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REVIEW 3 major objections 6 minor 64 references

Reionization in HESTIA: Studying reionization in the LG through zoom simulations

T0 review · 3 major / 6 minor · reviewed 2026-08-04 · deepseek-v4-flash

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Pith's one-line read This paper claims that reionization in the Local Group proceeds inside-out, with the Milky Way and Andromeda progenitors reaching 50 percent ionization by redshift 8.6–9.3, well before the cosmic average, and that external ionization fronts

desk verdict A solid, honestly-scoped first RT reionization study of a HESTIA Local Group; the inside-out result is plausible but rests on a subgrid model that isn't independently validated for external sources. read the letter →

arxiv 2509.10133 v2 pith:CQOSXV34 submitted 2025-09-12 astro-ph.CO astro-ph.GA

David Attard , Luke Conaboy , Noam Libeskind , Sergey Pillipenko , Keri Dixon , Ilian T. Iliev This is my paper
classification astro-ph.COastro-ph.GA
keywords reionizationLocalGroupMilkyWayAndromedaradiativetransferzoomsimulationssatellitegalaxiescosmicdawn
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

This paper tries to establish where the ionizing photons that reionized the Local Group came from, using radiative transfer post-processing on a constrained zoom simulation of the Milky Way–Andromeda system. Across four source and feedback models, the progenitors of the Milky Way and Andromeda reach 50 percent ionization at z≈8.6–9.3, significantly earlier than the global midpoint at z≈7.1–7.7, and external large-scale ionization fronts contribute negligibly. It also claims that present-day satellite galaxies show only weak radial trends in reionization time, and that satellites assembled before reionization are systematically more massive today. A sympathetic reader would care because this restricts where the oldest stars should be found and justifies using zoom-only simulations for local reionization studies.

What carries the argument

The argument rests on a subgrid collapse-fraction model that synthesizes ionizing sources in haloes below 10^9.4 solar masses, which the uniform 1024^3 dark-matter-only calibration simulation cannot resolve. This model, calibrated on a higher-resolution 4096^3 unconstrained simulation, is applied to the constrained Local Group box to match global reionization observables. The calibrated source efficiencies and two suppression models (full and partial) are then run through a radiative transfer code on a 256^3 grid for both the uniform and zoom simulations; halo reionization redshifts are assigned particle-by-particle from the 50 percent mass-weighted ionization threshold.

What would settle it

Run a full-box radiative transfer simulation of the same constrained initial conditions that resolves all haloes above 10^8 solar masses without subgrid synthesis, and compare the ionization history of the Local Group Lagrangian volume against the zoom-only result; if the full-box run shows material ionized before z≈9 by sources outside the zoom region, the inside-out claim fails.

Watch

Extended reading notes

Core claim

The central claim is that reionization in the Local Group is inside-out: the progenitors of the Milky Way and Andromeda ionize their own surroundings before any external front arrives. In all four radiative-transfer scenarios, the mass-weighted ionization fraction of both haloes crosses 50 percent at z≈8.6–9.3, while the full simulation box reaches its midpoint at z≈7.1–7.7. The authors attribute this early reionization to the overdense Lagrangian volume that eventually forms the Local Group, and conclude that external ionizing fronts from large-scale structure play a negligible role, even under the strongest feedback model.

Load-bearing premise

The conclusion that external fronts are negligible rests on the subgrid collapse-fraction model accurately estimating the ionizing photon budget of haloes below 10^9.4 solar masses throughout the box, including the external region, even though that model is calibrated on a different, unconstrained high-resolution simulation.

Editorial extensions

If this is right

  • Zoom-only radiative transfer, calibrated against a coarse full-box run, is sufficient to recover the Milky Way and Andromeda reionization histories, because internal sources dominate.
  • The oldest stellar populations in the Local Group should reside preferentially in the most massive present-day satellites, as pre-reionization formation is associated with higher z=0 mass.
  • Reionization of the Local Group at z≈9 predicts a local photoionization and photoheating epoch earlier than the cosmic average, affecting satellite quenching and gas content.
  • The weak radial correlation for Milky Way satellites (Spearman rank ≈ -0.12) and slightly stronger for Andromeda (≈ -0.2) implies that satellite reionization times are largely set by local conditions, not host distance.

