Pith. sign in

REVIEW 4 major objections 5 minor 64 references

The ionizing photon budget and effective clumping factor in radiative transfer simulations calibrated to Lyman-alpha forest data

T0 review · 4 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

Pith's one-line read Simulations calibrated to Lyman-alpha forest data show that the JWST ionizing photon budget is consistent with reionization ending as late as z ≈ 5.5, with escape fractions of 5% (z=6) to 15–30% (z=10) and clumping factors of 3–6.

desk verdict Plausible, well-calibrated resolution of the reionization photon budget crisis, but the clumping-factor consistency is partly built into the simulation and resolution limits could bias both f_esc and C_R low. read the letter →

arxiv 2412.01906 v1 pith:HW3J7XHG submitted 2024-12-02 astro-ph.CO

classification astro-ph.CO
keywords reionizationionizingphotonbudgetescapefractionclumpingfactorLyman-alphaforestradiativetransfersimulationshigh-redshiftgalaxiesJWST
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

Recent JWST measurements of the ionizing photon production efficiency of high-redshift galaxies seemed to leave too many ionizing photons for reionization to end as late as the Lyman-alpha forest indicates, a mismatch known as the photon budget crisis. This paper argues that the tension disappears once the ionizing emissivity is assigned to haloes and calibrated to Lyman-alpha forest data in full radiative transfer simulations. In their fiducial model, the inferred escape fraction grows from about 5% at $z=6$ to 15–30% at $z=10$, consistent with extrapolations of lower-redshift measurements. The effective clumping factor needed to balance the budget is 3–6, far below the value near 15 suggested in a recent data-driven analysis, and a source model in which only bright galaxies emit ionizing photons is disfavored because it would require escape fractions above 50% at $z>10$.

What carries the argument

The central object is the mapping from ionizing emissivity to UV luminosity, $L_{\rm UV} = \dot{N}_{\rm ion}/(f_{\rm esc}\,\xi_{\rm ion})$, which lets the simulations convert their calibrated emissivity into a UV luminosity function. Fitting that luminosity function to observations at each redshift fixes the product $f_{\rm esc}\,\xi_{\rm ion}$; dividing by the JWST-measured $\xi_{\rm ion}$ from Simmonds et al. (2024a) yields the escape fraction. The effective clumping factor is inferred by substituting the simulation's emissivity, gas density, and ionized fraction into the Madau et al. (1999) evolution equation for the volume filling factor $Q_{\rm HII}$ and solving for $C_R$. The simulations themselves use ATON-HE, a GPU-based radiative transfer code, post-processing cosmological hydrodynamical simulations with the total ionizing emissivity tuned to match the mean Lyman-$\alpha$ forest transmission at $5<z<6.2$.

What would settle it

A measurement of the escape fraction for a representative sample of $z\approx 10$ galaxies that found values near 50% rather than 15–30%, or a data-driven clumping factor derived from Lyman-$\alpha$ forest data using Case A recombination and $\alpha_\lambda=3$ that still exceeded 10 at $z\approx 5.5$, would contradict the paper's central claims.

Watch

Extended reading notes

Core claim

The paper's central claim is that the photon budget crisis does not exist: the ionizing emissivity implied by JWST $\xi_{\rm ion}$ measurements, when paired with escape fractions that rise from roughly 5% at $z=6$ to 15–30% at $z=10$, is exactly what is needed to complete reionization by $z\approx 5.5$ as demanded by Lyman-$\alpha$ forest data. The authors further claim that the effective clumping factor in their simulations is 3–6, not the value as high as 15 inferred by Davies et al. (2024) from the same forest data, and they trace the discrepancy to two modelling choices: Case A rather than Case B recombination coefficients, and a frequency scaling of the ionizing mean free path with $\alpha_\lambda=3$ rather than 1. Finally, they claim that the 'oligarchic' source model, where faint galaxies do not emit ionizing photons, is disfavored at $z>10$ because it forces escape fractions above 50%.

Load-bearing premise

The analysis assumes that the product $f_{\rm esc}\,\xi_{\rm ion}$ is the same for all halo masses at a given redshift, so a single value fit to the UV luminosity function applies to all ionizing sources; if escape fractions or $\xi_{\rm ion}$ vary systematically with galaxy mass, the inferred evolution and the disfavouring of the oligarchic model could change.

