REVIEW 3 major objections 5 minor 92 references
The connection between high-redshift galaxies and Lyman ${\alpha}$ transmission in the Sherwood-Relics simulations of patchy reionisation
T0 review · 3 major / 5 minor · reviewed 2026-08-09 · deepseek-v4-flash
Pith's one-line read Lyman-alpha halo signal matched, but reionisation is too late
desk verdict Solid simulation paper with a central redshift-mismatch claim whose proposed resolution is contradicted by its own Fig. 9; the physical decomposition of the signal is the more durable contribution. read the letter →
The pith
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
The reading
What carries the argument
The load-bearing object is the galaxy–Lyman-$\alpha$ transmission cross-correlation $\delta_F(r)=\langle F(r)\rangle/\bar{F}-1$, the fractional excess or deficit of Lyman-$\alpha$ transmission at comoving distance $r$ from galaxies. The simulations produce it by drawing mock sightlines through a hybrid radiative-transfer scheme in which the ionising luminosity of every source halo is proportional to its mass, and different reionisation histories are set by calibrating the total ionising emissivity. The key physical mechanism isolated by the analysis is local photoionisation: during reionisation, ionised bubbles around clustered sources produce the excess transmission, and the radius of the peak tracks the local mean free path of Lyman-limit photons around haloes. A set of rescaling experiments—forcing ionisation equilibrium, making the UV background uniform, and replacing the temperature field with a power-law density-temperature relation—separates the contributions of non-equilibrium effects, UV background fluctuations, and relic temperature fluctuations to the shape of $\delta_F$.
What would settle it
Measure the host halo masses of C IV absorbers at $z\approx5$–6 directly, for example from their clustering amplitude or from their association with spectroscopically confirmed galaxies: if the minimum mass is at or below $10^{10}\,h^{-1}{\rm M}_\odot$ while the excess transmission persists, the proposed resolution collapses and the simulation's required neutral fraction is ruled out by the Ly$\alpha$ effective optical depth data.
Extended reading notes
Core claim
The central claim is that the Sherwood-Relics suite of hybrid radiation-hydrodynamical simulations captures the physics of patchy reionisation well enough to explain the excess Lyman-$\alpha$ transmission observed at tens of comoving megaparsecs from high-redshift galaxies. When galaxies are selected as dark matter haloes above $10^{10}\,h^{-1}\,{\rm M}_\odot$, the simulations at $z=6$ reproduce the shape and amplitude of the measured C IV absorber–Ly$\alpha$ transmission cross-correlation, with the excess caused by local ionising radiation rather than by density or velocity effects. The catch is chronological: the observed system has mean redshift 5.2, so matching it at $z=6$ demands a neutral fraction $\bar{x}_{\rm HI}\sim 0.1$ at $z\approx 5.2$, in disagreement with the observed Lyman-$\alpha$ effective optical depth distribution. The authors propose that the minimum host halo mass of C IV absorbers at $z>5$ may be larger than $10^{10}\,h^{-1}\,{\rm M}_\odot$, which would allow the same correlation shape at a lower neutral fraction and remove the tension. After reionisation ends, relic temperature fluctuations continue to shape the correlation on scales of a few comoving megaparsecs at $4\le z\le 5$, offering a way to constrain reionisation timing.
Load-bearing premise
The load-bearing premise is that the observed C IV absorbers and [O III] emitters correspond exactly to all simulated dark matter haloes above $10^{10}\,h^{-1}{\rm M}_\odot$, with every halo's ionising output proportional to its mass; if the real host halo masses of these tracers are different, the quoted redshift offset and the inferred neutral fraction change.
Editorial extensions
If this is right
- If the central claim holds, the excess Lyman-alpha transmission seen near C IV absorbers at $z\approx5.2$ is a genuine reionisation-era proximity effect, not a low-redshift artefact.
- The correlation shape at fixed neutral fraction is nearly independent of reionisation history, so comparing models at equal $\bar{x}_{\rm HI}$ rather than equal redshift removes a major modelling uncertainty.
