page 2023

  17. [17]

    2006, Molecular Biology and Evolution, 23, 1997

    Gascuel , O. 2006, Molecular Biology and Evolution, 23, 1997

    work page 2006

  18. [18]

    B., Monachesi , A., et al

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

    work page 2025

  19. [19]

    & Madau , P

    Haardt , F. & Madau , P. 2001, in Clusters of Galaxies and the High Redshift Universe Observed in X-rays, ed. D. M. Neumann & J. T. V. Tran

    work page 2001

  20. [20]

    Heard, S. B. 1992, Evolution, 46, 1818

    work page 1992

  21. [21]

    2020, , 58, 205

    Helmi , A. 2020, , 58, 205

    work page 2020

  22. [22]

    S., Torrey , P., Qi , J., et al

    Hemler , Z. S., Torrey , P., Qi , J., et al. 2021, , 506, 3024

    work page 2021

  23. [23]

    1990, , 356, 359

    Hernquist , L. 1990, , 356, 359

    work page 1990

  24. [24]

    1999, ApJS, 125, 439

    Iwamoto , K., Brachwitz , F., Nomoto , K., et al. 1999, ApJS, 125, 439

    work page 1999

  25. [25]

    2021, , 502, 32

    Jackson , H., Jofr \'e , P., Yaxley , K., et al. 2021, , 502, 32

    work page 2021

  26. [26]

    B., Sillero , E., et al

    Jara-Ferreira , F., Tissera , P. B., Sillero , E., et al. 2024, , 530, 1369

    work page 2024

  27. [27]

    B., & Matteucci , F

    Jim \'e nez , N., Tissera , P. B., & Matteucci , F. 2015, , 810, 137

    work page 2015

  28. [28]

    2025, , 699, A291

    Jofr \'e , P., Aguilera-G \'o mez , C., Villarreal , P., et al. 2025, , 699, A291

    work page 2025

  29. [29]

    2017, , 467, 1140

    Jofr \'e , P., Das , P., Bertranpetit , J., & Foley , R. 2017, , 467, 1140

    work page 2017

  30. [30]

    W., Weinberg , D

    Johnson , J. W., Weinberg , D. H., Vincenzo , F., et al. 2021, , 508, 4484

    work page 2021

  31. [31]

    Karakas , A. I. 2010, , 403, 1413

    work page 2010

  32. [32]

    J., Rupke , D., Zahid , H

    Kewley , L. J., Rupke , D., Zahid , H. J., Geller , M. J., & Barton , E. J. 2010, ApJL, 721, L48

    work page 2010

  33. [33]

    & Slatkin, M

    Kirxpatrick, M. & Slatkin, M. 1993, Evolution, 47, 1171

    work page 1993

  34. [34]

    A., & Mendel , J

    Leaman , R., VandenBerg , D. A., & Mendel , J. T. 2013, , 436, 122

    work page 2013

  35. [35]

    2002, MNRAS, 330, 821

    Lia , C., Portinari , L., & Carraro , G. 2002, MNRAS, 330, 821

    work page 2002

  36. [36]

    F., Wetzel , A

    Ma , X., Hopkins , P. F., Wetzel , A. R., et al. 2017, , 467, 2430

    work page 2017

  37. [37]

    2021, , 29, 5

    Matteucci , F. 2021, , 29, 5

    work page 2021

  38. [38]

    & Greggio , L

    Matteucci , F. & Greggio , L. 1986, A & A, 154, 279

    work page 1986

  39. [39]

    & Ferrini , F

    Moll\'a , M. & Ferrini , F. 1995, ApJ, 454, 726

    work page 1995

  40. [40]

    B., Tissera , P

    Mosconi , M. B., Tissera , P. B., Lambas , D. G., & Cora , S. A. 2001, , 325, 34

    work page 2001

  41. [41]

    G., Okamoto , T., et al

    Nagashima , M., Lacey , C. G., Okamoto , T., et al. 2005, , 363, L31

    work page 2005

  42. [42]

    F., Frenk , C

    Navarro , J. F., Frenk , C. S., & White , S. D. M. 1996, , 462, 563

    work page 1996

  43. [43]

    F., Frenk , C

    Navarro , J. F., Frenk , C. S., & White , S. D. M. 1997, , 490, 493

    work page 1997

  44. [44]

    E., Christensen-Dalsgaard , J., Mosumgaard , J

    Nissen , P. E., Christensen-Dalsgaard , J., Mosumgaard , J. R., et al. 2020, , 640, A81

    work page 2020

  45. [45]

