pith. sign in

arxiv: 2605.24104 · v1 · pith:6RRJ3STAnew · submitted 2026-05-22 · 🌌 astro-ph.GA · astro-ph.CO

Resolving galaxy formation in the early Universe with BonFIRE and CampFIRE

Pith reviewed 2026-06-30 15:15 UTC · model grok-4.3

classification 🌌 astro-ph.GA astro-ph.CO
keywords galaxy formationcosmological simulationsUV luminosity functionearly universestar formation efficiencybursty star formationPopulation III starsJWST observations
0
0 comments X

The pith

Simulations of early galaxy formation predict UV luminosity functions that match observations at faint magnitudes with a turnover at M_UV ≈ -14.

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

The paper presents the first results from the BonFIRE and CampFIRE cosmological hydrodynamic simulations using the FIRE-3 model to study galaxy assembly at redshifts greater than 6. A resampling method merges the large volume statistics of BonFIRE with the finer resolution of CampFIRE to cover galaxy stellar masses from 10,000 to 10 billion solar masses. The simulations show that galaxies assemble through clustered, bursty star formation, achieving halo-scale efficiencies of 10-30 percent in high-mass systems and over 1 percent in some low-mass halos that host ultra-compact galaxies. The resulting predictions for UV luminosity functions from redshift 9 to 25 agree with current data at the faint end while slightly exceeding the observed numbers of brighter galaxies. A reader would care because these outcomes test whether standard feedback-regulated models can account for the rapid appearance of galaxies at cosmic dawn without invoking new physics.

Core claim

Galaxy formation in this suite emerges through clustered, bursty star formation, with halo-scale star formation efficiencies reaching 10-30% in high-mass halos. A subset of low-mass halos also have surprisingly high efficiencies of ≳1% and host ultra-compact galaxies with narrow age spreads. We predict galaxy UV luminosity functions at 9≲z≲25 in broad agreement with observations at M_UV≳−19, with a faint-end turnover at M_UV≈−14, but we slightly overpredict the abundance of brighter galaxies. We find that UV luminosity variability in early galaxies is strongly mass-dependent, with halo-to-halo scatter dominating at low masses and contributing comparably to rapid temporal burstiness at M_halo

What carries the argument

The resampling procedure that combines the large statistics of the BonFIRE simulation with the higher resolution of the CampFIRE simulation to predict galaxy properties over a wide dynamic range.

If this is right

  • UV luminosity functions at 9≲z≲25 exhibit broad agreement with observations for M_UV≳−19 and a faint-end turnover at M_UV≈−14.
  • Halo-scale star formation efficiencies reach 10-30% in high-mass halos and ≳1% in a subset of low-mass halos that form ultra-compact galaxies.
  • UV luminosity variability is mass-dependent, with halo-to-halo scatter dominating at low masses and comparable to temporal burstiness at higher masses.
  • A simple Pop III model with top-heavy IMF produces results in broad agreement with independent predictions and constraints.

Where Pith is reading between the lines

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

  • The ability to span four orders of magnitude in galaxy mass with one consistent model allows direct comparison of low-mass and high-mass assembly pathways at the same epoch.
  • The reported slight excess of bright galaxies at high redshift could be tested by varying feedback strength in follow-up runs to identify the minimal adjustment needed.
  • The mass dependence of UV variability implies that single-epoch observations of individual high-redshift galaxies may not reflect the time-averaged population properties.
  • The presence of ultra-compact galaxies in low-mass halos with narrow age spreads offers a possible observational signature for future high-resolution imaging.

Load-bearing premise

The resampling procedure to combine the large statistics of BonFIRE with the higher resolution of CampFIRE robustly predicts galaxy properties over a wide dynamic range.

What would settle it

Measurements of the UV luminosity function between redshifts 9 and 25 that show either no turnover near M_UV = -14 or a significantly lower abundance of galaxies brighter than M_UV = -19 than the simulations produce would settle whether the central predictions hold.

Figures

Figures reproduced from arXiv: 2605.24104 by Alessandra Venditti, Andrew Wetzel, Claude-Andre Faucher-Giguere, Connor Painter, Guochao Sun, James Bullock, Jenna Samuel, Jonathan Stern, Jorge Moreno, Julian Munoz, Maria Straight, Michael Boylan-Kolchin, Philip Hopkins, Pratik Gandhi, Rachel Cochrane, Robert Feldmann, Steven Finkelstein, Volker Bromm, Xuejian Shen.