Editorial extensions

If this is right

  • If correct, the photon budget crisis is resolved: JWST-era $\xi_{\rm ion}$ measurements do not require an unusually high clumping factor or an extremely early end to reionization.
  • The inferred escape fraction evolution (about 5% at $z=6$ rising to 15–30% at $z=10$) becomes a target for galaxy-scale simulations and for direct searches for Lyman-continuum leakage at high redshift.
  • The oligarchic model, where only massive galaxies emit ionizing photons, is disfavored at $z>10$, implying that faint galaxies must contribute substantially to the ionizing photon budget early in reionization.
  • The effective clumping factor of 3–6 is considerably lower than the value near 15 from Davies et al. (2024); accounting for Case A recombination and $\alpha_\lambda=3$ brings those data-driven estimates into agreement with the simulations.
  • Extending the observed luminosity functions to faint sources with $M_{\rm UV}=-11$ raises the inferred escape fractions by about a factor of 1.5 at $z=10$, implying that the unresolved faint population matters but is not the dominant driver of the budget.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If future JWST programs measure $\xi_{\rm ion}$ for fainter galaxies at $z>8$ and find a stronger mass or luminosity dependence than currently assumed, the inferred escape fractions would shift; the paper's assumption of mass-independent $f_{\rm esc}\,\xi_{\rm ion}$ could be checked directly by stacking Lyman-continuum measurements by halo mass.
  • The clumping factor comparison points toward a model-independent measurement: combining an observed mean free path with the photoionization rate and the Case A recombination coefficient pins down $C_R$ without simulations, and the authors' correction to Davies et al. suggests such a measurement would land in the 3–6 range if $\alpha_\lambda\approx 3$.
  • The consistency argument implicitly depends on the Lyman-alpha forest calibration at $5<z<6.2$; if the mean transmission measurements shift because of continuum uncertainties, the inferred escape fractions and clumping factors would scale, and the crisis could reappear in a different form.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 5 minor

Summary. The paper uses the GPU-based radiative transfer code ATON-HE to post-process Sherwood-Relics hydrodynamical simulations in a 160 cMpc/h box with 2048^3 cells, calibrating the total ionizing emissivity to match the mean Lyman-alpha forest transmission at 5<z<6.2 from Bosman et al. (2022). Four reionization histories are considered: Fiducial, Early, Extremely Early, and Oligarchic. The authors then fit the product f_esc*xi_ion independently at each redshift so that the simulated UV luminosity functions match observed UV LFs at z=5-12.5, and divide by literature xi_ion measurements (Simmonds et al. 2024a) to infer escape fractions. They also infer an effective clumping factor C_R from their simulations and compare it with Chen et al. (2020) and Davies et al. (2024). The central claims are that the inferred f_esc rises from ~5-6% at z=6 to 15-30% at z=10 for the fiducial source model, that the oligarchic model requires f_esc>50% at z>10 and is disfavored, and that the effective clumping factor is 3-6, suggesting consistency between JWST-era measurements of galaxy ionizing properties and the ionizing photon budget required for late reionization.

Significance. The question of whether JWST measurements of xi_ion and UV LFs create a 'photon budget crisis' for late reionization is timely, and this paper provides a concrete simulation-based estimate of the required escape fractions and clumping factors. The main strengths are the careful calibration of the simulations to Lyman-alpha forest data, the use of multiple reionization histories, and the explicit discussion of limitations such as the inability to resolve Lyman-limit systems and to model spectral hardening. If the results hold, they would support a picture where moderate escape fractions (15-30% at z=10) and effective clumping factors of 3-6 reconcile the observed galaxy population with a reionization ending at z~5.5. However, the central consistency claim is weakened by the fact that f_esc*xi_ion is fit to the UV LFs rather than predicted, and by the acknowledged resolution limitations of the simulations. The paper is therefore useful as a diagnostic exercise but should not be read as an independent test of the photon budget.

