pith. machine review for the scientific record. sign in

arxiv: 2605.13982 · v1 · submitted 2026-05-13 · 🌌 astro-ph.GA

Recognition: 2 theorem links

· Lean Theorem

Lyman-alpha Radiation Pressure in Dense Star Clusters: Implications for Star Formation and Winds at Cosmic Dawn

Authors on Pith no claims yet

Pith reviewed 2026-05-15 02:16 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords alphastarodotradiationformationpressurecosmicdawn
0
0 comments X

The pith

Lyα radiation pressure mildly reduces gas-to-star conversion efficiency in dense high-redshift clusters while dominating the launch of rapid outflows.

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

The study takes snapshots from simulations of very dense star-forming clouds where stars form at rates over 1000 solar masses per square parsec. These clouds have low dust levels typical of the early universe. Using a Monte Carlo code called COLT, the authors calculate how Lyman-alpha photons scatter and push on the gas. In regions with even a little dust, the pressure changes the fraction of gas turned into stars by only about 10 percent, keeping efficiencies above 60 percent. Even with no dust at all, efficiencies stay above 25 percent, much higher than in nearby galaxies. The densest gas filaments where most stars assemble stay below the limit where radiation can push them apart. But the more spread-out gas experiences strong pushing, with some parts pushed ten times harder than gravity, allowing winds to form in under 4 million years. Lyman-alpha pressure is several times to hundreds of times stronger than ultraviolet or infrared pressure in these settings. The force multiplier depends strongly on dust content.

Core claim

Lyα is likely to have mild (~10%) effects on the gas-to-star conversion efficiencies (ε* ≳60%) for Zd ≳0.01 Zd,⊙, and even in dust-free environments, ε* ≳25% - much higher than the <10% values typical of star-forming regions in the local Universe.

Load-bearing premise

The post-processed simulation snapshots accurately capture the density and velocity structure of real dense filaments (n ≳ 10^4 cm^{-3}) such that they remain sub-Eddington under Lyα radiation.

Figures

Figures reproduced from arXiv: 2605.13982 by Aaron Smith, Shyam H Menon.

Figure 1
Figure 1. Figure 1: Time evolution of relevant quantities in the simulation, shown at representative times spanning the early embedded phase through the later, feedback-dominated evolution. Each column corresponds to a different snapshot time (increasing from left to right). From top to bottom we show: the projected gas surface density, Σgas; the mass-weighted projected average of the hydrogen ionization fraction, ⟨xH+ ⟩m; th… view at source ↗
Figure 2
Figure 2. Figure 2: Mass-weighted projections of the ratio of the magnitude of the acceleration due to Lyα radiation pressure (aLyα) and due to the stellar and self-gravitational potential (agrav) at different times (columns), and for the four different dust abundances explored in this study (rows). We can clearly see that over time, as gas gets consumed by star formation and ejected by radiative feedback physics included in … view at source ↗
Figure 3
Figure 3. Figure 3: The potential impact of Lyα radiation pressure on the global competition between feedback and star formation. Left: Lines show the total stellar mass formed (M⋆; blue), remaining gas mass (Mgas; orange), and the mass ejected by radiative feedback physics included in the simulation (Mejected; green), all normalized to the initial cloud mass (Mcloud = 106 M⊙), as a function of the age of the stellar populati… view at source ↗
Figure 5
Figure 5. Figure 5: Distributions of the Lyα Eddington ratio, fEdd (Equation 3), shown as the cumulative fraction of Mcloud with fEdd greater than a given value at the time t⋆ = 0.83 Myr where the dust-free case peaks in [PITH_FULL_IMAGE:figures/full_fig_p010_5.png] view at source ↗
Figure 4
Figure 4. Figure 4: Main Panel: Mean value of the Eddington ratio (Equation 3) for gas at a number density (n) for the differ￾ent dust treatments at the time t⋆ = 0.83 Myr. We can see that ⟨fEdd⟩ decreases at the low n ≲ 10 cm−3 due to their lower optical depths, and more noticeably so for high n due to its stronger gravity, with higher dust abundance reflect￾ing in a transition from super- to sub-Eddington at lower n. Top-mi… view at source ↗
Figure 6
Figure 6. Figure 6: The Lyα force multiplier (Equation 4; left) and the Lyα and dust radiation pressure forces normalised to LUV/c (right) as a function of the age of the stellar population (t⋆). We can see that MF depends sensitively on the dust abundance, and decreases with time as the gas column in the cloud decreases ( [PITH_FULL_IMAGE:figures/full_fig_p012_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Plot quantifying the potential impact of Lyα radiation pressure on stellar growth using a semi-analytic model(Appendix C) informed by insights from our calculations. Left: The integrated efficiency of star formation (ϵ∗ = M⋆/Mcloud) for the different dust abundances relative to the case without Lyα radiation pressure (unfilled marker), with the parallel y-axis indicating the corresponding absolute value ap… view at source ↗
Figure 8
Figure 8. Figure 8: Distributions of the Lyα Eddington ratio, fEdd (Equation 3), shown as the cumulative fraction of Mcloud with fEdd greater than a given value at the time t⋆ = 0.83 Myr for the dust-free case. The four lines cor￾respond to different choices for how fEdd is calculated, as described in the text of Section A. Overall, we find that the different methods agree to within a factor ∼ 2 to our fiducial choice (green … view at source ↗
Figure 9
Figure 9. Figure 9: Distributions of the Lyα Eddington ratio, fEdd (Equation 3), shown as the cumulative fraction of Mcloud with fEdd greater than a given value at the time t⋆ = 0.83 Myr for the Zd = 0.01 Zd,⊙ case. Colors show the implications of the number of MC photons (nph) used to sample the radiation field, and linestyles show different choices of xcrit. We can see that our fiducial case (nph = 106 , xcrit = 2; blue sol… view at source ↗
read the original abstract