Reading between the lines

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

  • If external fronts are truly negligible in this constrained realization, applying the same pipeline to other constrained Local Group realizations could map the environmental variance in reionization timing; in realizations where the Local Group sits in an underdense region, external fronts might matter more.
  • The subgrid model's calibration on an unconstrained simulation leaves open the possibility that the external photon budget is underestimated; a full-box run resolving all haloes down to 10^8 solar masses would be the direct test.
  • The observed correlation between pre-reionization assembly and present-day mass could be turned into a prediction for the ancient-star content of massive dwarf spheroidals, testable with upcoming deep photometric and spectroscopic surveys.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 6 minor

Summary. This paper presents radiative-transfer post-processing of the HESTIA constrained Local Group simulations. The authors use a uniform 1024^3 DMO run plus a subgrid collapse-fraction model (Nasirudin et al. 2020) to calibrate ionizing efficiencies for low- and high-mass atomic cooling haloes against global observables (neutral fraction, Thomson optical depth, photoionization rate), then apply the calibrated source models in four scenarios to a 4096^3-effective zoom simulation of the MW-M31 pair. They report an inside-out reionization of the Local Group, with MW/M31 material reaching 50 per cent ionization at z~8.7-9.3, earlier than the global midpoint at z~7.1-7.7, and conclude that external ionization fronts play a negligible role. For present-day satellites they find weak anticorrelations between reionization redshift and host-centric distance, and that satellites formed before reionization are preferentially more massive at z=0.

Significance. If the central claims hold, the paper offers a computationally efficient and physically plausible pipeline for studying Local Group reionization in a realistic constrained environment, and it makes a concrete, testable prediction connecting the oldest stellar populations to the most massive present-day satellites. The work is careful in several respects: it calibrates source efficiencies against multiple independent global observables, explores four source/feedback scenarios, uses a particle-based definition of halo reionization times, and explicitly discusses an alternative boundary-mapping approach. However, the 'negligible external fronts' conclusion rests on the transfer of a subgrid model to a constrained field where it has not been directly validated, and the RT setup is not fully specified for DMO inputs. These issues are load-bearing and require attention before the claims can be accepted at face value.

major comments (3)
  1. [Sec 2.1.2, 3.2.2, 4(ii)] The conclusion that external fronts are negligible is not independently established. The subgrid collapse-fraction model is calibrated on S1, an unconstrained 4096^3 DMO simulation, and applied to the 09_18 constrained HESTIA-1024 field. The global calibration of g_gamma (Sec 3.1) can absorb a normalization offset but does not test whether the model places unresolved haloes correctly in space. Since the zoom runs contain no resolved sources outside the zoom region, the Run*_zoom vs Run*_subgrid agreement is a self-consistency check using the same source model, not an independent validation. Please validate the subgrid model within the constrained realization (e.g., against a high-resolution run of the same volume or resolved halo counts), or test the impact of imposing external radiation from the subgrid run on the zoom.
  2. [Sec 2.3] The RT calculation is performed on DMO outputs, but the paper never states how the gas density and temperature fields used by PyC2Ray are constructed from the dark-matter-only runs. Equation (1) defines photon rates, but recombination and absorption depend on the gas density and clumping. Without this information the quantitative z_reion values and the global calibration in Sec 3.1 are not reproducible. Please specify the assumed baryon fraction, the conversion from DM density to gas density, the initial temperature, and any clumping factor.
  3. [Sec 2.4 / 3.3] The RT grid is 256^3 with 0.39 h^-1 Mpc cells, while the satellite haloes analysed in Sec 3.3 have masses ~10^7.6-10^10.6 M_sun (virial radii ~10-100 kpc). Assigning z_reion from the ionization fraction of the cell containing each particle means the satellite times are coarse-grained values of the local background, not the reionization time of the halo's own gas. This could affect the correlation and KS test results in Sec 3.3.1-3.3.2. A resolution study or explicit demonstration that the satellite results are converged would strengthen those claims.
minor comments (6)
  1. [Sec 1, 2.1.2] The definition of LMACH/HMACH contains an apparent typo: 'virial temperatures >10^9 K' for HMACHs and 'below ~10^4 K' for LMACHs. HMACHs should be above ~10^4 K, not 10^9 K; otherwise the atomic-cooling terminology is inconsistent. Please correct.
  2. [Sec 3.1.2] The phrase 'due to their late/early end of reionization' appears misordered. Run 3 ends early and has the largest tau; Run 4 ends late and has the smallest tau. Please reword.
  3. [Sec 3.3.1] Spearman coefficients are reported without p-values or confidence intervals. With N~150, r=-0.12 is not necessarily significant. Please add significance tests and, if claiming a 'somewhat tighter' trend for M31, a formal comparison between the MW and M31 correlation coefficients.
  4. [Abstract / Sec 4] The phrase 'most permissive feedback model' is not defined. Specify that it refers to the Partial Suppression model (e.g., Run 3), or state the run explicitly.
  5. [Sec 4] The comparison of MW/M31 z_reion to the global midpoint should be explicitly labelled as a prediction of the calibrated model, not a parameter-free comparison, since the same calibrated efficiencies set both quantities. This would help readers interpret the 'significantly earlier' claim.
  6. [Throughout] There are several typographical errors ('occured', 'similiar', 'subgird') and a few run-on sentences. A careful proofreading pass is recommended.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the Local Group reionization predictions are not used in the calibration, so the central claim retains independent content.