- Larger simulation volumes (beyond $160\,h^{-1}\,{\rm cMpc}$ on a side) are required to capture the large-scale excess; future large-box runs can test the predicted peak location against the [O III] emitter data.
- Below $z\approx5$, relic temperature fluctuations imprint a measurable, evolving signature on the correlation at scales of a few comoving megaparsecs, so the redshift evolution of the excess absorption constrains when reionisation ended.
- If the minimum C IV absorber host halo mass is indeed above $10^{10}\,h^{-1}{\rm M}_\odot$, the apparent conflict with the Lyman-alpha effective optical depth distribution disappears, making the correlation usable as a neutral-fraction indicator.
Reading between the lines
- An implication the authors leave implicit is that the degeneracy between host halo mass and neutral fraction means a single measurement of $\delta_F$ cannot by itself pin down either quantity; independent halo-mass constraints, for example from clustering or abundance matching, are needed to break it.
- If the C IV absorber population is biased to more massive haloes at $z>5$, then the observed correlation could be used to measure the C IV absorber bias, providing a new connection between quasar absorption systems and the ionising source population.
- A testable extension would be to compute the same cross-correlation from simulations with alternative source models, such as ionising luminosity independent of halo mass; the paper predicts the $\delta_F$ shape would change, so observations of the peak amplitude could distinguish source models.
- The predicted post-reionisation signal at $z\approx4$ could be searched for in existing galaxy–Ly$\alpha$ forest datasets from that epoch; a detectable fading of the small-scale excess with decreasing redshift would support a late end to reionisation.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The paper uses the Sherwood-Relics hybrid radiative-transfer simulations to compute the galaxy–Lyα transmission cross-correlation δF during and after reionisation. The authors show that the predicted δF has a central decrement and an excess at larger scales during reionisation, that the excess is driven by inhomogeneous ionising radiation around clustered sources, and that relic temperature fluctuations affect δF at z ≤ 5. They compare with Meyer et al. (2019), Meyer et al. (2020), Kashino et al. (2023), and Kakiichi et al. (2025), reporting quantitative agreement with Meyer et al. (2019) at z = 6 rather than at the data mean z ≈ 5.18, and with Kakiichi et al. (2025) at z = 5.8 using the 160-2048 box. They suggest the Meyer et al. redshift mismatch could be partly resolved if C IV absorbers trace haloes more massive than 10^10 h^-1 M_sun, and they study the degeneracy between halo mass and neutral fraction as well as the post-reionisation temperature-fluctuation signature.
Significance. If the central claim holds, the paper provides a physical interpretation of the high-redshift galaxy–Lyα transmission correlation as a probe of patchy reionisation, connecting the scale of the excess transmission to the local mean free path of ionising photons. The work is careful in several respects: it includes resolution-convergence tests in Appendix A, a decomposition isolating ionisation-equilibrium, uniform-UVB, and temperature-fluctuation effects in Section 4.2, and a comparison at fixed neutral fraction across reionisation histories in Section 4.1. The qualitative prediction that relic temperature fluctuations imprint on δF at 4 ≤ z ≤ 5 is falsifiable with current and near-future observations. However, the quantitative claim is weakened by the redshift offset, the lack of error bars on the model curves, and an inconsistency between the proposed halo-mass resolution and the simulation results shown in Fig. 9.
major comments (3)
- [Sec. 3.2, Sec. 4.1, Fig. 9; abstract and Sec. 5] The proposed resolution of the redshift mismatch is contradicted by the paper's own Fig. 9. In the bottom panel at z = 5.4, increasing the halo mass makes the negative δF region more extended: the 10^12–10^13 h^-1 M_sun bin has δF < 0 out to r ~ 50 cMpc and shows no positive excess at 15–45 cMpc, exactly where Meyer et al. (2019) report δF > 0. Thus raising the minimum C IV host halo mass above 10^10 h^-1 M_sun moves the prediction in the wrong direction at z ~ 5.2–5.4, deepening the decrement instead of producing the observed excess. The abstract and conclusions state this higher halo mass may partly resolve the tension, but the paper contains no simulation demonstrating that outcome; this load-bearing suggestion therefore needs either a quantitative demonstration or removal.