Observations with the JWST in lensed fields have revealed that galaxies at cosmic dawn may concentrate their star formation in highly dense, compact, star clusters. The high columns and low metallicities encountered in their birth environments suggest that Lyman-alpha (Ly$\alpha$) radiation pressure may be crucial to their formation and evolution. In this study, we address this question by post-processing snapshots from radiation hydrodynamic simulations of dense star cluster-forming clouds ($\Sigma_*\gtrsim10^3{M_\odot{pc}^{-2}}$) with a range of dust abundances ($Z_d=0-0.1Z_{d,\odot}$) using the COLT Monte Carlo code. We infer that Ly$\alpha$ is likely to have mild (~10%) effects on the gas-to-star conversion efficiencies ($\epsilon_*\gtrsim60$%) for $Z_d\gtrsim0.01Z_{d,\odot}$, and even in dust-free environments, $\epsilon_*\gtrsim25$% - much higher than the <10% values typical of star-forming regions in the local Universe. This is because the densest filaments dominating stellar mass assembly ($n\gtrsim10^4{cm}^{-3}$) remain sub-Eddington ($f_{Edd}<1$). On the other hand, the bulk of the gas volume ($n\lesssim10^3{cm}^{-3}$) has $f_{Edd}>1$, with noticeable fractions having $f_{Edd}\gtrsim10$, implying that Ly$\alpha$ can launch dynamically significant winds from these systems rapidly ($\lesssim$4Myr), with possible implications for ionizing photon escape and galactic outflows. The Ly$\alpha$ force multiplier $M_F$ is highly sensitive to $Z_d$, with $M_F\lesssim3$ ($\lesssim 500$) for $0.1Z_{d,\odot}$ (dust-free) environments respectively. Nevertheless, Ly$\alpha$ dominates over UV and IR radiation pressure at all values of $Z_d\lesssim0.1Z_{d,\odot}$, by factors of ~3-500. Our results suggest that Ly$\alpha$ radiation pressure reinforces the emerging picture of locally efficient, bursty star formation accompanied by rapid outflows in galaxies at cosmic dawn.