Figure 1
Figure 1. Figure 1: Left: Stellar, gas, and dark matter density projected through a 5 cMpc slice in the BonFIRE volume. Right: Stellar density in the CampFIRE volume at the three resolutions simulated in the suite (left column, resolution increasing from bottom to top). Stellar density around the central halo in the CampFIRE region at each resolution (right column). All labeled distances are comoving. is only ≈ 0.2% of the Bo… view at source ↗
Figure 2
Figure 2. Figure 2: Left: The stellar mass–halo mass (SMHM) relation in BonFIRE+CampFIRE, BonFIRE, and CampFIRE-800 at z ∼ 9. Lines are median M⋆ in each Mhalo bin and shaded regions show the 68% scatter about the median. BonFIRE+CampFIRE extends the coverage of the SMHM relation in the simulations down to M⋆ ∼ 104 M⊙ at Mhalo ∼ 108 M⊙, whereas BonFIRE on its own suffers from a resolution-induced flattening in the relation at… view at source ↗
Figure 3
Figure 3. Figure 3: The stellar mass function (SMF) in BonFIRE+CampFIRE and CampFIRE-6k over 6 ≲ z ≲ 15. Shaded regions for simulations are the minimum and maximum values of the SMF over the corresponding redshift interval in each panel, whereas, lines and errorbars are the coadded SMF and 1 σ Poisson errors. BonFIRE+CampFIRE predicts a sharply rising SMF at M⋆ ≲ 107 M⊙, indicating a large population of low-mass galaxies at z… view at source ↗
Figure 4
Figure 4. Figure 4: Left: The halo-scale star formation efficiency (SFE, ϵ⋆) in BonFIRE+CampFIRE, BonFIRE, and CampFIRE-800 as a function of halo mass at z ∼ 9. As in [PITH_FULL_IMAGE:figures/full_fig_p013_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Images of three galaxies representing a diversity of morphologies in BonFIRE at z = 9. Left: True stellar surface density showing substructure down to scales of ∼ 10 pc. Dotted cyan circles are the radius enclosing 50% of a galaxy’s stellar mass (R⋆, 1/2). Middle: Map of stellar age highlighting the youngest stars in the lightest colors. Right: Mock JWST NIRCam F115W image showing rest-frame UV emission. L… view at source ↗
Figure 6
Figure 6. Figure 6: shows the size–mass (R⋆, 1/2–M⋆) relation for galaxies in BonFIRE+CampFIRE, BonFIRE, and CampFIRE-800 at z ∼ 9. We calculate the size of a galaxy as the spherical three-dimensional radius en￾closing 50% of a galaxy’s stellar mass (R⋆, 1/2). The horizontal grey lines mark galaxy size resolution limits, which we approximate as three times the gravitational force softening of stars (3 εstar) in each simulatio… view at source ↗
Figure 7
Figure 7. Figure 7: Top: The stellar mass functions of ultra-compact galaxies (UCGs) at z ∼ 9 in BonFIRE (blue solid), Camp￾FIRE-6k (orange dot-dashed), and CampFIRE-800 (pink dashed). Bottom: The fraction of galaxies classified as UCGs, fUCG, in each mass bin. Shaded regions indicate Poisson uncertainties. Though the absolute abundance of UCGs varies significantly with resolution, the stellar mass range over which UCGs domin… view at source ↗
Figure 8
Figure 8. Figure 8: Joint distributions of stellar mass, halo mass, star formation efficiency, stellar half-mass radius, and stellar age dispersion for galaxies in CampFIRE-800 (top row, pink), CampFIRE-6k (middle row, orange), and BonFIRE (bottom row, blue) at z ∼ 9. Filled contours show ultra-compact galaxies (UCGs), and unfilled contours show the total galaxy population. Contours represent enclosed probability levels (75/9… view at source ↗
Figure 9
Figure 9. Figure 9: Left: The MUV–Mhalo relation in BonFIRE+CampFIRE, BonFIRE, and CampFIRE-800 at z ∼ 9. Lines are median MUV in each Mhalo bin and shaded regions show the 68% scatter about the median. Solid and dashed colored lines include dust, while the dotted purple line shows dust-free results. The spread in the galaxy population is large at all halo masses, but especially at Mhalo ≲ 109.5 M⊙. Right: The evolution of th… view at source ↗
Figure 10
Figure 10. Figure 10: The BonFIRE+CampFIRE UV luminosity functions (UVLFs) at 9 ≲ z ≲ 25. In each panel, we show a purple line representing the UVLF stacked over ∼ 60 Myr with the average redshift indicated in the top left legend. We include a dust correction in our fiducial results, but we show results without dust as dotted purple lines (with minimal effects at faint magnitudes). The purple band is the maximal and minimal (d… view at source ↗
Figure 11
Figure 11. Figure 11: Top: Stacked BonFIRE+CampFIRE UVLFs in six redshift bins (points) with best-fit Schechter with turnover models (solid curves, Eq. 5). Redshift bins are the same as in [PITH_FULL_IMAGE:figures/full_fig_p023_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: The UV luminosity density and corre￾sponding star formation rate density (SFRD) in Bon￾FIRE+CampFIRE at 9 ≲ z ≲ 25. We compare to theoretical results from FIREbox-HR (R. Feldmann et al. 2025) and P. Madau & M. Dickinson (2014), as well as observational re￾sults from Y. Harikane et al. (2022); R. J. Bouwens et al. (2022); C. T. Donnan et al. (2023, 2024); Y. Harikane et al. (2023, 2024); I. Chemerynska et … view at source ↗
Figure 13
Figure 13. Figure 13 [PITH_FULL_IMAGE:figures/full_fig_p025_13.png] view at source ↗
Figure 14
Figure 14. Figure 14: The UV luminosity variability of galaxies at 9 < z < 12 as a function of halo mass in BonFIRE, Camp￾FIRE-6k, and CampFIRE-800. In all panels, solid colored lines show the median scatter measured in our simulations, and shaded regions indicate the 68% scatter across snap￾shots. Top: The inter-halo scatter (σinter, halo-to-halo varia￾tions for smooth star formation) is large in general (≳ 1 mag) and increas… view at source ↗
Figure 15
Figure 15. Figure 15: The Pop III star formation rate density (SFRD) in each of the BonFIRE, CampFIRE-6k, and CampFIRE-800 simulations over time. Note that the CampFIRE-6k run ex￾tends to z = 6, allowing us to make predictions through the end of reionization. We compare to various Pop III models from the literature and to limits from recent observations of candidate Pop III galaxies (see text for details). we recover ∼ 0.8 − 1… view at source ↗
Figure 16
Figure 16. Figure 16: The Pop III galaxy UVLF for Bon￾FIRE+CampFIRE and CampFIRE-800 at z ∼ 9, and for CampFIRE-6k at 6 ≤ z ≤ 7. We compare to photomet￾ric Pop III candidates from S. Fujimoto et al. (2025b) at 5.6 ≤ z ≤ 6.6, as well as the empirically calibrated models of H. A. G. Cruz et al. (2025) and A. Venditti et al. (2025). The BonFIRE+CampFIRE Pop III galaxy UVLF is simi￾lar to the observations where there is overlap be… view at source ↗
Figure 17
Figure 17. Figure 17: The evolution of the halo mass function in BonFIRE (left) and CampFIRE-800 (right) to z = 9. The dotted line is a Hubble-volume averaged fit from (J. Tinker et al. 2008) at z = 9; in the left panel we show the Tinker fit for average matter density and in the left panel we show the fit for CampFIRE’s corresponding overdensity (δ ≈ 0.4). counterparts. This underestimation shows that low-resolution simulatio… view at source ↗
Figure 18
Figure 18. Figure 18: Left: The fraction of halos occupied by a galaxy in BonFIRE at z = 9 − 25. The halo occupation fraction (HOF) rises steeply with halo mass, as expected, and it does not significantly evolve with redshift over z = 25 to z = 9. We note that halos at Mhalo < 107.5 M⊙ (≲ 100 particles) are likely numerically under-resolved. This metric remains unchanged by our resampling procedure. Right: We compare the HOF i… view at source ↗
Figure 19
Figure 19. Figure 19: Resolution convergence tests for the halo mass function (HMF), stellar mass function (SMF), and UVLF in BonFIRE, CampFIRE-6k, and CampFIRE-800 at z = 9. We show results from only the subregion of BonFIRE corresponding to CampFIRE for a fair comparison. The HMF is well converged across the three simulations for Mhalo ≳ 107 M⊙. The SMFs reflect a complicated relationship between resolution and the buildup o… view at source ↗
Figure 20
Figure 20. Figure 20: Resolution convergence tests for more nuanced galaxy properties in BonFIRE, CampFIRE-6k, and CampFIRE-800 at z = 9. The size of galaxies as measured by their median 3D stellar half-mass radii (R⋆, 1/2, left) shows clear resolution dependence in BonFIRE for halos at Mhalo ≲ 108.5 M⊙, such that the galaxy sizes tend towards the stellar force softening limit (8 pc). Whereas, galaxy sizes in the CampFIRE runs… view at source ↗
Figure 21
Figure 21. Figure 21: Dust attenuation in the UV, ∆MUV, as a function of halo mass at z ∼ 9 from SKIRT radiative transfer calculations of BonFIRE galaxies (points). The solid curve shows our best-fit exponential model, while the dashed curve shows the fit from R. Feldmann et al. (2025). Our model predicts a steeper rise in attenuation with halo mass and a lower characteristic mass scale for the onset of significant dust extinc… view at source ↗
read the original abstract