full rationale

The paper's calibration step fits the source efficiencies g_gamma,HMACH and g_gamma,LMACH on the uniform HESTIA-1024 run against global observables (x_HI, tau, Gamma_ion) in Sec. 3.1. The Local Group reionization redshifts and the inside-out morphology are then computed by applying those same calibrated efficiencies to the zoom simulation. The LG values are not used in the calibration, so the comparison between the LG z_reion values (~8.7-9.3) and the global midpoint (~7.1-7.7) is a genuine model prediction, not a quantity forced by the fit. The agreement between Run*_subgrid and Run*_zoom shown in Fig. 5 is a consistency check between two different source representations (mock subgrid haloes vs. directly resolved zoom haloes), but it does not set any parameter and does not reduce the central claim to its input. The reliance on the Nasirudin et al. (2020) subgrid model for unresolved external haloes, and the caveat in Sec. 2.3 that haloes outside the zoom region are not resolved, are limitations on model dependence rather than circularity; the paper also explicitly acknowledges the alternative thesan-zoom boundary-mapping method in Sec. 4. Self-citations to Dixon et al. (2016, 2018) and Iliev et al. (2011) are contextual and are not used as the sole justification for the paper's conclusions. No equation or fitted parameter is renamed as a prediction; the global reionization history is openly described as calibrated, and the local predictions follow from the calibrated model without being fed back into the calibration.

Assumptions & free parameters 3 free parameters · 5 assumptions · 0 invented entities

The central reionization redshifts and the inside-out conclusion rest on hand-calibrated source efficiencies, a subgrid model imported from prior work and calibrated on an unpublished simulation, a coarse RT grid, and the assumption that external radiation can be omitted after a self-consistency check. No new physical entities are introduced.

free parameters (3)
  • Source efficiency g_gamma,HMACH = Run1: 0.7, Run2: 1.5, Run3: 1.1, Run4: 1.1
    Ionizing photon efficiency per unit halo mass for high-mass atomic cooling haloes (M>10^9 Msun), tuned by hand so that each subgrid run matches global reionization observables (Sec 2.3, Sec 3.1).
  • Source efficiency g_gamma,LMACH = Run1: 1.5, Run2: 2, Run3: 1.7, Run4: 1.7
    Ionizing photon efficiency per unit halo mass for low-mass atomic cooling haloes (10^8-10^9 Msun), tuned by hand; values are larger than g_gamma,HMACH to represent PopIII stars (Sec 2.3).
  • LMACH/HMACH mass split = 10^9 Msun
    Hand-chosen threshold based on the Jeans mass in ionized regions, following Dixon et al. (2018); determines which haloes are suppressed in the source models (Sec 2.1.2).
assumptions (5)
  • domain assumption The instantaneous halo-bias subgrid model of Nasirudin et al. (2020), calibrated on S1, predicts the collapse fraction of unresolved LMACHs in HESTIA-1024.
    Used to add ionizing sources below 10^9.4 Msun in the uniform run; central to estimating the external source contribution (Sec 2.1.2).
  • domain assumption Zoom simulations without an external radiation field adequately reproduce the LG reionization field once inside-out topology is established.
    Underpins the claim that external fronts are negligible; validated only by comparing zoom to the same-calibration subgrid run (Sec 3.2.1, Discussion).
  • domain assumption Minihaloes below 10^8 Msun contribute negligibly to reionization after the earliest stages.
    Excluded from source models based on H2 suppression arguments (Ahn et al. 2009); affects early EoR but the paper focuses on later stages (Sec 2.3).
  • domain assumption The HESTIA 09_18 initial conditions reproduce the observed Local Group morphology (MW-M31 pair, Virgo, Local Void).
    Inherited from Libeskind et al. (2020); the paper verifies mass accretion histories against the original arepo run (Fig. 2).
  • domain assumption PyC2Ray RT on a 256^3 grid with non-equilibrium chemistry gives a converged ionization field for cell-scale reionization times.
    Resolution choice (0.39 h^-1 Mpc cells) is coarse for small satellites; convergence is not demonstrated (Sec 2.3, Sec 2.4).