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 post-processes radiation-hydrodynamic simulation snapshots of dense star cluster formation (Σ* ≳ 10^3 M⊙ pc^{-2}) with the COLT Monte Carlo code to quantify Lyman-alpha radiation pressure effects across dust abundances Zd = 0–0.1 Zd,⊙. It claims that Lyα has only mild (~10%) impact on gas-to-star conversion efficiencies (ε* ≳ 60% for Zd ≳ 0.01 Zd,⊙ and ≳ 25% dust-free) because the densest filaments (n ≳ 10^4 cm^{-3}) remain sub-Eddington (f_Edd < 1), while lower-density gas (n ≲ 10^3 cm^{-3}) has f_Edd > 1 and can drive rapid winds; Lyα dominates UV/IR pressure by factors of 3–500.

Significance. If the quantitative trends hold, the work supplies useful constraints on star-formation efficiencies and outflow launching in compact high-redshift clusters, reinforcing the emerging picture of locally efficient yet bursty star formation at cosmic dawn and offering direct implications for JWST observations of lensed galaxies. The Monte Carlo post-processing approach on existing snapshots is a clear methodological strength that enables detailed force-multiplier calculations without requiring new full radiation-hydrodynamic runs.

major comments (1)
  1. [Abstract and f_Edd results] Abstract and § on f_Edd results: the central claim that dense filaments (n ≳ 10^4 cm^{-3}) remain sub-Eddington (f_Edd < 1) and therefore suppress ε* by only ~10% rests on density and velocity fields taken from snapshots generated without the Lyα force term. Because the reported force multipliers reach M_F ≲ 3–500, modest changes in velocity gradients can alter resonant trapping times and push local f_Edd above unity, potentially lowering ε* more than stated; no convergence tests on filament resolution or sensitivity of f_Edd to the assumed velocity structure are provided.
minor comments (2)
  1. [Abstract] The abstract and results text report clear trends with Zd but omit explicit error bars, full parameter tables, or convergence metrics for the quoted ε* and f_Edd values, which would aid verification of the quantitative numbers.
  2. [Throughout] Notation for dust abundance (Zd vs. Z_d) and force multiplier (M_F) should be made fully consistent between text, figures, and tables.

Axiom & Free-Parameter Ledger

1 free parameters · 2 axioms · 0 invented entities

The central claim depends on the fidelity of pre-existing radiation-hydrodynamic snapshots and the accuracy of the COLT Monte Carlo treatment of Lyα scattering in dusty media; no new entities are postulated.

free parameters (1)
  • dust abundance Z_d = 0-0.1 Z_d,⊙
    Explored parametrically from 0 to 0.1 solar to test sensitivity; values are chosen rather than fitted to new data.
axioms (2)
  • domain assumption Radiation-hydrodynamic simulation snapshots provide representative density, velocity, and ionization structures for dense cluster-forming clouds.
    Paper relies on prior snapshots without re-deriving the hydrodynamics.
  • domain assumption COLT Monte Carlo radiative transfer accurately computes the Lyα force multiplier and Eddington ratio in the specified density and metallicity range.
    Standard assumption for the post-processing code.

pith-pipeline@v0.9.0 · 5723 in / 1473 out tokens · 53773 ms · 2026-05-15T02:16:29.241283+00:00 · methodology

discussion (0)

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

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

166 extracted references · 166 canonical work pages · 2 internal anchors

  1. [1]

    L., Coe, D., et al

    Abdurro’uf, Larson, R. L., Coe, D., et al. 2024, ApJ, 973, 47, doi: 10.3847/1538-4357/ad6001

  2. [2]

    D., Vanzella, E., et al

    Adamo, A., Bradley, L. D., Vanzella, E., et al. 2024, arXiv e-prints, arXiv:2401.03224, doi: 10.48550/arXiv.2401.03224

  3. [3]

    Adams, T. F. 1975, ApJ, 201, 350, doi: 10.1086/153891 Ad´ ela¨ ıde, C., Angela, A., Vasily, K., et al. 2026, A first GLIMPSE into star clusters populations across cosmic time, arXiv, doi: 10.48550/arXiv.2601.16281

  4. [4]

    Ahn, S.-H., Lee, H.-W., & Lee, H. M. 2002, The Astrophysical Journal, 567, 922, doi: 10.1086/338497 Amor´ ın, R. O., Rodr´ ıguez-Henr´ ıquez, M., Fern´ andez, V., et al. 2024, A&A, 682, L25, doi: 10.1051/0004-6361/202449175