major comments (4)
  1. [Abstract and Sections 3.2-3.3] The central claim that the inferred clumping factors 'suggest consistency between the observed ionizing properties of reionization-epoch galaxies and the ionizing photon budget' is not an independent test, because f_esc*xi_ion is a free parameter fit separately at each redshift to reproduce the observed UV luminosity functions. The escape fractions are then derived by dividing this fit by an assumed xi_ion; hence the agreement of the reionization history with Lyman-alpha forest data is built in by construction. The paper should explicitly state that the meaningful outputs are the required f_esc and C_R values to be compared with external constraints, and soften the language of 'consistency' accordingly.
  2. [Section 3.3 and Abstract] There is an internal inconsistency in the reported effect of extrapolating the UV luminosity function to M_UV=-11. The text states that this 'increases the inferred f_esc*xi_ion by a factor of 1.15', but the abstract and the same section state that the escape fractions increase by a factor ~1.5. Since xi_ion is assumed to be independent of luminosity, the escape fraction should scale by the same factor as f_esc*xi_ion. Please clarify which factor is correct; this affects the quantitative claim in the abstract.
  3. [Section 3.4] The effective clumping factor is inferred from simulations that the authors themselves state 'only marginally resolve Lyman-limit systems' and 'can not properly account for the spectral hardening of the ionizing UV background.' Because the total ionizing emissivity is calibrated to the mean Lyman-alpha transmission, an underestimated recombination rate (low C_R) would force the calibrated emissivity to be too low, biasing both C_R and the inferred f_esc low in the same direction. The paper should quantify the possible resolution bias, for example by comparing with higher-resolution simulations or analytic estimates, or should explicitly state that the reported C_R and f_esc are lower limits. This is load-bearing for the claimed consistency with the photon budget.
  4. [Section 3.3] The assumption that f_esc*xi_ion is independent of halo mass is not tested. If escape fractions vary systematically with halo mass, as suggested by some low-redshift observations (e.g., Chisholm et al. 2022), the inferred escape fractions and the conclusion that the oligarchic source model is disfavored could change. The paper should discuss the sensitivity of the conclusions to this assumption, particularly because the oligarchic model differs from the fiducial model precisely in which halo masses emit ionizing photons.
minor comments (5)
  1. [Section 3.4] There are stray '?' characters in the text: '(?Feron et al. 2024)' and '(?)' after 'tail-end of reionization'. These appear to be LaTeX citation errors and should be fixed.
  2. [Figure 3] Panel C is very dense, with multiple curves, shaded regions, and point sets. The capture would benefit from a clearer description of the open squares, the grey band, and the meaning of the different line styles.
  3. [Section 3.4, Equations (4)-(5)] The terms 'Case A' and 'Case B' recombination are used without definition; please provide a brief explanation or reference for readers not familiar with the distinction.
  4. [Abstract and Section 3.3] The phrase 'fiducial source model' in the abstract is potentially confusing because it could be read as referring only to the 'Fiducial' reionization history rather than to the assumption of mass-independent f_esc*xi_ion. Consider clarifying this terminology.
  5. [Data Availability] The data availability statement says 'available from the first author upon request'; for a modern journal, a persistent repository link or DOI would be preferable to ensure reproducibility.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the paper's escape fractions are transparently fit-derived quantities checked against external data, and its clumping factors are simulation diagnostics compared with independent estimates.

full rationale

The derivation chain in this paper is not circular. The total ionizing emissivity in the ATON-HE simulations is a free parameter calibrated to the external XQR-30/Bosman et al. (2022) Lyman-alpha forest mean transmission (Section 2). The escape-fraction inference is transparently a fit: Section 3.2 states that 'to achieve agreement with the observed luminosity functions, we have adjusted the combined value of f_esc×xi_ion and obtained a least square fit independently at each redshift.' The inferred f_esc is then obtained by dividing this fitted product by independently measured xi_ion values from Simmonds et al. (2024a), and checked against lower-redshift measurements (Begley+22, Saldana-Lopez+22, Rosdahl+22, Chisholm+22). This is an external consistency check, not a quantity forced by construction. The effective clumping factor is not an input to the calibration; it is diagnosed from the simulation by inverting the Madau et al. (1999) equation (Section 3.4), and is compared with external estimates from Chen et al. (2020) and Davies et al. (2024). The consistency claim is therefore a comparison between JWST-derived ionizing properties (xi_ion, UV luminosity functions) and a Lyman-alpha-calibrated simulation, with the clumping factor emerging from the simulation rather than being set to enforce agreement. The authors' reliance on their own earlier papers (Asthana et al. 2024a,b) for the code and simulation setup is a methodological citation, not a circular justification: the current analysis and comparisons are carried out in this paper. The Section 3.4 admission that the simulations 'only marginally resolve Lyman-limit systems' and cannot fully account for spectral hardening is a resolution/correctness caveat, but it does not make the inference definitionally equivalent to its inputs. No equation in the paper reduces a predicted quantity to a fitted parameter or to a self-citation; no circular step is present.