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Cite this review

Pith. "Pith review of Reionization in HESTIA: Studying reionization in the LG through zoom simulations." pith.science (2026). https://pith.science/paper/CQOSXV34

@misc{pith2026250910133,
  author       = {Pith},
  title        = {Pith review of: Reionization in HESTIA: Studying reionization in the LG through zoom simulations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/CQOSXV34}},
  note         = {Machine review of arXiv:2509.10133}
}
abstract

While cosmic reionization has been broadly constrained by global observables, the interplay between internal sources [Milky Way (MW), M31, and their satellites] and external ionization fronts remains poorly understood in a realistic Local Group (LG) context. To address this issue, we perform radiative transfer post-processing on the original hestia LG constrained simulation. We calibrate our source models using a uniform $1024^3$ particle, dark matter-only, hestia simulation coupled with a subgrid collapse fraction model to match the global reionization observables. These source models are then applied to the hestia zoom-in simulations, which consist of a $4096^3$ particle effective resolution in the zoom region centred on the MW and M31 haloes, which resolves haloes down to $10^8$ M$_{\odot}$. We find that in all scenarios, reionization within the LG proceeds in an inside-out manner with the progenitors of the MW and M31 having 50 per cent of their material ionized by $z \sim 9-8.6$, significantly earlier than the global mid-point at $z \sim 7-7.7$, noting that external fronts from large-scale structure play a negligible role, even under the most permissive feedback model. We further show that present-day satellite galaxies exhibit only a weak correlation between their reionization redshift and their present-day radial distance from their host halo, with somewhat tighter trends around M31 than the MW. Finally, we find that presentday satellites whose assembly preceded the reionization of most of their $z = 0$ material are systematically more massive today, suggesting that the oldest stellar populations preferentially reside in the most massive $z = 0$ subhaloes.

Figures

Figures reproduced from arXiv: 2509.10133 by the authors.

Figure 1
Figure 1. presents the distribution of the collapsed fractions of haloes with masses between 108 − 109 M⊙ ( 𝑓coll, 8 : 9) at 𝑧 = 8.899, comparing the direct 𝑁-body simulation using S1 data (right panel) with the instantaneous mock haloes applied to the HESTIA-1024 DMO simulation (left panel) [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. The mass accretion history of the MW halo (blue) and M31 (red), when the constrained initial conditions were evolved using ramses (solid) and arepo (dashed). In black, we also show the semi-analytical relation from Correa et al. (2015). differences produce distinguishable signatures in the reionization history. The source models adopted here were previously introduced in Dixon et al. (2016). We define a source as an… view at source ↗
Figure 3
Figure 3. The four different runs using the subgrid model simulation. Top: Volume-weighted mean neutral hydrogen fraction compared to observational constraints (Ouchi et al. 2010; McGreer et al. 2014; Greig & Mesinger 2017; Mason et al. 2018; Davies et al. 2018; Hoag et al. 2019; Jung et al. 2020; Ďurovčíková et al. 2024; Nakane et al. 2024; Umeda et al. 2025). Middle: Thomson optical depth, 𝜏, with Planck constraints from Pl… view at source ↗
Figures from the paper (5 more)
Figure 4
Figure 4. Figure 4: A 1.17 ℎ −1 Mpc projection of the reionization map centred on the location of the LG haloes (M31 and MW) at 𝑧 = 9.5. The average redshift of reionization along the projection is shown. The location of the M31 and MW progenitors at 𝑧 = 9.5, as identified through the zoo…
Figure 5
Figure 5. Figure 5: The mass-weighted ionization history in the four different runs. The ionization history of the full box in the subgrid-coupled simulations is shown in black. The mass-weighted ionization history of the M31 (red) and MW (blue) haloes is shown, and the results obtained f…
Figure 6
Figure 6. Figure 6: Top: The redshift of reionization (𝑧reion) of the MW satellites and MW halo against the radial distance of the satellite from the MW halo at 𝑧 = 0, where the satellite markers are coloured depending on the mass of the satellite at 𝑧 = 0. The solid red line shows the bi…
Figure 7
Figure 7. Figure 7: Same as [PITH_FULL_IMAGE:figures/full_fig_p009_7.png]
Figure 8
Figure 8. Figure 8: Top: Histograms of the present-day halo masses of MW satellites, split by formation history. Satellites that formed before their material was reionized are shown in blue, while those that formed after reionization are shown in orange. Results are shown for four differe…