  5. [5]

    D., McInnes, L

    Balay, S., Gropp, W. D., McInnes, L. C., & Smith, B. F. 1997, in Modern Software Tools in Scientific Computing, ed. E. Arge, A. M. Bruaset, & H. P. Langtangen (Birkh¨ auser Press), 163–202

  6. [6]

    F., et al

    Balay, S., Abhyankar, S., Adams, M. F., et al. 2021, PETSc/TAO Users Manual, Tech. Rep. ANL-21/39 - Revision 3.16, Argonne National Laboratory

  7. [7]

    , keywords =

    Baumgardt, H., & Kroupa, P. 2007, MNRAS, 380, 1589, doi: 10.1111/j.1365-2966.2007.12209.x

  8. [8]

    C., Turner, J

    Beck, S. C., Turner, J. L., Zweig, E., et al. 2025, arXiv e-prints, arXiv:2511.09911, doi: 10.48550/arXiv.2511.09911

  9. [9]

    1990, MNRAS, 244, 738

    Bithell, M. 1990, MNRAS, 244, 738

  10. [10]

    Noerdlinger, P. D. 1979, ApJ, 233, 649, doi: 10.1086/157426

  11. [11]

    2018, ApJ, 861, 80, doi: 10.3847/1538-4357/aac824

    Camps, P., & Baes, M. 2018, ApJ, 861, 80, doi: 10.3847/1538-4357/aac824

  12. [12]

    2025, A&A, 696, A87, doi: 10.1051/0004-6361/202452451

    Carniani, S., D’Eugenio, F., Ji, X., et al. 2025, A&A, 696, A87, doi: 10.1051/0004-6361/202452451

  13. [13]

    A., Cen, R., Scarlata, C., et al

    Carr, C. A., Cen, R., Scarlata, C., et al. 2024, arXiv e-prints, arXiv:2409.05180, doi: 10.48550/arXiv.2409.05180

  14. [14]

    M., Akins, H

    Casey, C. M., Akins, H. B., Shuntov, M., et al. 2023, arXiv e-prints, arXiv:2308.10932, doi: 10.48550/arXiv.2308.10932

  15. [15]

    2024, ApJ, 972, 143, doi: 10.3847/1538-4357/ad5f88

    Castellano, M., Napolitano, L., Fontana, A., et al. 2024, ApJ, 972, 143, doi: 10.3847/1538-4357/ad5f88

  16. [16]

    I., Abbott, D

    Castor, J. I., Abbott, D. C., & Klein, R. I. 1975, ApJ, 195, 157, doi: 10.1086/153315

  17. [17]

    H., Burkhart, B., et al

    Chen, A., Menon, S. H., Burkhart, B., et al. 2026, arXiv e-prints, arXiv:2604.00197, doi: 10.48550/arXiv.2604.00197

  18. [18]

    R., McLeod, A

    Chevance, M., Krumholz, M. R., McLeod, A. F., et al. 2023, in Astronomical Society of the Pacific Conference

  19. [19]

    534, Protostars and Planets VII, ed

    Series, Vol. 534, Protostars and Planets VII, ed. S. Inutsuka, Y. Aikawa, T. Muto, K. Tomida, & M. Tamura, 1, doi: 10.48550/arXiv.2203.09570

  20. [20]

    2023, arXiv e-prints, arXiv:2312.13339, doi: 10.48550/arXiv.2312.13339

    Chon, S., Hosokawa, T., Omukai, K., & Schneider, R. 2023, arXiv e-prints, arXiv:2312.13339, doi: 10.48550/arXiv.2312.13339

  21. [21]

    A first GLIMPSE into star clusters popula- tions across cosmic time

    Claeyssens, A., Adamo, A., Kokorev, V., et al. 2026, arXiv e-prints, arXiv:2601.16281, doi: 10.48550/arXiv.2601.16281 Crespo G´ omez, A., Tamura, Y., Colina, L., et al. 2025, arXiv e-prints, arXiv:2511.14658, doi: 10.48550/arXiv.2511.14658 23

  22. [22]

