pith. sign in

arxiv: 2605.26518 · v1 · pith:NZYUY64Znew · submitted 2026-05-26 · 🌌 astro-ph.CO

Unveiling the dark matter nature with reionization relics

Yao Zhang , Paulo Montero-Camacho , Catalina Morales-Guti\'errez , Heyang Long , Christopher M. Hirata , Yi Mao This is my paper

Pith reviewed 2026-06-29 16:19 UTC · model grok-4.3

classification 🌌 astro-ph.CO
keywords warm dark matterreionization relicsLyman-alpha forest21 cm intensity mappingDESISKAdark matter constraintsintergalactic medium
0
0 comments X

The pith

Reionization relics in Lyα forest and 21 cm maps constrain warm dark matter to masses above 5 keV.

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

The paper proposes that warm dark matter suppresses small-scale structures, which alters the timing of reionization and leaves persistent large-scale fluctuations in the intergalactic medium. These reionization relics imprint extra power in Lyman-alpha forest opacity at z=4 and in 21 cm intensity mapping at z=5.5, producing ~19% differences in the power spectrum at k=0.05 Mpc^{-1} for a 3 keV WDM model compared to cold dark matter. The authors forecast that a DESI-like Lyα survey can set a 95% lower limit of m_WDM > 5.0 keV, which rises to >7.1 keV when SKA 21 cm data are added, and could reach 39 keV with next-generation surveys. This large-scale approach complements existing small-scale bounds from the Lyα forest and Milky Way satellites.

Core claim

The central claim is that long-lived reionization relics—fluctuations arising because the thermal and dynamical state of the intergalactic medium depends on the local reionization redshift—provide a novel large-scale probe of warm dark matter. The relic strength couples to WDM mass through both suppressed small-scale gas evolution and shifts in the global reionization history, yielding the stated power-spectrum differences and the forecasted mass limits of m_WDM >5.0 keV (DESI), >7.1 keV (DESI+SKA), and up to 39 keV (next-generation surveys).

What carries the argument

Reionization relics: the additional large-scale fluctuations in Lyα opacity and post-reionization neutral hydrogen whose amplitude is modulated by WDM mass via its effects on small-scale structure formation and reionization timing.

If this is right

  • The Lyα power spectrum at k=0.05 Mpc^{-1}, z=4 differs by ~19% for 3 keV WDM versus CDM when reionization relics are included.
  • The 21 cm power spectrum at k=0.05 Mpc^{-1}, z=5.5 shows a comparable ~19% difference.
  • DESI-like Lyα forest data alone yield m_WDM >5.0 keV at 95% confidence.
  • Adding SKA 21 cm intensity mapping raises the limit to m_WDM >7.1 keV.
  • Next-generation surveys can push the lower bound from the current 9.7 keV up to 39 keV.

Where Pith is reading between the lines

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

  • The method could be combined with existing small-scale Lyα constraints to break degeneracies between WDM mass and reionization parameters.
  • If the relic signal is detected, it would provide an independent test of whether WDM alters the timing of reionization in hydrodynamic simulations.
  • The approach might extend to other large-scale intensity-mapping experiments beyond SKA for cross-checks on the same physical coupling.

Load-bearing premise

The 19% power-spectrum difference is assumed to translate directly into mass limits once the coupling of WDM to both gas evolution and reionization history is taken as given.

What would settle it

A direct measurement showing zero difference in the Lyα power spectrum at k=0.05 Mpc^{-1} and z=4 between a 3 keV WDM model and cold dark matter, after including patchy reionization, would falsify the claimed relic imprint strength.

Figures

Figures reproduced from arXiv: 2605.26518 by Catalina Morales-Guti\'errez, Christopher M. Hirata, Heyang Long, Paulo Montero-Camacho, Yao Zhang, Yi Mao.