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Works this paper leans on

64 extracted references · 5 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]

    T., 2022, @doi [ ] 10.1103/PhysRevD.106.083521 , https://ui.adsabs.harvard.edu/abs/2022PhRvD.106h3521A 106, 083521

    Abe K. T., 2022, @doi [ ] 10.1103/PhysRevD.106.083521 , https://ui.adsabs.harvard.edu/abs/2022PhRvD.106h3521A 106, 083521

    work page doi:10.1103/physrevd.106.083521 2022

  3. [3]

    R., Iliev I

    Ahn K., Shapiro P. R., Iliev I. T., Mellema G., Pen U.-L., 2009, @doi [ ] 10.1088/0004-637x/695/2/1430 , 695, 1430–1445

    doi:10.1088/0004-637x/695/2/1430 2009

  4. [4]

    T., Shapiro P

    Ahn K., Iliev I. T., Shapiro P. R., Mellema G., Koda J., Mao Y., 2012, @doi [ ] 10.1088/2041-8205/756/1/L16 , https://ui.adsabs.harvard.edu/abs/2012ApJ...756L..16A 756, L16

    doi:10.1088/2041-8205/756/1/l16 2012

  5. [5]

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

    doi:10.1038/s41586-024-07043-6 2024

  6. [6]

    Aubert D., et al., 2018, @doi [ ] 10.3847/2041-8213/aab14d , https://ui.adsabs.harvard.edu/abs/2018ApJ...856L..22A 856, L22

    doi:10.3847/2041-8213/aab14d 2018

  7. [7]

    Barkana R., Loeb A., 2001, @doi [Physics Reports] 10.1016/s0370-1573(01)00019-9 , 349, 125–238

    doi:10.1016/s0370-1573(01)00019-9 2001

  8. [8]

    S., Kravtsov A

    Bullock J. S., Kravtsov A. V., Weinberg D. H., 2000, @doi [ ] 10.1086/309279 , https://ui.adsabs.harvard.edu/abs/2000ApJ...539..517B 539, 517

    doi:10.1086/309279 2000

Show all 64 references
  1. [9]

    T., Wechsler R

    Busha M. T., Wechsler R. H., Behroozi P. S., Gerke B. F., Klypin A. A., Primack J. R., 2011, @doi [ ] 10.1088/0004-637X/743/2/117 , https://ui.adsabs.harvard.edu/abs/2011ApJ...743..117B 743, 117

    2011 doi

  2. [11]

    Carlesi E., et al., 2016, @doi [ ] 10.1093/mnras/stw357 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.458..900C 458, 900

    2016 doi

  3. [12]

    A., Wyithe J

    Correa C. A., Wyithe J. S. B., Schaye J., Duffy A. R., 2015, @doi [ ] 10.1093/mnras/stv1363 , 452, 1217–1232

    2015 doi

  4. [13]

    B., Trac H., Fuller S., Upton Sanderbeck P

    D'Aloisio A., McQuinn M., Maupin O., Davies F. B., Trac H., Fuller S., Upton Sanderbeck P. R., 2019, @doi [ ] 10.3847/1538-4357/ab0d83 , https://ui.adsabs.harvard.edu/abs/2019ApJ...874..154D 874, 154