- [Sec. 3.2, Fig. 5] The headline claim that the Meyer et al. (2019) excess is 'quantitatively reproduced' at z = 6 rather than at the data mean ⟨z_CIV⟩ = 5.18 is an internal tension, as the authors recognise: in their fiducial model this redshift offset corresponds to x_HI ~ 0.1 at z ~ 5.2, while the Lyα effective optical depth distribution at z ≤ 5.2 is consistent with a fully reionised IGM. Because the quantitative reproduction is the paper's central positive result, the offset must be treated as a first-class discrepancy, not a side comment. A statistical statement of how well the z = 6 curve actually agrees with the data, and whether the offset is within the model's reionisation-history uncertainties, would be needed before this claim can be assessed.
- [Sec. 3.2, Eqs. (2) and Figs. 5–8] The model δF curves are plotted without error bars, yet the text repeatedly states agreement at the '1σ' or '1.5σ' level (e.g., Sec. 3.2 for Meyer et al. 2019 and Kakiichi et al. 2025). There is no estimate of the sampling or cosmic-variance uncertainty on the simulated δF, which is particularly important given the finite box sizes (40 h^-1 Mpc and 160 h^-1 Mpc) and the limited number of independent sightlines. Without such uncertainties, the quantitative comparison to the data is not fully defined.
minor comments (5)
- [Abstract] The abstract opens by saying the simulations are 'qualitatively consistent' with the interpretation, then states the Meyer et al. (2019) excess is 'quantitatively reproduced'; these two characterisations should be reconciled in the abstract and in Sec. 5.
- [Sec. 2.2 and Fig. 2 caption] The notation 'Civ' is used inconsistently with 'C IV' elsewhere; please use a single notation throughout.
- [Sec. 4.1 and Fig. 10 caption] The phrase 'volume weighed' should read 'volume-weighted'.
- [Sec. 1] The sentence 'which they attributed to a small sample size and noise' would read more clearly as 'which they attributed to the small sample size and noise'.
- [Sec. 2.1] The phrase 'the quick Lyα approach' is a stylistic placeholder; consider giving the method a descriptive name or a citation.
Circularity Check
No significant circularity: the cross-correlation shape is an independent statistic compared against external data, and the paper explicitly reports its redshift mismatch rather than absorbing it into a fit.
full rationale
The paper's derivation chain is not circular. The Sherwood-Relics simulations fix the reionisation history by calibrating the mean Lyα transmission to external measurements (Bosman et al. 2018; Eilers et al. 2018; Bosman et al. 2022), and the galaxy-Lyα transmission correlation δF defined in Eq. (2) is an independent statistic: its radial shape is not fitted to the Meyer et al. (2019), Kashino et al. (2023), or Kakiichi et al. (2025) data. The comparison to those external datasets is therefore a genuine test, not a renaming of the input. The paper explicitly reports that quantitative agreement occurs only at a higher redshift (z = 6) than the mean redshift of the C IV absorbers (z ≈ 5.2), and it identifies the resulting tension with the observed effective optical depth distribution; this is an honest non-finding of agreement rather than a fitted prediction. The assumed halo-mass threshold M_h ≥ 10^10 h^-1 M_sun is motivated by external abundance-matching arguments and is varied explicitly in Fig. 9, so the central comparison is not forced by construction. The ablative tests in Sec. 4.2 (uniform photoionisation rate, ionisation equilibrium, removal of temperature fluctuations) provide controlled evidence for the physical interpretation. Self-citations to Puchwein et al. (2023) and related Sherwood-Relics papers describe the simulation methodology and prior calibration, not an unverified uniqueness theorem, and they are not used to forbid alternative explanations. The possible inconsistency between the proposed larger-halo-mass resolution and Fig. 9 is a physical correctness concern, not a circularity of the derivation.