    2023, arXiv e-prints, arXiv:2304.08516, doi: 10.48550/arXiv.2304.08516 De Vis, P., Jones, A., Viaene, S., et al

    Curti, M., Maiolino, R., Curtis-Lake, E., et al. 2023, arXiv e-prints, arXiv:2304.08516, doi: 10.48550/arXiv.2304.08516 De Vis, P., Jones, A., Viaene, S., et al. 2019, A&A, 623, A5, doi: 10.1051/0004-6361/201834444

  23. [23]

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

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

  24. [24]

    2008, , 385, 1053, 10.1111/j.1365-2966.2008.12909.x

    Dijkstra, M., & Loeb, A. 2008, Monthly Notices of the Royal Astronomical Society, 391, 457, doi: 10.1111/j.1365-2966.2008.13920.x

  25. [25]

    B., & Fisher, R

    Dubey, A., Reid, L. B., & Fisher, R. 2008, Physica Scripta Volume T, 132, 014046, doi: 10.1088/0031-8949/2008/T132/014046

  26. [26]

    Weisz, D. R. 2019, MNRAS, 490, 1961, doi: 10.1093/mnras/stz2773

  27. [27]

    J., Stanway, E

    Eldridge, J. J., Stanway, E. R., Xiao, L., et al. 2017, PASA, 34, e058, doi: 10.1017/pasa.2017.51

  28. [28]

    M., Krumholz, M

    Fall, S. M., Krumholz, M. R., & Matzner, C. D. 2010, Astrophysical Journal Letters, 710, L142, doi: 10.1088/2041-8205/710/2/L142

  29. [29]

    C., & Klessen, R

    Federrath, C., Banerjee, R., Clark, P. C., & Klessen, R. S. 2010a, ApJ, 713, 269, doi: 10.1088/0004-637X/713/1/269

  30. [30]

    Klessen, R. S. 2011, in IAU Symposium, Vol. 270, Computational Star Formation, ed. J. Alves, B. G

  31. [31]

    Elmegreen, J. M. Girart, & V. Trimble, 425–428, doi: 10.1017/S1743921311000755

  32. [32]

    Federrath, C., & Klessen, R. S. 2012, ApJ, 761, 156, doi: 10.1088/0004-637X/761/2/156

  33. [33]

    S., Iapichino, L., & Beattie, J

    Federrath, C., Klessen, R. S., Iapichino, L., & Beattie, J. R. 2021, Nature Astronomy, 5, 365, doi: 10.1038/s41550-020-01282-z

  34. [34]

    S., & Schmidt, W

    Federrath, C., Klessen, R. S., & Schmidt, W. 2008, ApJL, 688, L79, doi: 10.1086/595280

  35. [35]

    S., Schmidt, W., & Mac Low, M

    Federrath, C., Roman-Duval, J., Klessen, R. S., Schmidt, W., & Mac Low, M. M. 2010b, A&A, 512, A81, doi: 10.1051/0004-6361/200912437

  36. [36]

    S., Schmidt, W., & Mac Low, M.-M

    Federrath, C., Roman-Duval, J., Klessen, R. S., Schmidt, W., & Mac Low, M.-M. 2022, TG: Turbulence Generator,, Astrophysics Source Code Library, record ascl:2204.001 http://ascl.net/2204.001

  37. [37]

    2023, arXiv e-prints, arXiv:2310.12197, doi: 10.48550/arXiv.2310.12197

    Ferrara, A. 2023, arXiv e-prints, arXiv:2310.12197, doi: 10.48550/arXiv.2310.12197

  38. [38]

    2023, MNRAS, 522, 3986, doi: 10.1093/mnras/stad1095

    Ferrara, A., Pallottini, A., & Dayal, P. 2023, MNRAS, 522, 3986, doi: 10.1093/mnras/stad1095

  39. [39]

    2018, MNRAS, 481, 3325, doi: 10.1093/mnras/sty2466

    Fielding, D., Quataert, E., & Martizzi, D. 2018, MNRAS, 481, 3325, doi: 10.1093/mnras/sty2466

  40. [40]