The abundance and rapid growth of galaxies at cosmic dawn revealed by the James Webb Space Telescope challenges models of galaxy formation, motivating new simulations to uncover the processes driving early galaxy assembly. We present the first results from BonFIRE ($L\approx40$ cMpc, $m_{\rm baryon}\approx5\times10^4~\rm{M}_{\odot}$) and CampFIRE ($L\approx5$ cMpc, at both $m_{\rm baryon}\approx800~\rm{M}_{\odot}$ and $\approx6\times10^3~\rm{M}_{\odot}$), a suite of cosmological hydrodynamic simulations of early galaxy formation ($z\gtrsim6$) from the Feedback In Realistic Environments (FIRE) project, using the FIRE-3 model. We use a resampling procedure to combine the large statistics of BonFIRE with the higher resolution of CampFIRE and robustly predict galaxy properties over a wide dynamic range ($M_{\star}\sim10^4-10^{10}~\rm{M}_{\odot}$). Galaxy formation in this suite emerges through clustered, bursty star formation, with halo-scale star formation efficiencies reaching $10-30\%$ in high-mass halos. A subset of low-mass halos also have surprisingly high efficiencies of $\gtrsim1\%$ and host ultra-compact galaxies with narrow age spreads. We predict galaxy UV luminosity functions at $9\lesssim~z\lesssim25$ in broad agreement with observations at $M_{\rm UV}\gtrsim-19$, with a faint-end turnover at $M_{\rm UV}\approx-14$, but we slightly overpredict the abundance of brighter galaxies. We find that UV luminosity variability in early galaxies is strongly mass-dependent, with halo-to-halo scatter dominating at low masses and contributing comparably to rapid temporal burstiness at $M_{\rm halo}\gtrsim10^{10}~\rm{M}_{\odot}$. We also present first results from a simple Pop~III model with a top-heavy IMF, demonstrating broad agreement with independent Pop~III predictions and observational constraints.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