    2019 doi

  5. [14]

    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

    2018 doi

  6. [15]

    Dawoodbhoy T., et al., 2018, @doi [ ] 10.1093/mnras/sty1945 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.480.1740D 480, 1740

    2018 doi

  7. [16]

    D., Koposov S

    Diaz J. D., Koposov S. E., Irwin M., Belokurov V., Evans N. W., 2014, @doi [ ] 10.1093/mnras/stu1210 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.443.1688D 443, 1688

    2014 doi

  8. [17]

    L., Iliev I

    Dixon K. L., Iliev I. T., Mellema G., Ahn K., Shapiro P. R., 2016, @doi [ ] 10.1093/mnras/stv2887 , https://ui.adsabs.harvard.edu/abs/2016MNRAS.456.3011D 456, 3011

    2016 doi

  9. [18]

    L., Iliev I

    Dixon K. L., Iliev I. T., Gottlöber S., Yepes G., Knebe A., Libeskind N., Hoffman Y., 2018, @doi [ ] 10.1093/mnras/sty494 , 477, 867–881

    2018 doi

  10. [19]

    K., Strauss M

    Fan X., Narayanan V. K., Strauss M. A., White R. L., Becker R. H., Pentericci L., Rix H.-W., 2002, @doi [ ] 10.1086/339030 , https://ui.adsabs.harvard.edu/abs/2002AJ....123.1247F 123, 1247

    2002 doi

  11. [20]

    L., 2016, @doi [ ] 10.1017/pasa.2016.26 , https://ui.adsabs.harvard.edu/abs/2016PASA...33...37F 33, e037

    Finkelstein S. L., 2016, @doi [ ] 10.1017/pasa.2016.26 , https://ui.adsabs.harvard.edu/abs/2016PASA...33...37F 33, e037

    2016 doi

  12. [21]

    Y., Madau P., 2022, Modeling Cosmic Reionization ( @eprint arXiv 2208.02260 ), https://arxiv.org/abs/2208.02260

    Gnedin N. Y., Madau P., 2022, Modeling Cosmic Reionization ( @eprint arXiv 2208.02260 ), https://arxiv.org/abs/2208.02260

    2022 arXiv

  13. [22]

    arXiv:1005.2687

    Gottloeber S., Hoffman Y., Yepes G., 2010, @doi [arXiv e-prints] 10.48550/arXiv.1005.2687 , https://ui.adsabs.harvard.edu/abs/2010arXiv1005.2687G p. arXiv:1005.2687

    2010 doi arXiv

  14. [23]

    Greig B., Mesinger A., 2017, @doi [ ] 10.1093/mnras/stw3026 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.465.4838G 465, 4838

    2017 doi

  15. [25]

    T., Merz H., Emberson J

    Harnois-Deraps J., Pen U.-L., Iliev I. T., Merz H., Emberson J. D., Desjacques V., 2013, @doi [ ] 10.1093/mnras/stt1591 , 436, 540–559

    2013 doi

  16. [26]

    G., 2018, @doi [ ] 10.1093/mnras/stx2194 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.473..227H 473, 227

    Hassan S., Dav \'e R., Mitra S., Finlator K., Ciardi B., Santos M. G., 2018, @doi [ ] 10.1093/mnras/stx2194 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.473..227H 473, 227

    2018 doi

  17. [27]

    K., Iliev I

    Hirling P., Bianco M., Giri S. K., Iliev I. T., Mellema G., Kneib J. P., 2024, @doi [Astronomy and Computing] 10.1016/j.ascom.2024.100861 , https://ui.adsabs.harvard.edu/abs/2024A&C....4800861H 48, 100861

    2024

  18. [28]

    Hoag A., et al., 2019, @doi [ ] 10.3847/1538-4357/ab1de7 , https://ui.adsabs.harvard.edu/abs/2019ApJ...878...12H 878, 12

    2019 doi

  19. [29]

    T., Mellema G., Pen U

    Iliev I. T., Mellema G., Pen U. L., Merz H., Shapiro P. R., Alvarez M. A., 2006, @doi [ ] 10.1111/j.1365-2966.2006.10502.x , https://ui.adsabs.harvard.edu/abs/2006MNRAS.369.1625I 369, 1625

    2006

  20. [30]