Assumptions & free parameters
free parameters (4)
- Minimum halo mass for galaxy tracers =
M_h >= 10^10 h^-1 M_sun
- Ionising source minimum halo mass =
M_h > 10^9 h^-1 M_sun
- Ionising emissivity normalization and reionisation history =
Calibrated to match mean transmission (Bosman et al. 2018; Eilers et al. 2018; Bosman et al. 2022)
- Temperature-density relation parameters for rescaling =
T0 = 1.14e4 K, gamma = 1.15 (Sec 4.2) and 1.25 (Sec 4.3)
assumptions (4)
- domain assumption The hybrid radiative transfer scheme (aton run in post-processing on a periodically refreshed density field) captures the hydrodynamic response of the gas to inhomogeneous reionisation.
- domain assumption Ionising source luminosity scales linearly with halo mass.
- domain assumption The quick Lyα scheme, which converts gas particles with overdensity > 1000 and T < 10^5 K into stars, is a sufficient galaxy formation model for this statistic.
- domain assumption The Tepper-García (2006) approximation to the Voigt profile and the neglect of observational effects (noise, resolution) do not bias the cross-correlation comparison.
Cite this review
Pith. "Pith review of The connection between high-redshift galaxies and Lyman ${\alpha}$ transmission in the Sherwood-Relics simulations of patchy reionisation." pith.science (2026). https://pith.science/paper/LMBPULEV
@misc{pith2026250202983,
author = {Pith},
title = {Pith review of: The connection between high-redshift galaxies and Lyman $\alpha$ transmission in the Sherwood-Relics simulations of patchy reionisation},
year = {2026},
howpublished = {\url{https://pith.science/paper/LMBPULEV}},
note = {Machine review of arXiv:2502.02983}
}
abstract
Recent work has suggested that, during reionisation, spatial variations in the ionising radiation field should produce enhanced Ly ${\alpha}$ forest transmission at distances of tens of comoving Mpc from high-redshift galaxies. We demonstrate that the Sherwood-Relics suite of hybrid radiation-hydrodynamical simulations are qualitatively consistent with this interpretation. The shape of the galaxy--Ly ${\alpha}$ transmission cross-correlation is sensitive to both the mass of the haloes hosting the galaxies and the volume averaged fraction of neutral hydrogen in the IGM, $\bar{x}_{\rm HI}$. The reported excess Ly ${\alpha}$ forest transmission on scales r ~ 10 cMpc at $\langle z \rangle \approx 5.2$ -- as measured using C IV absorbers as proxies for high-redshift galaxies -- is quantitatively reproduced by Sherwood-Relics at z = 6 if we assume the galaxies that produce ionising photons are hosted in haloes with mass $M_{\rm h}\geq 10^{10}~h^{-1}\,{\rm M}_\odot$. However, this redshift mismatch is equivalent to requiring $\bar{x}_{\rm HI}\sim 0.1$ at $z\simeq 5.2$, which is inconsistent with the observed Ly ${\alpha}$ forest effective optical depth distribution. We suggest this tension may be partly resolved if the minimum C IV absorber host halo mass at z > 5 is larger than $M_{\rm h}=10^{10}~h^{-1}\,{\rm M}_\odot$. After reionisation completes, relic IGM temperature fluctuations will continue to influence the shape of the cross-correlation on scales of a few comoving Mpc at $4 \leq z \leq 5$. Constraining the redshift evolution of the cross-correlation over this period may therefore provide further insight into the timing of reionisation.