2 major / 2 minor

Summary. The manuscript presents first results from the BonFIRE (L≈40 cMpc, m_baryon≈5×10^4 M_⊙) and CampFIRE (L≈5 cMpc, m_baryon≈800 and 6×10^3 M_⊙) cosmological hydrodynamic simulations using the FIRE-3 model. A resampling procedure merges BonFIRE's volume statistics with CampFIRE's resolution to predict galaxy properties over M_star∼10^4–10^10 M_⊙ at z≳6. Galaxy formation proceeds via clustered, bursty star formation with halo-scale efficiencies of 10–30% in high-mass halos (and ≳1% in some low-mass halos hosting ultra-compact galaxies). The predicted UV luminosity functions at 9≲z≲25 agree broadly with observations for M_UV≳−19, show a faint-end turnover at M_UV≈−14, and slightly overpredict brighter galaxies; UV variability is mass-dependent. A simple Pop III model with top-heavy IMF is also presented.

Significance. If the central predictions hold after validation of the resampling, the work would be significant for interpreting JWST observations of cosmic dawn, as it supplies forward-model predictions of UV LFs, star-formation efficiencies, and variability over a wide mass range using the established FIRE-3 physics. The combination of large-volume and high-resolution runs plus the Pop III extension are strengths.

major comments (2)
  1. [methods (resampling procedure)] The resampling procedure (described in the methods section on combining BonFIRE and CampFIRE) is load-bearing for all wide-dynamic-range claims, including the faint-end turnover location at M_UV≈−14 and the 10–30% efficiencies. No explicit validation tests are shown for how the procedure handles resolution-dependent burstiness, halo matching, or weighting in the overlap regime; if offsets arise there, both the turnover and the slight overprediction of bright galaxies become sensitive to this choice rather than to FIRE-3 physics alone.
  2. [UV luminosity functions section] § on UV luminosity functions: the statement of 'broad agreement' at M_UV≳−19 and 'slight overprediction' of brighter galaxies is presented without quantitative comparison (e.g., χ² values, direct overlay with specific observational datasets and their error bars, or exclusion criteria for the plotted points). This weakens the ability to assess whether the discrepancy is within expected model uncertainties.
minor comments (2)
  1. [figures] Figure captions for the UV LF plots should explicitly state the redshift bins, the observational references used for comparison, and any completeness cuts applied to the simulated galaxies.
  2. [results on efficiencies] The definition of 'halo-scale star formation efficiency' (used for the 10–30% and ≳1% values) should be given with an equation or clear reference to how it is computed from the simulation outputs.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their detailed and constructive report. We address each major comment below. Both points identify areas where the manuscript can be strengthened with additional material, and we will incorporate revisions to address them.

read point-by-point responses
  1. Referee: [methods (resampling procedure)] The resampling procedure (described in the methods section on combining BonFIRE and CampFIRE) is load-bearing for all wide-dynamic-range claims, including the faint-end turnover location at M_UV≈−14 and the 10–30% efficiencies. No explicit validation tests are shown for how the procedure handles resolution-dependent burstiness, halo matching, or weighting in the overlap regime; if offsets arise there, both the turnover and the slight overprediction of bright galaxies become sensitive to this choice rather than to FIRE-3 physics alone.

    Authors: We agree that the resampling procedure is central to the wide-dynamic-range results and that explicit validation tests would strengthen the manuscript. In the revised version we will add a new subsection (or appendix) that presents validation tests in the overlap regime, including: (i) direct comparisons of star-formation histories and burstiness metrics between BonFIRE and CampFIRE at matched halo masses, (ii) halo-matching accuracy statistics, and (iii) sensitivity checks on the weighting scheme. These additions will demonstrate that the reported turnover at M_UV≈−14 and the efficiency trends are robust to the procedure rather than driven by resolution mismatches. revision: yes

  2. Referee: [UV luminosity functions section] § on UV luminosity functions: the statement of 'broad agreement' at M_UV≳−19 and 'slight overprediction' of brighter galaxies is presented without quantitative comparison (e.g., χ² values, direct overlay with specific observational datasets and their error bars, or exclusion criteria for the plotted points). This weakens the ability to assess whether the discrepancy is within expected model uncertainties.

    Authors: We accept that the current text relies on qualitative language without quantitative support. In the revision we will add quantitative comparisons to the UV luminosity function section, including χ² values (or equivalent metrics) against the primary observational datasets, explicit overlays that include observational error bars, and a clear statement of the selection/exclusion criteria used for the plotted points. This will allow readers to evaluate the significance of the slight overprediction at the bright end relative to model uncertainties. revision: yes

Circularity Check

0 steps flagged

No significant circularity; forward-modeling simulations with independent resampling step

full rationale

The paper presents results from cosmological hydrodynamic simulations (BonFIRE and CampFIRE) using the FIRE-3 model. Galaxy properties and UV luminosity functions are direct outputs of running the simulations from initial conditions, not defined in terms of the target observables or fitted to them. The resampling procedure merges volume and resolution statistics but is presented as a methodological choice for dynamic range, not a self-definitional fit or prediction that reduces to input data by construction. No self-citation load-bearing steps, ansatzes smuggled via citation, or renaming of known results appear in the load-bearing claims. The derivation chain is self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