Assumptions & free parameters 3 free parameters · 7 assumptions · 0 invented entities

The central inferences rest on several modeling assumptions: the source model, mass-independent f_esc*xi_ion, luminosity-independent xi_ion, and the choices of Case A recombination and alpha_lambda=3 in the re-analysis of Davies et al. (2024). These are physically motivated but not independently verified.

free parameters (3)
  • Total ionizing emissivity = Adjusted to match Ly-alpha forest mean transmission (Bosman et al. 2022)
    Set as a free parameter to calibrate the simulation's reionization history to Lyman-alpha forest data at 5<z<6.2.
  • f_esc * xi_ion per redshift = Values in Figure 3A, ranging roughly from 1e24 to 1e26 s^-1
    Adjusted independently at each redshift to match observed UV luminosity functions (Bouwens et al. 2021, Donnan et al. 2024, Napolitano et al. 2024).
  • Oligarchic model minimum halo mass = 8.5e9 M_sun/h
    Manually imposed cutoff; causes the oligarchic model's UV LF to terminate earlier than the other models.
assumptions (7)
  • domain assumption Ionizing emissivity of halos is proportional to halo mass
    Section 2: the source model assigns Ndot_ion proportional to halo mass, as described in Asthana et al. (2024a). This determines the UV LF shape.
  • domain assumption f_esc * xi_ion is independent of halo mass
    Section 3.3: 'we assume f_esc*xi_ion to be independent of the mass of the host haloes of the ionizing sources.'
  • domain assumption Observed xi_ion from Simmonds et al. (2024a) applies to all galaxies independent of luminosity
    Section 3.3: 'we use the photometric measurements of galaxies between 3<z<9 (Simmonds et al. 2024a), neglecting any possible dependence on luminosity.'
  • domain assumption Uniform UV background (Puchwein et al. 2019) approximates the hydrodynamic response of gas to reionization
    Section 2: 'A uniform UV background as described by Puchwein et al. (2019) is integrated into the simulations to approximate the hydrodynamic response of the gas density to reionization.'
  • domain assumption Case A recombination is appropriate in highly ionized regions at the tail end of reionization
    Section 3.4: 'we use the case A recombination coefficient, which is about a factor 1.6 larger at the relevant temperatures and should be the correct choice in highly ionized regions at the tail-end of reionization.'
  • domain assumption Mean free path scales as lambda_nu propto nu^3 (alpha_lambda=3)
    Section 3.4: 'as the mean free path is still limited by the remaining neutral islands (Feron et al. 2024), alpha_lambda=3 should be a more appropriate choice than alpha_lambda=1, used by Davies et al. (2024).'
  • domain assumption Halo mass cutoff at 1e9 M_sun/h is set by resolution, not physics
    Section 3.2: 'The halo mass cutoff at 1e9 M_sun/h for the Fiducial, Early, and Extremely Early models is set by the mass resolution of the post-processed Gadget simulation. We do not have a physical model for the suppression of star formation in small mass haloes.'

how reviews work

0 comments
Cite this review

Pith. "Pith review of The ionizing photon budget and effective clumping factor in radiative transfer simulations calibrated to Lyman-alpha forest data." pith.science (2026). https://pith.science/paper/HW3J7XHG

@misc{pith2026241201906,
  author       = {Pith},
  title        = {Pith review of: The ionizing photon budget and effective clumping factor in radiative transfer simulations calibrated to Lyman-alpha forest data},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/HW3J7XHG}},
  note         = {Machine review of arXiv:2412.01906}
}
abstract

Recent JWST observations have allowed for the first time to obtain comprehensive measurements of the ionizing photon production efficiency $\xi_\text{ion} $ for a wide range of reionization-epoch galaxies. We explore implications for the inferred UV luminosity functions and escape fractions of ionizing sources in our suite of simulations. These are run with the GPU-based radiative transfer code ATON-HE and are calibrated to the XQR-30 Lyman-alpha forest data at $5<z<6.2$. For our fiducial source model, the inferred ionizing escape fractions increase from (6.1, 5.4, 4.9)% at $z=6$ to (14.4, 23.8, 29.4)% at $z=10$ for our (Fiducial, Early, Extremely Early) models in good agreement with extrapolations of lower redshift escape fraction measurements. Extrapolating observed luminosity functions beyond the resolution limit of the simulations to faint sources with $M_\text{UV}=-11$ increases the inferred escape fractions by a factor $\sim 1.5$ at $z=10$. For our oligarchic source model, where no ionizing photons are emitted in faint sources, the inferred escape fractions increase from 10% at $z=6$ to uncomfortably large values $>50$% at $z> 10$, disfavouring the oligarchic source model at very high redshift. The inferred effective clumping factors in our simulations are in the range of $3-6$, suggesting consistency between the observed ionizing properties of reionization-epoch galaxies and the ionizing photon budget in our simulations.