    T., Moore B., Gottl \"o ber S., Yepes G., Hoffman Y., Mellema G., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18292.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.413.2093I 413, 2093

    Iliev I. T., Moore B., Gottl \"o ber S., Yepes G., Hoffman Y., Mellema G., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18292.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.413.2093I 413, 2093

    2011

  21. [31]

    T., Mellema G., Ahn K., Shapiro P

    Iliev I. T., Mellema G., Ahn K., Shapiro P. R., Mao Y., Pen U.-L., 2014, @doi [ ] 10.1093/mnras/stt2497 , 439, 725–743

    2014 doi

  22. [32]

    Jung I., et al., 2020, @doi [ ] 10.3847/1538-4357/abbd44 , 904, 144

    2020 doi

  23. [33]

    Jung M., et al., 2024, @doi [ ] 10.3847/1538-4357/ad245b , https://ui.adsabs.harvard.edu/abs/2024ApJ...964..123J 964, 123

    2024 doi

  24. [34]

    R., Sharma S., Lewis G

    Kafle P. R., Sharma S., Lewis G. F., Bland-Hawthorn J., 2014, @doi [ ] 10.1088/0004-637x/794/1/59 , 794, 59

    2014 doi

  25. [35]

    arXiv:2502.20437

    Kannan R., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2502.20437 , https://ui.adsabs.harvard.edu/abs/2025arXiv250220437K p. arXiv:2502.20437

    2025 doi

  26. [36]

    C., Bolton J

    Keating L. C., Bolton J. S., Cullen F., Haehnelt M. G., Puchwein E., Kulkarni G., 2024, @doi [ ] 10.1093/mnras/stae1530 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.532.1646K 532, 1646

    2024 doi

  27. [37]

    R., Knebe A., 2009, @doi [ ] 10.1088/0067-0049/182/2/608 , https://ui.adsabs.harvard.edu/abs/2009ApJS..182..608K 182, 608

    Knollmann S. R., Knebe A., 2009, @doi [ ] 10.1088/0067-0049/182/2/608 , https://ui.adsabs.harvard.edu/abs/2009ApJS..182..608K 182, 608

    2009 doi

  28. [38]

    Lewis J. S. W., et al., 2022, @doi [ ] 10.1093/mnras/stac2383 , 516, 3389–3397

    2022 doi

  29. [39]

    Y., Alvarez M

    Li T. Y., Alvarez M. A., Wechsler R. H., Abel T., 2014, @doi [ ] 10.1088/0004-637X/785/2/134 , https://ui.adsabs.harvard.edu/abs/2014ApJ...785..134L 785, 134

    2014 doi

  30. [40]

    I., Yepes G., Knebe A., Gottl \"o ber S., Hoffman Y., Knollmann S

    Libeskind N. I., Yepes G., Knebe A., Gottl \"o ber S., Hoffman Y., Knollmann S. R., 2010, @doi [ ] 10.1111/j.1365-2966.2009.15766.x , https://ui.adsabs.harvard.edu/abs/2010MNRAS.401.1889L 401, 1889

    2010

  31. [41]

    I., et al., 2020, @doi [ ] 10.1093/mnras/staa2541 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.498.2968L 498, 2968

    Libeskind N. I., et al., 2020, @doi [ ] 10.1093/mnras/staa2541 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.498.2968L 498, 2968

    2020 doi

  32. [42]

    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

    2018 doi

  33. [43]

    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

    2019 doi

  34. [44]

    W., 2012, @doi [ ] 10.1088/0004-6256/144/1/4 , https://ui.adsabs.harvard.edu/abs/2012AJ....144....4M 144, 4

    McConnachie A. W., 2012, @doi [ ] 10.1088/0004-6256/144/1/4 , https://ui.adsabs.harvard.edu/abs/2012AJ....144....4M 144, 4

    2012 doi

  35. [46]

    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

    2015 doi

  36. [47]

    Nakane M., et al., 2024, @doi [ ] 10.3847/1538-4357/ad38c2 , https://ui.adsabs.harvard.edu/abs/2024ApJ...967...28N 967, 28

    2024 doi

  37. [48]

    T., Ahn K., 2020, @doi [ ] 10.1093/mnras/staa853 , 494, 3294

    Nasirudin A., Iliev I. T., Ahn K., 2020, @doi [ ] 10.1093/mnras/staa853 , 494, 3294