2 free parameters · 2 axioms · 0 invented entities

Based solely on the abstract, the central claims rest on the validity of the FIRE-3 feedback and star formation model plus the accuracy of the resampling procedure; no independent evidence for these is provided in the available text.

free parameters (2)
  • BonFIRE baryon mass resolution
    Chosen simulation resolution of approximately 5 times 10^4 solar masses for the large-volume run.
  • CampFIRE baryon mass resolutions
    Chosen higher resolutions of approximately 800 and 6 times 10^3 solar masses for the small-volume runs.
axioms (2)
  • domain assumption The FIRE-3 model accurately represents the relevant baryonic physics for galaxy formation at z greater than or equal to 6.
    All results are generated using the FIRE-3 model as stated in the abstract.
  • domain assumption The resampling procedure preserves the statistical properties needed to predict galaxy UV luminosities across the full mass range.
    The abstract states that this procedure is used to combine the two simulation sets for robust predictions.

pith-pipeline@v0.9.1-grok · 5986 in / 1588 out tokens · 42480 ms · 2026-06-30T15:15:07.451801+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

163 extracted references · 161 canonical work pages · 10 internal anchors

  1. [1]

    D., Vanzella, E., et al

    Adamo, A., Bradley, L. D., Vanzella, E., et al. 2024, Nature, 632, 513, doi: 10.1038/s41586-024-07703-7

  2. [2]

    J., Conselice, C

    Adams, N. J., Conselice, C. J., Ferreira, L., et al. 2023, MNRAS, 518, 4755, doi: 10.1093/mnras/stac3347

  3. [3]

    J., Conselice, C

    Adams, N. J., Conselice, C. J., Austin, D., et al. 2024, ApJ, 965, 169, doi: 10.3847/1538-4357/ad2a7b Angl´ es-Alc´ azar, D., Faucher-Gigu` ere, C.-A., Kereˇ s, D., et al. 2017a, MNRAS, 470, 4698, doi: 10.1093/mnras/stx1517 Angl´ es-Alc´ azar, D., Faucher-Gigu` ere, C.-A., Quataert, E., et al. 2017b, MNRAS, 472, L109, doi: 10.1093/mnrasl/slx161 Astropy Co...

  4. [4]

    2018, MNRAS, 479, 5184, doi: 10.1093/mnras/sty1820

    Atek, H., Richard, J., Kneib, J.-P., & Schaerer, D. 2018, MNRAS, 479, 5184, doi: 10.1093/mnras/sty1820

  5. [5]

    J., et al

    Atek, H., Shuntov, M., Furtak, L. J., et al. 2023, MNRAS, 519, 1201, doi: 10.1093/mnras/stac3144

  6. [6]

    A GLIMPSE of the 99%: a census of the faintest galaxies during the epoch reionization and its implications for galaxy formation models

    Atek, H., Chemerynska, I., Furtak, L. J., et al. 2026, arXiv e-prints, arXiv:2604.23823, doi: 10.48550/arXiv.2604.23823

  7. [7]

    2018, MNRAS, 478, 1520, doi: 10.1093/mnras/sty1057

    Baumgardt, H., & Hilker, M. 2018, MNRAS, 478, 1520, doi: 10.1093/mnras/sty1057

  8. [8]

    H., Hearin, A

    Behroozi, P., Wechsler, R. H., Hearin, A. P., & Conroy, C. 2019, MNRAS, 488, 3143, doi: 10.1093/mnras/stz1182

  9. [9]

    S., & Silk, J

    Behroozi, P. S., & Silk, J. 2015, ApJ, 799, 32, doi: 10.1088/0004-637X/799/1/32

  10. [10]

    S., Wechsler, R

    Behroozi, P. S., Wechsler, R. H., & Conroy, C. 2013a, ApJL, 762, L31, doi: 10.1088/2041-8205/762/2/L31

  11. [11]

    S., Wechsler, R

    Behroozi, P. S., Wechsler, R. H., & Wu, H.-Y. 2013b, ApJ, 762, 109, doi: 10.1088/0004-637X/762/2/109

  12. [12]

    S., Wechsler, R

    Behroozi, P. S., Wechsler, R. H., Wu, H.-Y., et al. 2013c, ApJ, 763, 18, doi: 10.1088/0004-637X/763/1/18

  13. [13]

    2022, ApJ, 940, 55, doi: 10.3847/1538-4357/ac86d1

    Stefanon, M. 2022, ApJ, 940, 55, doi: 10.3847/1538-4357/ac86d1

  14. [14]

    J., Oesch, P

    Bouwens, R. J., Oesch, P. A., Illingworth, G. D., Ellis, R. S., & Stefanon, M. 2017, ApJ, 843, 129, doi: 10.3847/1538-4357/aa70a4

  15. [15]

    J., Stefanon, M., Brammer, G., et al

    Bouwens, R. J., Stefanon, M., Brammer, G., et al. 2023, MNRAS, 523, 1036, doi: 10.1093/mnras/stad1145 40Samuel et al

  16. [16]

    2023, Nature Astronomy, 7, 731, doi: 10.1038/s41550-023-01937-7

    Boylan-Kolchin, M. 2023, Nature Astronomy, 7, 731, doi: 10.1038/s41550-023-01937-7