Figure 1
Figure 1. Figure 1: WDM mass constraints. Insights from Lyα forest and 21 cm IM. The dot (star) with an arrow represents the lower bound of the WDM mass obtained in the literature (in this work). The data include both observed (filled markers) and forecast (unfilled markers) values from surveys in the Lyα forest, 21 cm IM, and their combination, providing a comprehensive overview of WDM mass constraints across a range of obse… view at source ↗
Figure 2
Figure 2. Figure 2: Flow diagram illustrating the steps of our hybrid methodology. dition of the simulations, excluding thermal velocities in the initial particle velocity distributions. The CDM power spectrum was obtained using Class (D. Blas et al. 2011), with WDM small-scale suppression intro￾duced via a transfer function (P. Bode et al. 2001) T(k) = [1 + (αk) 2ν ] −5/ν , (17) where ν = 1.12 and the scale of the break α is… view at source ↗
Figure 3
Figure 3. Figure 3: The imprint of reionization in different dark matter models. We show the Lyα forest power spectrum with µ = 0.1 at z = 4 and z = 2 in the top row, and the 21 cm IM power spectrum with µ = 0.9 at z = 5.5 and z = 3.5 in the bottom row, including the imprint of reionization for the different WDM models considered herein (colored solid lines) and for the CDM model (blue solid line). Here, µ = cos θ and θ is th… view at source ↗
Figure 4
Figure 4. Figure 4: Relative transparency of a patch of gas locally reionized at zre and observed at zobs = 4 compared to gas reionized at zre = 8 in CDM model. Colored lines represent different dark matter models considered in this work, and the shaded region shows the standard deviation of four real￾izations. dued sensitivity of H I density to zre, as shown in [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: The post-reionization (zre = 7) gas overdensity ρ/ρ¯ (first row) and temperature in Kelvin (second row) at zobs = 5. The left and right columns correspond to 9 keV and 3 keV WDM models, respectively. The length of each panel is 1275 kpc. For 21 cm IM, we consider the low-frequency array of the Square Kilometre Array in Phase 1 (SKA1-Low), and Stage II IM surveys, e.g., Packed Ultra-wideband Mapping Array (… view at source ↗
Figure 6
Figure 6. Figure 6: The post-reionization temperature-density relation of a patch of gas that locally reionizes at zre = 6 and is observed at zobs = 4 (top row) and zobs = 2 (bottom row). The left, middle, and right columns correspond to CDM, 6 keV WDM and 3 keV WDM, respectively. In each panel, particles are smoothed with a Gaussian kernel density estimation with a full-width at half-maximum of 0.05 dex on each axis. The num… view at source ↗
Figure 7
Figure 7. Figure 7: Evolution of volume-weighted global neutral hy￾drogen fraction given by semi-numerical reionization simula￾tions. The solid lines indicate the evolution of xHI in different DM models with other parameters set to fiducial values. The dashed lines show five examples when σ8, ionizing efficiency ζ and turnover mass of halos unable to host star-forming galaxies Mturn change. The rightmost dashed line is the ea… view at source ↗
Figure 9
Figure 9. Figure 9: Forecast of the constraints on mWDM and σ8. We show the constraints by DESI-like Lyα survey (purple), the combination of DESI and SKA1-Low 5,000-h observation of 21 cm IM (blue), Stage V Lyα surveys (green), Stage II IM 1,000-h observation (grey), and the combination of Stage V Lyα surveys and Stage II IM (orange), respectively, with the dark (light) contours representing the 68% (95%) credible regions. Ou… view at source ↗
Figure 8
Figure 8. Figure 8: Relative H I density of a patch of gas locally reionized at zre and observed at zobs = 5.5 compared to gas reionized at zre = 8. Colored lines and shaded regions follow the same convention as in [PITH_FULL_IMAGE:figures/full_fig_p012_8.png] view at source ↗
Figure 10
Figure 10. Figure 10: Comparison of 4D and 2D MCMC forecasts using a single realization. (A) The 4D MCMC introduces two additional free parameters, ionizing efficiency ζ and turnover mass of halos unable to host star-forming galaxies Mturn, which represent the uncertainties of reionization astrophysics. The fiducial model is CDM (1 keV/mWDM = 0), σ8 = 0.8159, ζ = 24 and Log10(Mturn/M⊙) = 8.7. (B) The 2D MCMC fixes ζ and Mturn … view at source ↗
read the original abstract