Figures

Figures reproduced from arXiv: 2412.01906 by the authors.

Figure 1
Figure 1. Panel A compares the mean Lyman-𝛼 forest transmission, ⟨𝐹⟩, in our simulations, with measurements by Bosman et al. (2022). Panel B shows the volume-averaged neutral hydrogen fraction, ⟨𝑥HI⟩v. This panel also shows inferences of the neutral hydrogen fraction from various observations: the fraction of Lyman-break galaxies showing Lyman-𝛼 emission (Mason et al. 2018, 2019), dark gaps in the Lyman-𝛼 forest (McGreer et a… view at source ↗
Figure 2
Figure 2. The UV luminosity function in our four models at redshifts 𝑧 = 5.11, 5.95, 7.14, 8.15, 9.02, 10.14, 10.83, 12.59. The observational data points are taken from Bouwens et al. (2021), Donnan et al. (2024), and Napolitano et al. (2024). The dashed and dotted grey curves represent the best-fit Schechter function and double power law (with faint end slope ∝ 𝐿 −1 ) curves, respectively, to the data points. 3.2 UV luminosi… view at source ↗
Figure 3
Figure 3. In Panel A, the solid lines represent the values of 𝑓esc × 𝜉ion required to match the observed UV luminosity function for the four models. The dashed line represents the same value now integrating the observed UV LF down to 𝑀UV = −11. For the oligarchic model, an extension to fainter magnitudes is not sensible as this model is constructed to model reionization by bright sources only. In Panel B, the solid lines repr… view at source ↗

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

64 extracted references · 1 canonical work pages

  1. [1]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.state := if if FUNCTION not #0 #1 if FUNCTION and 'skip pop #0 if FUNCTION or pop #1...

  2. [2]

    G., Kulkarni G., Aubert D., Bolton J

    Asthana S., Haehnelt M. G., Kulkarni G., Aubert D., Bolton J. S., Keating L. C., 2024a, @doi [ ] 10.1093/mnras/stae1945 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.tmp.1922A

  3. [3]

    G., Kulkarni G., Bolton J

    Asthana S., Haehnelt M. G., Kulkarni G., Bolton J. S., Gaikwad P., Keating L. C., Puchwein E., 2024b, @doi [arXiv e-prints] 10.48550/arXiv.2409.15453 , https://ui.adsabs.harvard.edu/abs/2024arXiv240915453A p. arXiv:2409.15453

  4. [4]

    Atek H., et al., 2024, @doi [ ] 10.1038/s41586-024-07043-6 , https://ui.adsabs.harvard.edu/abs/2024Natur.626..975A 626, 975

  5. [5]

    Aubert D., Teyssier R., 2008, @doi [ ] 10.1111/j.1365-2966.2008.13223.x , https://ui.adsabs.harvard.edu/abs/2008MNRAS.387..295A 387, 295

  6. [6]

    Aubert D., Teyssier R., 2010, @doi [ ] 10.1088/0004-637X/724/1/244 , https://ui.adsabs.harvard.edu/abs/2010ApJ...724..244A 724, 244

  7. [7]

    Ba \ n ados E., et al., 2018, @doi [ ] 10.1038/nature25180 , https://ui.adsabs.harvard.edu/abs/2018Natur.553..473B 553, 473

  8. [8]

    D., D'Aloisio A., Christenson H

    Becker G. D., D'Aloisio A., Christenson H. M., Zhu Y., Worseck G., Bolton J. S., 2021, @doi [ ] 10.1093/mnras/stab2696 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.508.1853B 508, 1853

Show all 64 references
  1. [9]

    Begley R., et al., 2022, @doi [ ] 10.1093/mnras/stac1067 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.513.3510B 513, 3510

  2. [10]

    arXiv:2410.10988

    Begley R., et al., 2024, arXiv e-prints, https://ui.adsabs.harvard.edu/abs/2024arXiv241010988B p. arXiv:2410.10988

  3. [11]