  17. [17]

    2025, MNRAS, 538, 3210, doi: 10.1093/mnras/staf471

    Boylan-Kolchin, M. 2025, MNRAS, 538, 3210, doi: 10.1093/mnras/staf471

  18. [18]

    R., Johnson, B

    Boylan-Kolchin, M., Weisz, D. R., Johnson, B. D., et al. 2015, MNRAS, 453, 1503, doi: 10.1093/mnras/stv1736

  19. [19]

    2013, Reports on Progress in Physics, 76, 112901, doi: 10.1088/0034-4885/76/11/112901

    Bromm, V. 2013, Reports on Progress in Physics, 76, 112901, doi: 10.1088/0034-4885/76/11/112901

  20. [20]

    P., & Loeb, A

    Bromm, V., Kudritzki, R. P., & Loeb, A. 2001, ApJ, 552, 464, doi: 10.1086/320549

  21. [21]

    Bromm, V., & Larson, R. B. 2004, ARA&A, 42, 79, doi: 10.1146/annurev.astro.42.053102.134034

  22. [22]

    2011, ARA&A, 49, 373, doi: 10.1146/annurev-astro-081710-102608

    Bromm, V., & Yoshida, N. 2011, ARA&A, 49, 373, doi: 10.1146/annurev-astro-081710-102608

  23. [23]

    2024, ApJ, 973, 149, doi: 10.3847/1538-4357/ad67ca

    Byrne, L., Faucher-Gigu` ere, C.-A., Wellons, S., et al. 2024, ApJ, 973, 149, doi: 10.3847/1538-4357/ad67ca

  24. [24]

    M., Akins, H

    Casey, C. M., Akins, H. B., Shuntov, M., et al. 2024, ApJ, 965, 98, doi: 10.3847/1538-4357/ad2075

  25. [25]

    2025, A&A, 704, A158, doi: 10.1051/0004-6361/202555082

    Castellano, M., Fontana, A., Merlin, E., et al. 2025, A&A, 704, A158, doi: 10.1051/0004-6361/202555082

  26. [26]

    J., et al

    Chemerynska, I., Atek, H., Furtak, L. J., et al. 2026, MNRAS, 546, staf2267, doi: 10.1093/mnras/staf2267

  27. [27]

    L., Boylan-Kolchin, M., et al

    Chworowsky, K., Finkelstein, S. L., Boylan-Kolchin, M., et al. 2024, AJ, 168, 113, doi: 10.3847/1538-3881/ad57c1

  28. [28]

    2024, A&A, 686, A128, doi: 10.1051/0004-6361/202348091

    Ciesla, L., Elbaz, D., Ilbert, O., et al. 2024, A&A, 686, A128, doi: 10.1051/0004-6361/202348091

  29. [29]

    K., Angl´ es-Alc´ azar, D., Mercedes-Feliz, J., et al

    Cochrane, R. K., Angl´ es-Alc´ azar, D., Mercedes-Feliz, J., et al. 2023, MNRAS, 523, 2409, doi: 10.1093/mnras/stad1528

  30. [30]

    Cruz, H. A. G., Mu˜ noz, J. B., Sabti, N., & Kamionkowski, M. 2025, PhRvD, 111, 083503, doi: 10.1103/PhysRevD.111.083503

  31. [31]

    L., Tacchella, S., ¨Ubler, H., et al

    Danhaive, A. L., Tacchella, S., ¨Ubler, H., et al. 2025, MNRAS, 543, 3249, doi: 10.1093/mnras/staf1540 Dav´ e, R., Angl´ es-Alc´ azar, D., Narayanan, D., et al. 2019, MNRAS, 486, 2827, doi: 10.1093/mnras/stz937

  32. [32]

    R., Bromm, V., & Pacucci, F

    Dayal, P., Choudhury, T. R., Bromm, V., & Pacucci, F. 2017, ApJ, 836, 16, doi: 10.3847/1538-4357/836/1/16

  33. [33]

    2018, PhR, 780, 1, doi: 10.1016/j.physrep.2018.10.002

    Dayal, P., & Ferrara, A. 2018, PhR, 780, 1, doi: 10.1016/j.physrep.2018.10.002

  34. [34]

    2023, MNRAS, 523, 3201, doi: 10.1093/mnras/stad1557

    Li, Z. 2023, MNRAS, 523, 3201, doi: 10.1093/mnras/stad1557

  35. [35]

    T., McLeod, D

    Donnan, C. T., McLeod, D. J., Dunlop, J. S., et al. 2023, MNRAS, 518, 6011, doi: 10.1093/mnras/stac3472

  36. [36]

    T., McLure, R

    Donnan, C. T., McLure, R. J., Dunlop, J. S., et al. 2024, MNRAS, 533, 3222, doi: 10.1093/mnras/stae2037 Faucher-Gigu` ere, C.-A. 2020, MNRAS, 493, 1614, doi: 10.1093/mnras/staa302 Faucher-Gigu` ere, C.-A., Lidz, A., Zaldarriaga, M., &

  37. [37]

    2009, ApJ, 703, 1416, doi: 10.1088/0004-637X/703/2/1416

    Hernquist, L. 2009, ApJ, 703, 1416, doi: 10.1088/0004-637X/703/2/1416

  38. [38]