Dark matter constitutes roughly one-fourth of the Universe, yet its physical nature remains unknown. Warm dark matter (WDM), a class of dark matter candidates, has non-negligible velocity dispersion that suppresses the formation of small-scale cosmic structures. Current constraints therefore rely mainly on small-scale probes such as the Lyman-alpha (Ly${\alpha}$) forest and Milky Way observations of satellite galaxies and stellar streams. We propose a novel large-scale probe based on long-lived "reionization relics": because the thermal and dynamical evolution of the intergalactic medium depends on the local reionization redshift, patchy reionization imprints additional large-scale fluctuations in Ly${\alpha}$ forest opacity and post-reionization HI traced by 21 cm intensity mapping. The strength of these imprints depends on WDM through both small-scale gas evolution and WDM-driven changes in the reionization history. For example, the Ly${\alpha}$ (21 cm) power spectrum in 3 keV WDM differs from cold dark matter by ~19% (~19%) at $k=0.05\,{\rm Mpc^{-1}}$ at z=4 (z=5.5) when reionization relics are included. Using Ly${\alpha}$ forest with a covariance model designed to mimic the capabilities of the Dark Energy Spectroscopic Instrument (DESI), we forecast a constraint of $m_{\rm WDM}>5.0\,{\rm keV}$ (95%), which improves to $m_{\rm WDM}>7.1\,{\rm keV}$ when combined with 21 cm intensity-mapping observations from the Square Kilometre Array (SKA). The next-generation surveys can further strengthen the current best lower bounds from 9.7 to 39 keV.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

2 major / 1 minor

Summary. The manuscript proposes using long-lived reionization relics as a novel large-scale probe of warm dark matter (WDM). It reports that including these relics produces ~19% differences in the Lyα forest power spectrum at k=0.05 Mpc^{-1}, z=4 (and similarly for 21 cm at z=5.5) between 3 keV WDM and CDM, and translates this contrast into forecasted 95% lower limits of m_WDM > 5.0 keV from a DESI-like Lyα survey, >7.1 keV when combined with SKA 21 cm intensity mapping, and up to 39 keV with next-generation surveys.

Significance. If the modeling of the relic imprint and its scaling with m_WDM were shown to be robust, the work would provide a useful large-scale complement to existing small-scale WDM bounds. The explicit use of DESI and SKA covariance models is a concrete strength that allows direct comparison with planned observations.

major comments (2)
  1. [Abstract / Results] Abstract and modeling description: the central 19% power-spectrum contrast at k=0.05 Mpc^{-1} is stated to arise from WDM-driven changes in reionization history, yet no explicit demonstration is given that this contrast survives marginalization over reionization parameters (ionizing efficiency, escape fraction, etc.). Because the forecast limits are derived directly from this contrast, the absence of such tests is load-bearing for the quoted m_WDM bounds.
  2. [Forecasts] Forecast section: the manuscript provides no error budget, no validation of the relic signal against existing Lyα or 21 cm data, and no assessment of foregrounds or systematics. These omissions directly affect the reliability of the numerical forecasts (m_WDM >5.0 keV, >7.1 keV, and 39 keV).
minor comments (1)
  1. [Methods] Clarify how the covariance matrix for the DESI-like Lyα survey is constructed and whether it includes the full covariance between different redshift bins.

Simulated Author's Rebuttal

2 responses · 1 unresolved

We thank the referee for their thorough review and insightful comments on our manuscript. We address each of the major comments point by point below.

read point-by-point responses

  1. Referee: [Abstract / Results] Abstract and modeling description: the central 19% power-spectrum contrast at k=0.05 Mpc^{-1} is stated to arise from WDM-driven changes in reionization history, yet no explicit demonstration is given that this contrast survives marginalization over reionization parameters (ionizing efficiency, escape fraction, etc.). Because the forecast limits are derived directly from this contrast, the absence of such tests is load-bearing for the quoted m_WDM bounds.

    Authors: We concur that showing the persistence of the power spectrum contrast after marginalizing over reionization parameters is crucial for the robustness of our forecasts. We will revise the manuscript to include explicit tests varying key reionization parameters such as ionizing efficiency and escape fraction, confirming that the ~19% difference remains significant at the scales of interest. revision: yes

  2. Referee: [Forecasts] Forecast section: the manuscript provides no error budget, no validation of the relic signal against existing Lyα or 21 cm data, and no assessment of foregrounds or systematics. These omissions directly affect the reliability of the numerical forecasts (m_WDM >5.0 keV, >7.1 keV, and 39 keV).