    2017, MNRAS, 470, L39, doi: 10.1093/mnrasl/slx072

    Fielding, D., Quataert, E., Martizzi, D., & Faucher-Gigu` ere, C.-A. 2017, MNRAS, 470, L39, doi: 10.1093/mnrasl/slx072

  41. [41]

    L., Leung, G

    Finkelstein, S. L., Leung, G. C. K., Bagley, M. B., et al. 2023, arXiv e-prints, arXiv:2311.04279, doi: 10.48550/arXiv.2311.04279

  42. [42]

    2000, ApJS, 131, 273, doi: 10.1086/317361

    Fryxell, B., Olson, K., Ricker, P., et al. 2000, ApJS, 131, 273, doi: 10.1086/317361

  43. [43]

    2021, MNRAS, 506, 5512, doi: 10.1093/mnras/stab2099

    Fukushima, H., & Yajima, H. 2021, MNRAS, 506, 5512, doi: 10.1093/mnras/stab2099

  44. [44]

    and others , year=

    Gardner, J. P., Mather, J. C., Abbott, R., et al. 2023, PASP, 135, 068001, doi: 10.1088/1538-3873/acd1b5

  45. [45]

    Gelli, V., Mason, C., & Hayward, C. C. 2024, ApJ, 975, 192, doi: 10.3847/1538-4357/ad7b36

  46. [46]

    S., Krumholz, M

    Gentry, E. S., Krumholz, M. R., Dekel, A., & Madau, P. 2017, MNRAS, 465, 2471, doi: 10.1093/mnras/stw2746

  47. [47]

    C., & Wolfire, M

    Gong, M., Ostriker, E. C., & Wolfire, M. G. 2017, ApJ, 843, 38, doi: 10.3847/1538-4357/aa7561 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., Faucher-Gigu` ere, C.-A., et al. 2018, MNRAS, 475, 3511, doi: 10.1093/mnras/sty035

  48. [48]

    2022, ApJ, 935, 53, doi: 10.3847/1538-4357/ac7ff3

    Han, D., Kimm, T., Katz, H., Devriendt, J., & Slyz, A. 2022, ApJ, 935, 53, doi: 10.3847/1538-4357/ac7ff3

  49. [49]

    Hansen, M., & Oh, S. P. 2006, MNRAS, 367, 979, doi: 10.1111/j.1365-2966.2005.09870.x

  50. [50]

    R., Millman, 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

  51. [51]

    2019, MNRAS, 489, 1880, doi: 10.1093/mnras/stz2239

    He, C.-C., Ricotti, M., & Geen, S. 2019, MNRAS, 489, 1880, doi: 10.1093/mnras/stz2239

  52. [52]

    2014, A&A, 570, A81, doi: 10.1051/0004-6361/201423392

    Hennebelle, P., & Iffrig, O. 2014, A&A, 570, A81, doi: 10.1051/0004-6361/201423392

  53. [53]

    2019, MNRAS, 482, 2555, doi: 10.1093/mnras/sty2838

    Hirashita, H., & Aoyama, S. 2019, MNRAS, 482, 2555, doi: 10.1093/mnras/sty2838

  54. [54]

    Hosokawa, T., Omukai, K., Yoshida, N., & Yorke, H. W. 2011, Science, 334, 1250, doi: 10.1126/science.1207433

  55. [55]

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

  56. [56]

    K., Li, W., & Ho, L

    Inayoshi, K., Harikane, Y., Inoue, A. K., Li, W., & Ho, L. C. 2022, ApJL, 938, L10, doi: 10.3847/2041-8213/ac9310

  57. [57]

    2023, ApJ, 956, 139, doi: 10.3847/1538-4357/acf376

    Isobe, Y., Ouchi, M., Nakajima, K., et al. 2023, ApJ, 956, 139, doi: 10.3847/1538-4357/acf376

  58. [58]

    Jaskot, A. E. 2025, ARA&A, 63, 45, doi: 10.1146/annurev-astro-111324-074935

  59. [59]

    Jaura, O., Glover, S. C. O., Wollenberg, K. M. J., et al. 2022, MNRAS, 512, 116, doi: 10.1093/mnras/stac487

  60. [60]