    2023, MNRAS, 522, 3831, doi: 10.1093/mnras/stad1205

    Feldmann, R., Quataert, E., Faucher-Gigu` ere, C.-A., et al. 2023, MNRAS, 522, 3831, doi: 10.1093/mnras/stad1205

  39. [39]

    S., et al

    Feldmann, R., Boylan-Kolchin, M., Bullock, J. S., et al. 2025, MNRAS, 536, 988, doi: 10.1093/mnras/stae2633

  40. [40]

    L., & Bagley, M

    Finkelstein, S. L., & Bagley, M. B. 2022, ApJ, 938, 25, doi: 10.3847/1538-4357/ac89eb

  41. [41]

    L., Bagley, M

    Finkelstein, S. L., Bagley, M. B., Ferguson, H. C., et al. 2023, ApJL, 946, L13, doi: 10.3847/2041-8213/acade4

  42. [42]

    L., Leung, G

    Finkelstein, S. L., Leung, G. C. K., Bagley, M. B., et al. 2024, ApJL, 969, L2, doi: 10.3847/2041-8213/ad4495 Flores Vel´ azquez, J. A., Gurvich, A. B., Faucher-Gigu` ere, C.-A., et al. 2021, MNRAS, 501, 4812, doi: 10.1093/mnras/staa3893

  43. [43]

    2024, dfm/emcee: v3.1.6, v3.1.6 Zenodo, doi: 10.5281/zenodo.10996751

    Foreman-Mackey, D., Meierjurgen Farr, W., Archibald, A., et al. 2024, dfm/emcee: v3.1.6, v3.1.6 Zenodo, doi: 10.5281/zenodo.10996751

  44. [44]

    2025a, Nature Astronomy, doi: 10.1038/s41550-025-02592-w

    Fujimoto, S., Ouchi, M., Kohno, K., et al. 2025a, Nature Astronomy, doi: 10.1038/s41550-025-02592-w

  45. [45]

    P., et al

    Fujimoto, S., Asada, Y., Naidu, R. P., et al. 2025b, arXiv e-prints, arXiv:2512.11790, doi: 10.48550/arXiv.2512.11790

  46. [46]

    1986, ApJ, 303, 336, doi: 10.1086/164079 Grudi´ c, M

    Gehrels, N. 1986, ApJ, 303, 336, doi: 10.1086/164079 Grudi´ c, M. Y., Guszejnov, D., Offner, S. S. R., et al. 2022, MNRAS, 512, 216, doi: 10.1093/mnras/stac526 Grudi´ c, M. Y., & Hopkins, P. F. 2020, MNRAS, 495, 4306, doi: 10.1093/mnras/staa1453 Grudi´ c, M. Y., Hopkins, P. F., Quataert, E., & Murray, N. 2019, MNRAS, 483, 5548, doi: 10.1093/mnras/sty3386

  47. [47]

    B., Stern, J., Faucher-Gigu` ere, C.-A., et al

    Gurvich, A. B., Stern, J., Faucher-Gigu` ere, C.-A., et al. 2023, MNRAS, 519, 2598, doi: 10.1093/mnras/stac3712

  48. [48]

    2011, MNRAS, 415, 2101, doi: 10.1111/j.1365-2966.2011.18820.x

    Hahn, O., & Abel, T. 2011, MNRAS, 415, 2101, doi: 10.1111/j.1365-2966.2011.18820.x

  49. [49]

    A., & Loeb, A

    Haiman, Z., Thoul, A. A., & Loeb, A. 1996, ApJ, 464, 523, doi: 10.1086/177343

  50. [50]

    2024, ApJ, 960, 56, doi: 10.3847/1538-4357/ad0b7e

    Harikane, Y., Nakajima, K., Ouchi, M., et al. 2024, ApJ, 960, 56, doi: 10.3847/1538-4357/ad0b7e

  51. [51]

    2022, ApJS, 259, 20, doi: 10.3847/1538-4365/ac3dfc

    Harikane, Y., Ono, Y., Ouchi, M., et al. 2022, ApJS, 259, 20, doi: 10.3847/1538-4365/ac3dfc

  52. [52]

    2023, ApJS, 265, 5, doi: 10.3847/1538-4365/acaaa9

    Harikane, Y., Ouchi, M., Oguri, M., et al. 2023, ApJS, 265, 5, doi: 10.3847/1538-4365/acaaa9

  53. [53]

    K., Ellis, R

    Harikane, Y., Inoue, A. K., Ellis, R. S., et al. 2025, ApJ, 980, 138, doi: 10.3847/1538-4357/ad9b2c

  54. [54]

    Harris and K

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

  55. [55]

    Hegde, S., & Furlanetto, S. R. 2025, The Open Journal of Astrophysics, 8, 147, doi: 10.33232/001c.145070 BonFIRE and CampFIRE41

  56. [56]

    M., Rieke, G

    Helton, J. M., Rieke, G. H., Alberts, S., et al. 2025, Nature Astronomy, 9, 729, doi: 10.1038/s41550-025-02503-z

  57. [57]

    2019, Frontiers in Astronomy and Space Sciences, 6, 5, doi: 10.3389/fspas.2019.00005

    Hennebelle, P., & Inutsuka, S.-i. 2019, Frontiers in Astronomy and Space Sciences, 6, 5, doi: 10.3389/fspas.2019.00005