    Authors: Our forecasts are constructed using the specified covariance models for DESI-like and SKA observations. We will add an expanded discussion of the error budget and potential impacts of foregrounds and systematics in the revised manuscript. Validation of the relic signal is challenging as it represents a novel probe not previously identified in existing datasets; we will clarify this limitation in the text. revision: partial

standing simulated objections not resolved
  • Validation of the relic signal against existing Lyα or 21 cm data

Circularity Check

0 steps flagged

No circularity: forecasts rest on explicit modeled power-spectrum differences without reduction to fitted inputs or self-citations

full rationale

The provided abstract and context contain no equations, self-citations, or ansatzes that reduce the claimed 19% power-spectrum contrast or the resulting m_WDM forecasts to their own inputs by construction. The difference is presented as an output of the reionization-relic modeling (including WDM effects on history and gas evolution), and the DESI/SKA forecasts are standard projections from that modeled signal strength. No load-bearing step matches any enumerated circularity pattern; the derivation chain is self-contained against external benchmarks for the purpose of this analysis.

Axiom & Free-Parameter Ledger

1 free parameters · 2 axioms · 0 invented entities

The central forecast rests on the assumption that WDM alters both small-scale gas clumping and the global reionization timeline in a way that imprints measurable large-scale power; no independent calibration of this coupling is shown. No new particles or forces are postulated beyond standard WDM.

free parameters (1)
  • WDM particle mass m_WDM
    Target parameter whose lower bound is being forecasted; the 3 keV example and the 5.0/7.1 keV limits are outputs of the model.
axioms (2)
  • domain assumption Patchy reionization imprints additional large-scale fluctuations in Lyα forest opacity and post-reionization HI that survive to z=4–5.5.
    Invoked to justify the relic signal; location implicit in the proposal of the probe.
  • domain assumption The strength of these imprints depends on WDM through both small-scale gas evolution and WDM-driven changes in the reionization history.
    This coupling is the load-bearing link between WDM mass and the observable power-spectrum difference.

pith-pipeline@v0.9.1-grok · 5873 in / 1725 out tokens · 35592 ms · 2026-06-29T16:19:05.815147+00:00 · methodology

discussion (0)

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

Reference graph

Works this paper leans on

91 extracted references · 91 canonical work pages · 2 internal anchors

  1. [1]

    2024, ApJ, 963, 23, doi: 10.3847/1538-4357/ad0f1d

    Amiri, M., Bandura, K., Chakraborty, A., et al. 2024, ApJ, 963, 23, doi: 10.3847/1538-4357/ad0f1d

    work page doi:10.3847/1538-4357/ad0f1d 2024

  2. [2]

    2015, JCAP, 2015, 017, doi: 10.1088/1475-7516/2015/12/017

    Arinyo-i-Prats, A., Miralda-Escud´ e, J., Viel, M., & Cen, R. 2015, JCAP, 2015, 017, doi: 10.1088/1475-7516/2015/12/017

    work page doi:10.1088/1475-7516/2015/12/017 2015

  3. [3]

    Banik, N., Bovy, J., Bertone, G., Erkal, D., & de Boer, T. J. L. 2021, JCAP, 2021, 043, doi: 10.1088/1475-7516/2021/10/043

    work page doi:10.1088/1475-7516/2021/10/043 2021

  4. [4]

    2016, JCAP, 2016, 012, doi: 10.1088/1475-7516/2016/08/012

    Baur, J., Palanque-Delabrouille, N., Y` eche, C., Magneville, C., & Viel, M. 2016, JCAP, 2016, 012, doi: 10.1088/1475-7516/2016/08/012

    work page doi:10.1088/1475-7516/2016/08/012 2016

  5. [5]

    M., Athey, A

    Bernstein, G. M., Athey, A. E., Bernstein, R., et al. 2002, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 4485, Optical Spectroscopic Techniques, Remote Sensing, and Instrumentation for Atmospheric and Space Research IV, ed. A. M. Larar & M. G. Mlynczak, 453–459, doi: 10.1117/12.454281

    work page doi:10.1117/12.454281 2002

  6. [6]