    U., Baes, M., van der Wel, A., et al

    Kapoor, A. U., Baes, M., van der Wel, A., et al. 2023, MNRAS, 526, 3871, doi: 10.1093/mnras/stad2977 24

  61. [61]

    2026, ApJ, 996, 103, doi: 10.3847/1538-4357/ae1f8b

    Kar, A., Alam, S., & Silk, J. 2026, ApJ, 996, 103, doi: 10.3847/1538-4357/ae1f8b

  62. [62]

    Kim, C.-G., & Ostriker, E. C. 2015, ApJ, 802, 99, doi: 10.1088/0004-637X/802/2/99

  63. [63]

    Kim, J.-G., Gong, M., Kim, C.-G., & Ostriker, E. C. 2023, ApJS, 264, 10, doi: 10.3847/1538-4365/ac9b1d

  64. [64]

    Kim, J.-G., Kim, W.-T., & Ostriker, E. C. 2018, ApJ, 859, 68, doi: 10.3847/1538-4357/aabe27

  65. [65]

    C., & Skinner, M

    Kim, J.-G., Kim, W.-T., Ostriker, E. C., & Skinner, M. A. 2017, ApJ, 851, 93, doi: 10.3847/1538-4357/aa9b80

  66. [66]

    C., & Filippova, N

    Kim, J.-G., Ostriker, E. C., & Filippova, N. 2021, ApJ, 911, 128, doi: 10.3847/1538-4357/abe934

  67. [67]

    J., Bayliss, M

    Kim, K. J., Bayliss, M. B., Rigby, J. R., et al. 2023, ApJL, 955, L17, doi: 10.3847/2041-8213/acf0c5

  68. [68]

    2018, Monthly Notices of the Royal Astronomical Society, 475, 4617, doi: 10.1093/mnras/sty126

    Kimm, T., Haehnelt, M., Blaizot, J., et al. 2018, Monthly Notices of the Royal Astronomical Society, 475, 4617, doi: 10.1093/mnras/sty126

  69. [69]

    S., & Glover, S

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

  70. [70]

    S., Krumholz, M

    Komarova, L., Oey, M. S., Krumholz, M. R., et al. 2021, ApJL, 920, L46, doi: 10.3847/2041-8213/ac2c09

  71. [71]

    S., Hernandez, S., et al

    Komarova, L., Oey, M. S., Hernandez, S., et al. 2024, ApJ, 967, 117, doi: 10.3847/1538-4357/ad3962

  72. [72]

    2024, arXiv e-prints, arXiv:2405.04578, doi: 10.48550/arXiv.2405.04578

    Kravtsov, A., & Belokurov, V. 2024, arXiv e-prints, arXiv:2405.04578, doi: 10.48550/arXiv.2405.04578

  73. [73]

    Krumholz, M. R. 2018, MNRAS, 480, 3468, doi: 10.1093/mnras/sty2105

  74. [74]

    R., & Matzner, C

    Krumholz, M. R., & Matzner, C. D. 2009, Astrophysical Journal, 703, 1352, doi: 10.1088/0004-637X/703/2/1352

  75. [75]

    R., Matzner, C

    Krumholz, M. R., Matzner, C. D., & McKee, C. F. 2006, ApJ, 653, 361, doi: 10.1086/508679

  76. [76]

    R., & Thompson, T

    Krumholz, M. R., & Thompson, T. A. 2012, ApJ, 760, 155, doi: 10.1088/0004-637X/760/2/155

  77. [77]

    R., & Thompson, T

    Krumholz, M. R., & Thompson, T. A. 2013, Monthly Notices of the Royal Astronomical Society, 434, 2329, doi: 10.1093/mnras/stt1174

  78. [78]

    Bryan, G. L. 2025, ApJ, 989, 43, doi: 10.3847/1538-4357/ade66c

  79. [79]

    Bryan, G. L. 2024, ApJ, 970, 18, doi: 10.3847/1538-4357/ad47f6

  80. [80]

    C., Kim, J.-G., & Kim, C.-G

    Lancaster, L., Ostriker, E. C., Kim, J.-G., & Kim, C.-G. 2021a, ApJL, 922, L3, doi: 10.3847/2041-8213/ac3333

Showing first 80 references.