  58. [58]

    Hopkins, P. F. 2015, MNRAS, 450, 53, doi: 10.1093/mnras/stv195

  59. [59]

    F., Kereˇ s, D., O˜ norbe, J., et al

    Hopkins, P. F., Kereˇ s, D., O˜ norbe, J., et al. 2014, MNRAS, 445, 581, doi: 10.1093/mnras/stu1738

  60. [60]

    F., Nadler, E

    Hopkins, P. F., Nadler, E. O., Grudi´ c, M. Y., et al. 2023a, MNRAS, 525, 5951, doi: 10.1093/mnras/stad2548

  61. [61]

    F., Wetzel, A., Kereˇ s, D., et al

    Hopkins, P. F., Wetzel, A., Kereˇ s, D., et al. 2018, MNRAS, 480, 800, doi: 10.1093/mnras/sty1690

  62. [62]

    F., Wetzel, A., Wheeler, C., et al

    Hopkins, P. F., Wetzel, A., Wheeler, C., et al. 2023b, MNRAS, 519, 3154, doi: 10.1093/mnras/stac3489

  63. [63]

    F., Gurvich, A

    Hopkins, P. F., Gurvich, A. B., Shen, X., et al. 2023c, MNRAS, 525, 2241, doi: 10.1093/mnras/stad1902

  64. [64]

    Hunter, J. D. 2007, Computing in Science and Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

  65. [65]

    L., & Bromm, V

    Jaacks, J., Finkelstein, S. L., & Bromm, V. 2019, MNRAS, 488, 2202, doi: 10.1093/mnras/stz1529

  66. [66]

    L., & Bromm, V

    Jaacks, J., Thompson, R., Finkelstein, S. L., & Bromm, V. 2018, MNRAS, 475, 4396, doi: 10.1093/mnras/sty062

  67. [67]

    B., Jeon, M., Song, H., & Bromm, V

    Jeong, T. B., Jeon, M., Song, H., & Bromm, V. 2025, ApJ, 980, 10, doi: 10.3847/1538-4357/ada27d

  68. [68]

    2022, MNRAS, 511, 4005, doi: 10.1093/mnras/stab3710

    Kannan, R., Garaldi, E., Smith, A., et al. 2022, MNRAS, 511, 4005, doi: 10.1093/mnras/stab3710

  69. [69]

    2013, Reviews of Modern Physics, 85, 809, doi: 10.1103/RevModPhys.85.809

    Karlsson, T., Bromm, V., & Bland-Hawthorn, J. 2013, Reviews of Modern Physics, 85, 809, doi: 10.1103/RevModPhys.85.809

  70. [70]

    S., Rose, C., Vanderhoof, B

    Kartaltepe, J. S., Rose, C., Vanderhoof, B. N., et al. 2023, ApJL, 946, L15, doi: 10.3847/2041-8213/acad01

  71. [71]

    S., Devriendt, J., & Slyz, A

    Katz, H., Kimm, T., Ellis, R. S., Devriendt, J., & Slyz, A. 2023a, MNRAS, 524, 351, doi: 10.1093/mnras/stad1903

  72. [72]

    2023b, The Open Journal of Astrophysics, 6, 44, doi: 10.21105/astro.2309.03269

    Katz, H., Rosdahl, J., Kimm, T., et al. 2023b, The Open Journal of Astrophysics, 6, 44, doi: 10.21105/astro.2309.03269

  73. [73]

    P., Cadiou, C., et al

    Katz, H., Rey, M. P., Cadiou, C., et al. 2025, arXiv e-prints, arXiv:2510.05201, doi: 10.48550/arXiv.2510.05201

  74. [74]

    W., Munshi, F., Trebitsch, M., & Tremmel, M

    Keller, B. W., Munshi, F., Trebitsch, M., & Tremmel, M. 2023, ApJL, 943, L28, doi: 10.3847/2041-8213/acb148

  75. [75]

    S., Moreno, J., et al

    Klein, C., Bullock, J. S., Moreno, J., et al. 2024, MNRAS, 532, 538, doi: 10.1093/mnras/stae1505

  76. [76]

    S., & Glover, S

    Klessen, R. S., & Glover, S. C. O. 2023, ARA&A, 61, 65, doi: 10.1146/annurev-astro-071221-053453

  77. [77]

    2025, ApJL, 983, L22, doi: 10.3847/2041-8213/adc458

    Kokorev, V., Atek, H., Chisholm, J., et al. 2025, ApJL, 983, L22, doi: 10.3847/2041-8213/adc458

  78. [78]

    Kruijssen, J. M. D. 2026, in Encyclopedia of Astrophysics, Volume 4, Vol. 4, 500–534, doi: 10.1016/B978-0-443-21439-4.00078-X Labb´ e, I., van Dokkum, P., Nelson, E., et al. 2023, Nature, 616, 266, doi: 10.1038/s41586-023-05786-2

  79. [79]

    Leung, G. C. K., Bagley, M. B., Finkelstein, S. L., et al. 2023, ApJL, 954, L46, doi: 10.3847/2041-8213/acf365

  80. [80]

    C., et al

    Li, Z., Dekel, A., Sarkar, K. C., et al. 2024, A&A, 690, A108, doi: 10.1051/0004-6361/202348727

Showing first 80 references.