Figures
Figures from the paper (7 more)
Reference graph
Works this paper leans on
-
[1]
Adelberger K. L., Shapley A. E., Steidel C. C., Pettini M., Erb D. K., Reddy N. A., 2005, @doi [ ] 10.1086/431753 , 629, 636
doi:10.1086/431753 2005
-
[2]
Arrabal Haro P., et al., 2023, @doi [ ] 10.1038/s41586-023-06521-7 , 622, 707
-
[3]
Asthana S., Haehnelt M. G., Kulkarni G., Bolton J. S., Gaikwad P., Keating L. C., Puchwein E., 2024a, @doi [arXiv e-prints] 10.48550/arXiv.2409.15453 , p. arXiv:2409.15453
-
[4]
G., Kulkarni G., Aubert D., Bolton J
Asthana S., Haehnelt M. G., Kulkarni G., Aubert D., Bolton J. S., Keating L. C., 2024b, @doi [ ] 10.1093/mnras/stae1945 , 533, 2843
-
[5]
Atek H., et al., 2024, @doi [ ] 10.1038/s41586-024-07043-6 , 626, 975
-
[6]
Aubert D., Teyssier R., 2008, @doi [ ] 10.1111/j.1365-2966.2008.13223.x , 387, 295
arXiv 2008
-
[7]
Ba \ n ados E., et al., 2018, @doi [ ] 10.1038/nature25180 , 553, 473
-
[8]
Banerjee E., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2411.11959 , p. arXiv:2411.11959
Show all 92 references
-
[9]
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 , 508, 1853
2021 doi
-
[10]
D., Bolton J
Becker G. D., Bolton J. S., Zhu Y., Hashemi S., 2024, @doi [ ] 10.1093/mnras/stae1918 , 533, 1525
2024 doi
- [11]
-
[12]
M., et al., 2017, @doi [ ] 10.1093/mnras/stx1772 , 471, 2174
Bielby R. M., et al., 2017, @doi [ ] 10.1093/mnras/stx1772 , 471, 2174
2017 doi
-
[13]
D., Bolton J
Boera E., Becker G. D., Bolton J. S., Nasir F., 2019, @doi [ ] 10.3847/1538-4357/aafee4 , 872, 101
2019 doi
-
[14]
S., Becker G
Bolton J. S., Becker G. D., 2009, @doi [ ] 10.1111/j.1745-3933.2009.00700.x , 398, L26
2009
-
[15]
Bosman S. E. I., Fan X., Jiang L., Reed S., Matsuoka Y., Becker G., Haehnelt M., 2018, @doi [ ] 10.1093/mnras/sty1344 , 479, 1055
2018 doi
-
[16]
Bosman S. E. I., et al., 2022, @doi [ ] 10.1093/mnras/stac1046 , 514, 55
2022 doi
-
[17]
Dobb's Journal of Software Tools
Bradski G., 2000, Dr. Dobb's Journal of Software Tools
2000
-
[18]
Cain C., D'Aloisio A., Gangolli N., McQuinn M., 2023, @doi [ ] 10.1093/mnras/stad1057 , 522, 2047
2023 doi
-
[19]
Castellano M., et al., 2024, @doi [ ] 10.3847/1538-4357/ad5f88 , 972, 143
2024 doi
-
[20]
M., et al., 2023, @doi [ ] 10.3847/1538-4357/acf450 , 955, 138
Christenson H. M., et al., 2023, @doi [ ] 10.3847/1538-4357/acf450 , 955, 138
2023 doi
-
[21]
B., Furlanetto S
D'Aloisio A., McQuinn M., Davies F. B., Furlanetto S. R., 2018, @doi [ ] 10.1093/mnras/stx2341 , 473, 560
2018 doi
-
[22]
B., et al., 2018, @doi [ ] 10.3847/1538-4357/aad6dc , 864, 142
Davies F. B., et al., 2018, @doi [ ] 10.3847/1538-4357/aad6dc , 864, 142
2018 doi
-
[23]
Davis M., Peebles P. J. E., 1983, @doi [ ] 10.1086/160884 , 267, 465