    S., Haehnelt M

    Bolton J. S., Haehnelt M. G., 2007, @doi [ ] 10.1111/j.1365-2966.2007.12372.x , https://ui.adsabs.harvard.edu/abs/2007MNRAS.382..325B 382, 325

  4. [12]

    Bosman S. E. I., Fan X., Jiang L., Reed S., Matsuoka Y., Becker G., Haehnelt M., 2018, @doi [ ] 10.1093/mnras/sty1344 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.479.1055B 479, 1055

  5. [13]

    Bosman S. E. I., et al., 2022, @doi [ ] 10.1093/mnras/stac1046 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.514...55B 514, 55

  6. [14]

    J., et al., 2014, @doi [ ] 10.1088/0004-637X/793/2/115 , https://ui.adsabs.harvard.edu/abs/2014ApJ...793..115B 793, 115

    Bouwens R. J., et al., 2014, @doi [ ] 10.1088/0004-637X/793/2/115 , https://ui.adsabs.harvard.edu/abs/2014ApJ...793..115B 793, 115

  7. [15]

    J., et al., 2021, @doi [ ] 10.3847/1538-3881/abf83e , https://ui.adsabs.harvard.edu/abs/2021AJ....162...47B 162, 47

    Bouwens R. J., et al., 2021, @doi [ ] 10.3847/1538-3881/abf83e , https://ui.adsabs.harvard.edu/abs/2021AJ....162...47B 162, 47

  8. [16]

    Cain C., D'Aloisio A., Gangolli N., McQuinn M., 2023, @doi [ ] 10.1093/mnras/stad1057 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.522.2047C 522, 2047

  9. [17]

    B., Jansen R

    Cain C., Lopez G., D'Aloisio A., Munoz J. B., Jansen R. A., Windhorst R. A., Gangolli N., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2409.02989 , https://ui.adsabs.harvard.edu/abs/2024arXiv240902989C p. arXiv:2409.02989

  10. [18]

    Chen N., Doussot A., Trac H., Cen R., 2020, @doi [ ] 10.3847/1538-4357/abc890 , https://ui.adsabs.harvard.edu/abs/2020ApJ...905..132C 905, 132

  11. [19]

    Chisholm J., et al., 2022, @doi [ ] 10.1093/mnras/stac2874 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.5104C 517, 5104

  12. [20]

    D'Odorico V., et al., 2023, @doi [ ] 10.1093/mnras/stad1468 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.523.1399D 523, 1399

  13. [21]

    B., et al., 2018, @doi [ ] 10.3847/1538-4357/aad6dc , https://ui.adsabs.harvard.edu/abs/2018ApJ...864..142D 864, 142

    Davies F. B., et al., 2018, @doi [ ] 10.3847/1538-4357/aad6dc , https://ui.adsabs.harvard.edu/abs/2018ApJ...864..142D 864, 142

  14. [22]

    B., Bosman S

    Davies F. B., Bosman S. E. I., Furlanetto S. R., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2406.18186 , https://ui.adsabs.harvard.edu/abs/2024arXiv240618186D p. arXiv:2406.18186

  15. [23]

    Dayal P., Ferrara A., 2018, @doi [ ] 10.1016/j.physrep.2018.10.002 , https://ui.adsabs.harvard.edu/abs/2018PhR...780....1D 780, 1

  16. [24]

    arXiv:2401.11242

    Dayal P., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2401.11242 , https://ui.adsabs.harvard.edu/abs/2024arXiv240111242D p. arXiv:2401.11242

  17. [25]

    T., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2403.03171 , https://ui.adsabs.harvard.edu/abs/2024arXiv240303171D p

    Donnan C. T., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2403.03171 , https://ui.adsabs.harvard.edu/abs/2024arXiv240303171D p. arXiv:2403.03171

  18. [26]

    Fan X., et al., 2006, @doi [ ] 10.1086/504836 , https://ui.adsabs.harvard.edu/abs/2006AJ....132..117F 132, 117

  19. [27]

    S., Chapman E., Haehnelt M

    Feron J., Conaboy L., Bolton J. S., Chapman E., Haehnelt M. G., Keating L. C., Kulkarni G., Puchwein E., 2024, @doi [ ] 10.1093/mnras/stae1636 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.532.2401F 532, 2401

  20. [28]

    L., et al., 2019, @doi [ ] 10.3847/1538-4357/ab1ea8 , https://ui.adsabs.harvard.edu/abs/2019ApJ...879...36F 879, 36