    2020 doi

  38. [49]

    Neyer M., et al., 2024, @doi [ ] 10.1093/mnras/stae1325 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.531.2943N 531, 2943

    2024 doi

  39. [50]

    Ocvirk P., et al., 2014, @doi [ ] 10.1088/0004-637X/794/1/20 , https://ui.adsabs.harvard.edu/abs/2014ApJ...794...20O 794, 20

    2014 doi

  40. [51]

    Ocvirk P., et al., 2020, @doi [ ] 10.1093/mnras/staa1266 , 496, 4087–4107

    2020 doi

  41. [52]

    Ouchi M., et al., 2010, @doi [ ] 10.1088/0004-637X/723/1/869 , https://ui.adsabs.harvard.edu/abs/2010ApJ...723..869O 723, 869

    2010 doi

  42. [53]

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

    2014 doi

  43. [54]

    Planck Collaboration et al., 2018, arXiv e-prints, http://adsabs.harvard.edu/abs/2018arXiv180706209P

    2018

  44. [55]

    Rosdahl J., et al., 2018, @doi [ ] 10.1093/mnras/sty1655 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.479..994R 479, 994

    2018 doi

  45. [56]

    R., Giroux M

    Shapiro P. R., Giroux M. L., Babul A., 1994, @doi [ ] 10.1086/174120 , https://ui.adsabs.harvard.edu/abs/1994ApJ...427...25S 427, 25

    1994 doi

  46. [57]

    G., et al., 2022, @doi [ ] 10.1093/mnras/stac2007 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.515.2970S 515, 2970

    Sorce J. G., et al., 2022, @doi [ ] 10.1093/mnras/stac2007 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.515.2970S 515, 2970

    2022 doi

  47. [58]

    Teyssier R., 2002, @doi [ ] 10.1051/0004-6361:20011817 , https://ui.adsabs.harvard.edu/abs/2002A&A...385..337T 385, 337

    2002 doi

  48. [59]

    Trebitsch M., Volonteri M., Dubois Y., 2020, @doi [ ] 10.1093/mnras/staa1012 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.494.3453T 494, 3453

    2020 doi

  49. [60]

    Umeda H., et al., 2025, @doi [ ] 10.3847/1538-4365/adb1c0 , https://ui.adsabs.harvard.edu/abs/2025ApJS..277...37U 277, 37

    2025 doi

  50. [61]

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

    2020 doi

  51. [62]

    L., van der Marel R

    Watkins L. L., van der Marel R. P., Sohn S. T., Evans N. W., 2019, @doi [ ] 10.3847/1538-4357/ab089f , https://ui.adsabs.harvard.edu/abs/2019ApJ...873..118W 873, 118

    2019 doi

  52. [63]

    M., Macci \`o A

    Weinmann S. M., Macci \`o A. V., Iliev I. T., Mellema G., Moore B., 2007, @doi [ ] 10.1111/j.1365-2966.2007.12279.x , https://ui.adsabs.harvard.edu/abs/2007MNRAS.381..367W 381, 367

    2007

  53. [64]

    Wempe E., Helmi A., White S. D. M., Jasche J., Lavaux G., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2501.08089 , https://ui.adsabs.harvard.edu/abs/2025arXiv250108089W p. arXiv:2501.08089

    2025 doi

  54. [65]

    Wyithe J. S. B., Bolton J. S., 2011, @doi [ ] 10.1111/j.1365-2966.2010.18030.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.412.1926W 412, 1926

    2011

  55. [66]

    Springer Berlin Heidelberg, Berlin, Heidelberg, pp 45--101, @doi 10.1007/978-3-642-32362-1_2 , https://doi.org/10.1007/978-3-642-32362-1_2

    Zaroubi S., 2013, The Epoch of Reionization. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 45--101, @doi 10.1007/978-3-642-32362-1_2 , https://doi.org/10.1007/978-3-642-32362-1_2

    2013 doi

  56. [67]

    D urov c \' kov \'a D., et al., 2024, @doi [ ] 10.3847/1538-4357/ad4888 , https://ui.adsabs.harvard.edu/abs/2024ApJ...969..162D 969, 162

    2024 doi

Pith tools

Reviewed August 4, 2026 · model on record in the stance chip above.