1983 doi
-
[24]
D urov c \'i kov \'a D., et al., 2024, @doi [ ] 10.3847/1538-4357/ad4888 , 969, 162
2024 doi
-
[25]
B., Hennawi J
Eilers A.-C., Davies F. B., Hennawi J. F., 2018, @doi [ ] 10.3847/1538-4357/aad4fd , 864, 53
2018 doi
-
[26]
Fan J., Chen H., Avestruz C., Khadir A., 2025, @doi [ ] 10.3847/1538-4357/ada1d3 , 979, 150
2025 doi
-
[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 , 532, 2401
2024 doi
-
[28]
Gaikwad P., et al., 2020, @doi [ ] 10.1093/mnras/staa907 , 494, 5091
2020 doi
-
[29]
Gaikwad P., et al., 2023, @doi [ ] 10.1093/mnras/stad2566 , 525, 4093
2023 doi
- [30]
-
[31]
arXiv:2410.02850
Garaldi E., Bellscheidt V., 2024a, @doi [arXiv e-prints] 10.48550/arXiv.2410.02850 , p. arXiv:2410.02850
-
[32]
arXiv:2410.02853
Garaldi E., Bellscheidt V., 2024b, @doi [arXiv e-prints] 10.48550/arXiv.2410.02853 , p. arXiv:2410.02853
-
[33]
Y., Madau P., 2019, @doi [ ] 10.3847/1538-4357/ab12dc , 876, 31
Garaldi E., Gnedin N. Y., Madau P., 2019, @doi [ ] 10.3847/1538-4357/ab12dc , 876, 31
2019 doi
-
[34]
Garaldi E., Kannan R., Smith A., Springel V., Pakmor R., Vogelsberger M., Hernquist L., 2022, @doi [ ] 10.1093/mnras/stac257 , 512, 4909
2022 doi
- [35]
-
[36]
Y., 2014, @doi [ ] 10.1088/0004-637X/793/1/29 , 793, 29
Gnedin N. Y., 2014, @doi [ ] 10.1088/0004-637X/793/1/29 , 793, 29
2014 doi
-
[37]
Grazian A., et al., 2024, @doi [ ] 10.3847/1538-4357/ad6980 , 974, 84
2024 doi
-
[38]
Greig B., Mesinger A., Ba \ n ados E., 2019, @doi [ ] 10.1093/mnras/stz230 , 484, 5094
2019 doi
- [39]
-
[40]
Harikane Y., et al., 2023, @doi [ ] 10.3847/1538-4357/ad029e , 959, 39
2023 doi
-
[41]
Harikane Y., Nakajima K., Ouchi M., Umeda H., Isobe Y., Ono Y., Xu Y., Zhang Y., 2024, @doi [ ] 10.3847/1538-4357/ad0b7e , 960, 56
2024 doi
-
[42]
R., et al., 2020, @doi [ ] 10.1038/s41586-020-2649-2 , 585, 357
Harris C. R., et al., 2020, @doi [ ] 10.1038/s41586-020-2649-2 , 585, 357
2020 doi
-
[43]
D., 2007, @doi [Computing in Science and Engineering] 10.1109/MCSE.2007.55 , 9, 90
Hunter J. D., 2007, @doi [Computing in Science and Engineering] 10.1109/MCSE.2007.55 , 9, 90
2007 doi
-
[44]
S., White S
Jenkins A., Frenk C. S., White S. D. M., Colberg J. M., Cole S., Evrard A. E., Couchman H. M. P., Yoshida N., 2001, @doi [ ] 10.1046/j.1365-8711.2001.04029.x , 321, 372
2001
-
[45]
Jin X., et al., 2023, @doi [ ] 10.3847/1538-4357/aca678 , 942, 59
2023 doi
-
[46]
Jin X., et al., 2024, @doi [ ] 10.3847/1538-4357/ad82de , 976, 93
2024 doi
-
[47]
Jung I., et al., 2020, @doi [ ] 10.3847/1538-4357/abbd44 , 904, 144
2020 doi
-
[48]
Kakiichi K., et al., 2018, @doi [ ] 10.1093/mnras/sty1318 , 479, 43
2018 doi
- [49]
-
[50]