    Finkelstein S. L., et al., 2019, @doi [ ] 10.3847/1538-4357/ab1ea8 , https://ui.adsabs.harvard.edu/abs/2019ApJ...879...36F 879, 36

  21. [29]

    Gaikwad P., et al., 2023, @doi [ ] 10.1093/mnras/stad2566 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.525.4093G 525, 4093

  22. [30]

    A., 2017, @doi [ ] 10.1093/mnras/stw3351 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.466.4239G 466, 4239

    Greig B., Mesinger A., Haiman Z., Simcoe R. A., 2017, @doi [ ] 10.1093/mnras/stw3351 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.466.4239G 466, 4239

  23. [31]

    Greig B., Mesinger A., Ba \ n ados E., 2019, @doi [ ] 10.1093/mnras/stz230 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.484.5094G 484, 5094

  24. [32]

    Jin X., et al., 2023, @doi [ ] 10.3847/1538-4357/aca678 , https://ui.adsabs.harvard.edu/abs/2023ApJ...942...59J 942, 59

  25. [33]

    C., Weinberger L

    Keating L. C., Weinberger L. H., Kulkarni G., Haehnelt M. G., Chardin J., Aubert D., 2020, @doi [ ] 10.1093/mnras/stz3083 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.491.1736K 491, 1736

  26. [34]

    Kogut A., et al., 2003, @doi [ ] 10.1086/377219 , https://ui.adsabs.harvard.edu/abs/2003ApJS..148..161K 148, 161

  27. [35]

    C., Haehnelt M

    Kulkarni G., Keating L. C., Haehnelt M. G., Bosman S. E. I., Puchwein E., Chardin J., Aubert D., 2019, @doi [ ] 10.1093/mnrasl/slz025 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.485L..24K 485, L24

  28. [36]

    J., 1999, @doi [ ] 10.1086/306975 , https://ui.adsabs.harvard.edu/abs/1999ApJ...514..648M 514, 648

    Madau P., Haardt F., Rees M. J., 1999, @doi [ ] 10.1086/306975 , https://ui.adsabs.harvard.edu/abs/1999ApJ...514..648M 514, 648

  29. [37]

    Madau P., Giallongo E., Grazian A., Haardt F., 2024, @doi [ ] 10.3847/1538-4357/ad5ce8 , https://ui.adsabs.harvard.edu/abs/2024ApJ...971...75M 971, 75

  30. [38]

    Mason C. A., Treu T., Dijkstra M., Mesinger A., Trenti M., Pentericci L., de Barros S., Vanzella E., 2018, @doi [ ] 10.3847/1538-4357/aab0a7 , https://ui.adsabs.harvard.edu/abs/2018ApJ...856....2M 856, 2

  31. [39]

    A., et al., 2019, @doi [ ] 10.1093/mnras/stz632 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.485.3947M 485, 3947

    Mason C. A., et al., 2019, @doi [ ] 10.1093/mnras/stz632 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.485.3947M 485, 3947

  32. [40]

    D., Mesinger A., D'Odorico V., 2015, @doi [ ] 10.1093/mnras/stu2449 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.447..499M 447, 499

    McGreer I. D., Mesinger A., D'Odorico V., 2015, @doi [ ] 10.1093/mnras/stu2449 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.447..499M 447, 499

  33. [41]

    McQuinn M., 2016, @doi [ ] 10.1146/annurev-astro-082214-122355 , https://ui.adsabs.harvard.edu/abs/2016ARA&A..54..313M 54, 313

  34. [42]

    B., Mirocha J., Chisholm J., Furlanetto S

    Mu \ n oz J. B., Mirocha J., Chisholm J., Furlanetto S. R., Mason C., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2404.07250 , https://ui.adsabs.harvard.edu/abs/2024arXiv240407250M p. arXiv:2404.07250

  35. [43]

    P., Tacchella S., Mason C

    Naidu R. P., Tacchella S., Mason C. A., Bose S., Oesch P. A., Conroy C., 2020, @doi [ ] 10.3847/1538-4357/ab7cc9 , https://ui.adsabs.harvard.edu/abs/2020ApJ...892..109N 892, 109

  36. [44]

    arXiv:2312.06804

    Nakane M., et al., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2312.06804 , https://ui.adsabs.harvard.edu/abs/2023arXiv231206804N p. arXiv:2312.06804

  37. [45]

    arXiv:2410.10967

    Napolitano L., et al., 2024, arXiv e-prints, https://ui.adsabs.harvard.edu/abs/2024arXiv241010967N p. arXiv:2410.10967