    2011, JCAP, 2011, 034, doi: 10.1088/1475-7516/2011/07/034

    Blas, D., Lesgourgues, J., & Tram, T. 2011, JCAP, 2011, 034, doi: 10.1088/1475-7516/2011/07/034

    work page doi:10.1088/1475-7516/2011/07/034 2011

  7. [7]

    P., & Turok, N

    Bode, P., Ostriker, J. P., & Turok, N. 2001, ApJ, 556, 93, doi: 10.1086/321541

    work page doi:10.1086/321541 2001

  8. [8]

    J., & Mahesh, N

    Mozdzen, T. J., & Mahesh, N. 2018, Nature, 555, 67, doi: 10.1038/nature25792

    work page doi:10.1038/nature25792 2018

  9. [9]

    2019, PhRvD, 100, 123005, doi: 10.1103/PhysRevD.100.123005

    Rudakovskyi, A., & Valkenburg, W. 2019, PhRvD, 100, 123005, doi: 10.1103/PhysRevD.100.123005

    work page doi:10.1103/physrevd.100.123005 2019

  10. [10]

    2009, JCAP, 2009, 012, doi: 10.1088/1475-7516/2009/05/012

    Boyarsky, A., Lesgourgues, J., Ruchayskiy, O., & Viel, M. 2009, JCAP, 2009, 012, doi: 10.1088/1475-7516/2009/05/012

    work page doi:10.1088/1475-7516/2009/05/012 2009

  11. [11]

    arXiv e-prints , year =

    Braun, R., Bonaldi, A., Bourke, T., Keane, E., & Wagg, J. 2019, arXiv e-prints, arXiv:1912.12699, doi: 10.48550/arXiv.1912.12699

    work page doi:10.48550/arxiv.1912.12699 2019

  12. [12]

    G., Patel, P., & Santos, M

    Bull, P., Ferreira, P. G., Patel, P., & Santos, M. G. 2015, ApJ, 803, 21, doi: 10.1088/0004-637X/803/1/21

    work page doi:10.1088/0004-637x/803/1/21 2015

  13. [13]

    and Boylan-Kolchin, Michael , year=

    Bullock, J. S., & Boylan-Kolchin, M. 2017, ARA&A, 55, 343, doi: 10.1146/annurev-astro-091916-055313

    work page doi:10.1146/annurev-astro-091916-055313 2017

  14. [14]

    2023, JCAP, 2023, 002, doi: 10.1088/1475-7516/2023/01/002

    Cain, C., D’Aloisio, A., Irˇ siˇ c, V., Gangolli, N., & Dhami, S. 2023, JCAP, 2023, 002, doi: 10.1088/1475-7516/2023/01/002

    work page doi:10.1088/1475-7516/2023/01/002 2023

  15. [15]

    2024, MNRAS, 533, L100, doi: 10.1093/mnrasl/slae067

    Trac, H. 2024, MNRAS, 533, L100, doi: 10.1093/mnrasl/slae067

    work page doi:10.1093/mnrasl/slae067 2024

  16. [16]

    2026, arXiv e-prints, arXiv:2603.25788

    Cain, C., Das, A., D’Aloisio, A., et al. 2026, arXiv e-prints, arXiv:2603.25788. https://arxiv.org/abs/2603.25788

    work page arXiv 2026

  17. [17]

    P., & Corasaniti, P.-S

    Carucci, I. P., & Corasaniti, P.-S. 2019, PhRvD, 99, 023518, doi: 10.1103/PhysRevD.99.023518

    work page doi:10.1103/physrevd.99.023518 2019

  18. [18]

    P., Villaescusa-Navarro, F., Viel, M., & Lapi, A

    Carucci, I. P., Villaescusa-Navarro, F., Viel, M., & Lapi, A. 2015, JCAP, 2015, 047, doi: 10.1088/1475-7516/2015/07/047

    work page doi:10.1088/1475-7516/2015/07/047 2015

  19. [19]