Kannan R., Garaldi E., Smith A., Pakmor R., Springel V., Vogelsberger M., Hernquist L., 2022, @doi [ ] 10.1093/mnras/stab3710 , 511, 4005
2022 doi
-
[51]
J., Matthee J., Eilers A.-C., Mackenzie R., Bordoloi R., Simcoe R
Kashino D., Lilly S. J., Matthee J., Eilers A.-C., Mackenzie R., Bordoloi R., Simcoe R. A., 2023, @doi [ ] 10.3847/1538-4357/acc588 , 950, 66
2023 doi
-
[52]
C., Puchwein E., Haehnelt M
Keating L. C., Puchwein E., Haehnelt M. G., 2018, @doi [ ] 10.1093/mnras/sty968 , 477, 5501
2018 doi
-
[53]
C., Weinberger L
Keating L. C., Weinberger L. H., Kulkarni G., Haehnelt M. G., Chardin J., Aubert D., 2020a, @doi [ ] 10.1093/mnras/stz3083 , 491, 1736
-
[54]
C., Kulkarni G., Haehnelt M
Keating L. C., Kulkarni G., Haehnelt M. G., Chardin J., Aubert D., 2020b, @doi [ ] 10.1093/mnras/staa1909 , 497, 906
-
[55]
F., O \ n orbe J., Rorai A., Springel V., 2015, @doi [ ] 10.1088/0004-637X/812/1/30 , 812, 30
Kulkarni G., Hennawi J. F., O \ n orbe J., Rorai A., Springel V., 2015, @doi [ ] 10.1088/0004-637X/812/1/30 , 812, 30
2015 doi
-
[56]
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 , 485, L24
2019 doi
-
[57]
Madau P., Giallongo E., Grazian A., Haardt F., 2024, @doi [ ] 10.3847/1538-4357/ad5ce8 , 971, 75
2024 doi
-
[58]
Maiolino R., et al., 2024, @doi [ ] 10.1051/0004-6361/202347640 , 691, A145
2024 doi
-
[59]
Matthee J., et al., 2024, @doi [ ] 10.1093/mnras/stae673 , 529, 2794
2024 doi
-
[60]
S., Puchwein E., 2017, @doi [ ] 10.1093/mnras/stx191 , 468, 1893
Meiksin A., Bolton J. S., Puchwein E., 2017, @doi [ ] 10.1093/mnras/stx191 , 468, 1893
2017 doi
-
[61]
A., Bosman S
Meyer R. A., Bosman S. E. I., Kakiichi K., Ellis R. S., 2019, @doi [ ] 10.1093/mnras/sty2954 , 483, 19
2019 doi
-
[62]
A., et al., 2020, @doi [ ] 10.1093/mnras/staa746 , 494, 1560
Meyer R. A., et al., 2020, @doi [ ] 10.1093/mnras/staa746 , 494, 1560
2020 doi
-
[63]
Molaro M., et al., 2022, @doi [ ] 10.1093/mnras/stab3416 , 509, 6119
2022 doi
-
[64]
S., Lieu M., Keating L
Molaro M., Ir s i c V., Bolton J. S., Lieu M., Keating L. C., Puchwein E., Haehnelt M. G., Viel M., 2023, @doi [ ] 10.1093/mnras/stad598 , 521, 1489
2023 doi
-
[65]
P., et al., 2022, @doi [ ] 10.3847/2041-8213/ac9b22 , 940, L14
Naidu R. P., et al., 2022, @doi [ ] 10.3847/2041-8213/ac9b22 , 940, L14
2022 doi
-
[66]
Nasir F., D'Aloisio A., 2020, @doi [ ] 10.1093/mnras/staa894 , 494, 3080
2020 doi
-
[67]
Pizzati E., et al., 2024, @doi [ ] 10.1093/mnras/stae2307 , 534, 3155
2024 doi
-
[68]
Planck Collaboration et al., 2014, @doi [ ] 10.1051/0004-6361/201321591 , 571, A16
2014 doi
-
[69]
Planck Collaboration et al., 2020, @doi [ ] 10.1051/0004-6361/201833910 , 641, A6
2020 doi
-
[70]
G., Madau P., 2019, @doi [ ] 10.1093/mnras/stz222 , 485, 47