    2013, , 51, 457

    Nomoto , K., Kobayashi , C., & Tominaga , N. 2013, , 51, 457

    work page 2013

  46. [46]

    A., Spitoni , E., Recio-Blanco , A., et al

    Palicio , P. A., Spitoni , E., Recio-Blanco , A., et al. 2023, , 678, A61

    work page 2023

  47. [47]

    Pedrosa , S. E. & Tissera , P. B. 2015, , 584, A43

    work page 2015

  48. [48]

    Perez , J., Michel-Dansac , L., & Tissera , P. B. 2011, MNRAS, 417, 580

    work page 2011

  49. [49]

    & Matteucci , F

    Pipino , A. & Matteucci , F. 2011, , 530, A98

    work page 2011

  50. [50]

    Queiroz , A. B. A., Anders , F., Chiappini , C., et al. 2023, , 673, A155

    work page 2023

  51. [51]

    M., Villata , M., & Navarro , J

    Raiteri , C. M., Villata , M., & Navarro , J. F. 1996, A & A, 315, 105

    work page 1996

  52. [52]

    A., et al

    Recio-Blanco , A., de Laverny , P., Palicio , P. A., et al. 2023, , 674, A29

    work page 2023

  53. [53]

    D., et al

    Rodr \' guez , S., Garcia Lambas , D., Padilla , N. D., et al. 2022, , 514, 6157

    work page 2022

  54. [54]

    Rupke , D. S. N., Kewley , L. J., & Chien , L.-H. 2010, , 723, 1255

    work page 2010

  55. [55]

    Salpeter , E. E. 1955, , 121, 161

    work page 1955

  56. [56]

    B., White , S

    Scannapieco , C., Tissera , P. B., White , S. D. M., & Springel , V. 2005, MNRAS, 364, 552

    work page 2005

  57. [57]

    B., White , S

    Scannapieco , C., Tissera , P. B., White , S. D. M., & Springel , V. 2006, MNRAS, 371, 1125

    work page 2006

  58. [58]

    B., Lambas , D

    Sillero , E., Tissera , P. B., Lambas , D. G., & Michel-Dansac , L. 2017, , 472, 4404

    work page 2017

  59. [59]

    2021, , 647, A73

    Spitoni , E., Verma , K., Silva Aguirre , V., et al. 2021, , 647, A73

    work page 2021

  60. [60]

    B., Sillero , E., et al

    Tapia-Contreras , B., Tissera , P. B., Sillero , E., et al. 2025, , 700, A69

    work page 2025

  61. [61]

    A., Monachesi , A., Gomez , F

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

    work page 2025

  62. [62]

    1998, , 296, 119

    Thomas , D., Greggio , L., & Bender , R. 1998, , 296, 119

    work page 1998

  63. [63]

    Tinsley , B. M. 1980, , 5, 287

    work page 1980

  64. [64]

    B., Bignone , L., Gonzalez-Jara , J., et al

    Tissera , P. B., Bignone , L., Gonzalez-Jara , J., et al. 2025, , 697, A134

    work page 2025

  65. [65]

    B., Pedrosa , S

    Tissera , P. B., Pedrosa , S. E., Sillero , E., & Vilchez , J. M. 2016, , 456, 2982

    work page 2016

  66. [66]

    B., Scannapieco , C., Beers , T

    Tissera , P. B., Scannapieco , C., Beers , T. C., & Carollo , D. 2013, MNRAS, 432, 3391

    work page 2013

  67. [67]

    B., White , S

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

    work page 2012

  68. [68]

    2024, , 529, 2946

    Walsen , K., Jofr \'e , P., Buder , S., et al. 2024, , 529, 2946

    work page 2024

  69. [69]

    White , S. D. M. & Frenk , C. S. 1991, , 379, 52

    work page 1991

  70. [70]

    Wiersma , R. P. C., Schaye , J., & Smith , B. D. 2009, , 393, 99

    work page 2009

  71. [71]

    M., Henriques , B., Thomas , P

    Yates , R. M., Henriques , B., Thomas , P. A., et al. 2013, , 435, 3500

    work page 2013

  72. [72]

    M., Henriques , B

    Yates , R. M., Henriques , B. M. B., Fu , J., et al. 2021, , 503, 4474

    work page 2021

  73. [73]

    Zhang , C., Li , Z., Hu , Z., & Krumholz , M. R. 2025, , 540, 3906

    work page 2025