    R., & Hutter, A

    Chatterjee, A., Dayal, P., Choudhury, T. R., & Hutter, A. 2019, MNRAS, 487, 3560, doi: 10.1093/mnras/stz1444 Cosmic Visions 21 cm Collaboration, Ansari, R., Arena, E. J., et al. 2018, arXiv e-prints, arXiv:1810.09572. https://arxiv.org/abs/1810.09572

    work page doi:10.1093/mnras/stz1444 2019

  20. [20]

    Crighton, N. H. M., Murphy, M. T., Prochaska, J. X., et al. 2015, MNRAS, 452, 217, doi: 10.1093/mnras/stv1182 de Belsunce, R., Philcox, O. H. E., Irˇ siˇ c, V., et al. 2024, MNRAS, 533, 3756, doi: 10.1093/mnras/stae2035

    work page doi:10.1093/mnras/stv1182 2015

  21. [21]

    R., Parsons, A

    DeBoer, D. R., Parsons, A. R., Aguirre, J. E., et al. 2017, PASP, 129, 045001, doi: 10.1088/1538-3873/129/974/045001

    work page doi:10.1088/1538-3873/129/974/045001 2017

  22. [22]

    2000, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol

    Kotzlowski, H. 2000, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 4008, Optical and IR Telescope Instrumentation and Detectors, ed. M. Iye & A. F. Moorwood, 534–545, doi: 10.1117/12.395512 DESI Collaboration, Abareshi, B., Aguilar, J., et al. 2022, AJ, 164, 207, doi: 10.3847/1538-3881/ac882b

    work page doi:10.1117/12.395512 2000

  23. [23]

    R., et al

    Dunkley, J., Komatsu, E., Nolta, M. R., et al. 2009, ApJS, 180, 306, doi: 10.1088/0067-0049/180/2/306

    work page doi:10.1088/0067-0049/180/2/306 2009

  24. [24]

    2014, JCAP, 2014, 023, doi: 10.1088/1475-7516/2014/05/023

    Font-Ribera, A., McDonald, P., Mostek, N., et al. 2014, JCAP, 2014, 023, doi: 10.1088/1475-7516/2014/05/023

    work page doi:10.1088/1475-7516/2014/05/023 2014

  25. [25]

    2013, JCAP, 2013, 018, doi: 10.1088/1475-7516/2013/05/018

    Font-Ribera, A., Arnau, E., Miralda-Escud´ e, J., et al. 2013, JCAP, 2013, 018, doi: 10.1088/1475-7516/2013/05/018

    work page doi:10.1088/1475-7516/2013/05/018 2013

  26. [26]

    W., Lang, D., & Goodman, J

    Foreman-Mackey, D., Hogg, D. W., Lang, D., & Goodman, J. 2013, PASP, 125, 306, doi: 10.1086/670067

    work page doi:10.1086/670067 2013

  27. [27]

    R., & Oh, S

    Furlanetto, S. R., & Oh, S. P. 2006, ApJ, 652, 849, doi: 10.1086/508448 18

    work page doi:10.1086/508448 2006

  28. [28]

    G., & Choudhury, T

    Gaikwad, P., Srianand, R., Haehnelt, M. G., & Choudhury, T. R. 2021, MNRAS, 506, 4389, doi: 10.1093/mnras/stab2017

    work page doi:10.1093/mnras/stab2017 2021

  29. [29]

    2017, Physics Letters B, 773, 258, doi: 10.1016/j.physletb.2017.08.022

    Garzilli, A., Boyarsky, A., & Ruchayskiy, O. 2017, Physics Letters B, 773, 258, doi: 10.1016/j.physletb.2017.08.022

    work page doi:10.1016/j.physletb.2017.08.022 2017

  30. [30]

    2021, MNRAS, 502, 2356, doi: 10.1093/mnras/stab192

    Garzilli, A., Magalich, A., Ruchayskiy, O., & Boyarsky, A. 2021, MNRAS, 502, 2356, doi: 10.1093/mnras/stab192

    work page doi:10.1093/mnras/stab192 2021

  31. [31]

    Gnedin, N. Y. 2000, ApJ, 542, 535, doi: 10.1086/317042

    work page doi:10.1086/317042 2000

  32. [32]