Puchwein E., Haardt F., Haehnelt M. G., Madau P., 2019, @doi [ ] 10.1093/mnras/stz222 , 485, 47
2019 doi
-
[71]
Puchwein E., et al., 2023, @doi [ ] 10.1093/mnras/stac3761 , 519, 6162
2023 doi
-
[72]
C., Haehnelt M
Satyavolu S., Kulkarni G., Keating L. C., Haehnelt M. G., 2024, @doi [ ] 10.1093/mnras/stae1717 , 533, 676
2024 doi
-
[73]
Saxena A., et al., 2024, @doi [ ] 10.1051/0004-6361/202347132 , 684, A84
2024 doi
-
[74]
Schaye J., et al., 2023, @doi [ ] 10.1093/mnras/stad2419 , 526, 4978
2023 doi
-
[75]
Simmonds C., et al., 2024, @doi [ ] 10.1093/mnras/stad3605 , 527, 6139
2024 doi
-
[76]
Smith A., Kannan R., Garaldi E., Vogelsberger M., Pakmor R., Springel V., Hernquist L., 2022, @doi [ ] 10.1093/mnras/stac713 , 512, 3243
2022 doi
-
[77]
Sorini D., Dav \'e R., Angl \'e s-Alc \'a zar D., 2020, @doi [ ] 10.1093/mnras/staa2937 , 499, 2760
2020 doi
-
[78]
Spina B., Bosman S. E. I., Davies F. B., Gaikwad P., Zhu Y., 2024, @doi [ ] 10.1051/0004-6361/202450798 , 688, L26
2024 doi
-
[79]
Springel V., 2005, @doi [ ] 10.1111/j.1365-2966.2005.09655.x , 364, 1105
2005
-
[80]
Tepper-Garc \'i a T., 2006, @doi [ ] 10.1111/j.1365-2966.2006.10450.x , 369, 2025
2006
-
[81]
M., Shanks T., Theuns T., Crighton N
Tummuangpak P., Bielby R. M., Shanks T., Theuns T., Crighton N. H. M., Francke H., Infante L., 2014, @doi [ ] 10.1093/mnras/stu828 , 442, 2094
2014 doi
-
[82]
L., Schaye J., Steidel C
Turner M. L., Schaye J., Steidel C. C., Rudie G. C., Strom A. L., 2014, @doi [ ] 10.1093/mnras/stu1801 , 445, 794
2014 doi
-
[83]
Umeda H., Ouchi M., Nakajima K., Harikane Y., Ono Y., Xu Y., Isobe Y., Zhang Y., 2024, @doi [ ] 10.3847/1538-4357/ad554e , 971, 124
2024 doi
- [84]
-
[85]
G., Springel V., 2004, @doi [ ] 10.1111/j.1365-2966.2004.08224.x , 354, 684
Viel M., Haehnelt M. G., Springel V., 2004, @doi [ ] 10.1111/j.1365-2966.2004.08224.x , 354, 684
2004
-
[86]
Virtanen P., et al., 2020, @doi [Nature Methods] 10.1038/s41592-019-0686-2 , 17, 261
2020 doi
-
[87]
A., et al., 2024, @doi [Nature Astronomy] 10.1038/s41550-024-02397-3
Zavala J. A., et al., 2024, @doi [Nature Astronomy] 10.1038/s41550-024-02397-3
2024 doi
-
[88]
Zhu Y., et al., 2023, @doi [ ] 10.3847/1538-4357/aceef4 , 955, 115
2023 doi
-
[89]
Zhu Y., et al., 2024a, @doi [ ] 10.1093/mnrasl/slae061 , 533, L49
-
[90]
Y., Avestruz C., 2024b, @doi [ ] 10.3847/1538-4357/ad793c , 975, 115
Zhu H., Gnedin N. Y., Avestruz C., 2024b, @doi [ ] 10.3847/1538-4357/ad793c , 975, 115
-
[91]
van der Velden E., 2020, @doi [The Journal of Open Source Software] 10.21105/joss.02004 , 5, 2004
2020 doi
-
[92]
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.stat...
Reviewed August 9, 2026 · model on record in the stance chip above.
Discussion (0). Continue with ORCID to comment.