  38. [46]

    Ning Y., Jiang L., Zheng Z.-Y., Wu J., 2022, @doi [ ] 10.3847/1538-4357/ac4268 , https://ui.adsabs.harvard.edu/abs/2022ApJ...926..230N 926, 230

  39. [47]

    B., Gunn J

    Oke J. B., Gunn J. E., 1983, @doi [ ] 10.1086/160817 , https://ui.adsabs.harvard.edu/abs/1983ApJ...266..713O 266, 713

  40. [48]

    Planck Collaboration et al., 2014, @doi [ ] 10.1051/0004-6361/201321591 , https://ui.adsabs.harvard.edu/abs/2014A&A...571A..16P 571, A16

  41. [49]

    Planck Collaboration et al., 2020, @doi [ ] 10.1051/0004-6361/201833910 , https://ui.adsabs.harvard.edu/abs/2020A&A...641A...6P 641, A6

  42. [50]

    G., Madau P., 2019, @doi [ ] 10.1093/mnras/stz222 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.485...47P 485, 47

    Puchwein E., Haardt F., Haehnelt M. G., Madau P., 2019, @doi [ ] 10.1093/mnras/stz222 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.485...47P 485, 47

  43. [51]

    Puchwein E., et al., 2023, @doi [ ] 10.1093/mnras/stac3761 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.519.6162P 519, 6162

  44. [52]

    Rosdahl J., et al., 2022, @doi [ ] 10.1093/mnras/stac1942 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.515.2386R 515, 2386

  45. [53]

    Saldana-Lopez A., et al., 2022, @doi [ ] 10.1051/0004-6361/202141864 , https://ui.adsabs.harvard.edu/abs/2022A&A...663A..59S 663, A59

  46. [54]

    arXiv:2409.01286

    Simmonds C., et al., 2024a, @doi [arXiv e-prints] 10.48550/arXiv.2409.01286 , https://ui.adsabs.harvard.edu/abs/2024arXiv240901286S p. arXiv:2409.01286

  47. [55]

    Simmonds C., et al., 2024b, @doi [ ] 10.1093/mnras/stad3605 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.6139S 527, 6139

  48. [56]

    Tepper-Garc \' a T., 2006, @doi [ ] 10.1111/j.1365-2966.2006.10450.x , https://ui.adsabs.harvard.edu/abs/2006MNRAS.369.2025T 369, 2025

  49. [57]

    arXiv:2306.00487

    Umeda H., Ouchi M., Nakajima K., Harikane Y., Ono Y., Xu Y., Isobe Y., Zhang Y., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2306.00487 , https://ui.adsabs.harvard.edu/abs/2023arXiv230600487U p. arXiv:2306.00487

  50. [58]

    G., Springel V., 2004, @doi [ ] 10.1111/j.1365-2966.2004.08224.x , https://ui.adsabs.harvard.edu/abs/2004MNRAS.354..684V 354, 684

    Viel M., Haehnelt M. G., Springel V., 2004, @doi [ ] 10.1111/j.1365-2966.2004.08224.x , https://ui.adsabs.harvard.edu/abs/2004MNRAS.354..684V 354, 684

  51. [59]

    Wang F., et al., 2020, @doi [ ] 10.3847/1538-4357/ab8c45 , https://ui.adsabs.harvard.edu/abs/2020ApJ...896...23W 896, 23

  52. [60]

    Yang J., et al., 2020a, @doi [ ] 10.3847/2041-8213/ab9c26 , https://ui.adsabs.harvard.edu/abs/2020ApJ...897L..14Y 897, L14

  53. [61]

    Yang J., et al., 2020b, @doi [ ] 10.3847/1538-4357/abbc1b , https://ui.adsabs.harvard.edu/abs/2020ApJ...904...26Y 904, 26

  54. [62]

    Yeh J. Y. C., et al., 2023, @doi [ ] 10.1093/mnras/stad210 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.520.2757Y 520, 2757

  55. [63]

    Zhu Y., et al., 2022, @doi [ ] 10.3847/1538-4357/ac6e60 , https://ui.adsabs.harvard.edu/abs/2022ApJ...932...76Z 932, 76

  56. [64]

    arXiv:2401.10328

    D urov c \' kov \'a D., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2401.10328 , https://ui.adsabs.harvard.edu/abs/2024arXiv240110328D p. arXiv:2401.10328

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.