    2023, JCAP, 2023, 045, doi: 10.1088/1475-7516/2023/11/045

    Gordon, C., Cuceu, A., Chaves-Montero, J., et al. 2023, JCAP, 2023, 045, doi: 10.1088/1475-7516/2023/11/045

    work page doi:10.1088/1475-7516/2023/11/045 2023

  33. [33]

    B., et al

    Greig, B., Mesinger, A., Davies, F. B., et al. 2022, MNRAS, 512, 5390, doi: 10.1093/mnras/stac825

    work page doi:10.1093/mnras/stac825 2022

  34. [34]

    2024, MNRAS, 530, 3208, doi: 10.1093/mnras/stae1080

    Greig, B., Mesinger, A., Ba˜ nados, E., et al. 2024, MNRAS, 530, 3208, doi: 10.1093/mnras/stae1080

    work page doi:10.1093/mnras/stae1080 2024

  35. [35]

    2023, AJ, 165, 144, doi: 10.3847/1538-3881/acb212

    Guy, J., Bailey, S., Kremin, A., et al. 2023, AJ, 165, 144, doi: 10.3847/1538-3881/acb212

    work page doi:10.3847/1538-3881/acb212 2023

  36. [36]

    Hirata, C. M. 2018, MNRAS, 474, 2173, doi: 10.1093/mnras/stx2854

    work page doi:10.1093/mnras/stx2854 2018

  37. [37]

    2019, ApJ, 878, 12, doi: 10.3847/1538-4357/ab1de7

    Hoag, A., Bradaˇ c, M., Huang, K., et al. 2019, ApJ, 878, 12, doi: 10.3847/1538-4357/ab1de7

    work page doi:10.3847/1538-4357/ab1de7 2019

  38. [38]

    Fuzzy Cold Dark Matter: The Wave Properties of Ultralight Particles , volume=

    Hu, W., Barkana, R., & Gruzinov, A. 2000, PhRvL, 85, 1158, doi: 10.1103/PhysRevLett.85.1158

    work page doi:10.1103/physrevlett.85.1158 2000

  39. [39]

    Hui, L., & Gnedin, N. Y. 1997, MNRAS, 292, 27, doi: 10.1093/mnras/292.1.27 Irˇ siˇ c, V., Xiao, H., & McQuinn, M. 2020, PhRvD, 101, 123518, doi: 10.1103/PhysRevD.101.123518 Irˇ siˇ c, V., Viel, M., Haehnelt, M. G., et al. 2017, PhRvD, 96, 023522, doi: 10.1103/PhysRevD.96.023522 Irˇ siˇ c, V., Viel, M., Haehnelt, M. G., et al. 2024, PhRvD, 109, 043511, doi...

    work page doi:10.1093/mnras/292.1.27 1997

  40. [40]

    2023, ApJ, 942, 59, doi: 10.3847/1538-4357/aca678

    Jin, X., Yang, J., Fan, X., et al. 2023, ApJ, 942, 59, doi: 10.3847/1538-4357/aca678

    work page doi:10.3847/1538-4357/aca678 2023

  41. [41]

    D., Gillet, N., & Mesinger, A

    Kaur, H. D., Gillet, N., & Mesinger, A. 2020, MNRAS, 495, 2354, doi: 10.1093/mnras/staa1323

    work page doi:10.1093/mnras/staa1323 2020

  42. [42]

    Y., Peter, A

    Kim, S. Y., Peter, A. H. G., & Hargis, J. R. 2018, PhRvL, 121, 211302, doi: 10.1103/PhysRevLett.121.211302

    work page doi:10.1103/physrevlett.121.211302 2018

  43. [43]

    Carswell, R. F. 2007, MNRAS, 382, 1657, doi: 10.1111/j.1365-2966.2007.12406.x

    work page doi:10.1111/j.1365-2966.2007.12406.x 2007

  44. [44]

    J., & Hirata, C

    Long, H., Givans, J. J., & Hirata, C. M. 2022, MNRAS, 513, 117, doi: 10.1093/mnras/stac658

    work page doi:10.1093/mnras/stac658 2022

  45. [45]

    Hirata, C. M. 2023, MNRAS, 525, 6036, doi: 10.1093/mnras/stad2639

    work page doi:10.1093/mnras/stad2639 2023

  46. [46]

    A., Treu, T., Dijkstra, M., et al

    Mason, C. A., Treu, T., Dijkstra, M., et al. 2018, ApJ, 856, 2, doi: 10.3847/1538-4357/aab0a7

    work page doi:10.3847/1538-4357/aab0a7 2018

  47. [47]

    A., Fontana, A., Treu, T., et al

    Mason, C. A., Fontana, A., Treu, T., et al. 2019, MNRAS, 485, 3947, doi: 10.1093/mnras/stz632

    work page doi:10.1093/mnras/stz632 2019

  48. [48]

    McDonald, P., & Eisenstein, D. J. 2007, PhRvD, 76, 063009, doi: 10.1103/PhysRevD.76.063009

    work page doi:10.1103/physrevd.76.063009 2007

  49. [49]

    D., Mesinger, A., & D’Odorico, V

    McGreer, I. D., Mesinger, A., & D’Odorico, V. 2015, MNRAS, 447, 499, doi: 10.1093/mnras/stu2449

    work page doi:10.1093/mnras/stu2449 2015

  50. [50]

    2024, MNRAS, 535, 1035, doi: 10.1093/mnras/stae2438

    Meiksin, A., & Puchwein, E. 2024, MNRAS, 535, 1035, doi: 10.1093/mnras/stae2438

    work page doi:10.1093/mnras/stae2438 2024

  51. [51]

    2015, MNRAS, 446, 566, doi: 10.1093/mnras/stu2089

    Mesinger, A., Aykutalp, A., Vanzella, E., et al. 2015, MNRAS, 446, 566, doi: 10.1093/mnras/stu2089

    work page doi:10.1093/mnras/stu2089 2015

  52. [52]

    D., Bolton, J

    Mesinger, A., Furlanetto, S., & Cen, R. 2011, MNRAS, 411, 955, doi: 10.1111/j.1365-2966.2010.17731.x

    work page doi:10.1111/j.1365-2966.2010.17731.x 2011

  53. [53]

    The effect of inhomogeneous reionization on the lyman-αforest power spectrum at redshift z ¿ 4: implications for thermal parameter recovery,

    Molaro, M., Irˇ siˇ c, V., Bolton, J. S., et al. 2022, MNRAS, 509, 6119, doi: 10.1093/mnras/stab3416

    work page doi:10.1093/mnras/stab3416 2022

  54. [54]

    Hirata, C. M. 2019a, JCAP, 2019, 031, doi: 10.1088/1475-7516/2019/08/031

    work page doi:10.1088/1475-7516/2019/08/031 2019

  55. [55]

    2019b, MNRAS, 487, 1047, doi: 10.1093/mnras/stz1388

    Honscheid, K. 2019b, MNRAS, 487, 1047, doi: 10.1093/mnras/stz1388

    work page doi:10.1093/mnras/stz1388

  56. [56]

    2020, MNRAS, 499, 1640, doi: 10.1093/mnras/staa2918

    Montero-Camacho, P., & Mao, Y. 2020, MNRAS, 499, 1640, doi: 10.1093/mnras/staa2918

    work page doi:10.1093/mnras/staa2918 2020

  57. [57]

    2021, MNRAS, 508, 1262, doi: 10.1093/mnras/stab2569

    Montero-Camacho, P., & Mao, Y. 2021, MNRAS, 508, 1262, doi: 10.1093/mnras/stab2569

    work page doi:10.1093/mnras/stab2569 2021

  58. [58]

    2025, MNRAS, 536, 1645, doi: 10.1093/mnras/stae2684

    Long, H., & Mao, Y. 2025, MNRAS, 536, 1645, doi: 10.1093/mnras/stae2684

    work page doi:10.1093/mnras/stae2684 2025

  59. [59]

    2024, MNRAS, 529, 3666, doi: 10.1093/mnras/stae751

    Montero-Camacho, P., Zhang, Y., & Mao, Y. 2024, MNRAS, 529, 3666, doi: 10.1093/mnras/stae751

    work page doi:10.1093/mnras/stae751 2024

  60. [60]

    R., Boehm, C., & Wong, Y

    Mosbech, M. R., Boehm, C., & Wong, Y. Y. Y. 2023, JCAP, 2023, 047, doi: 10.1088/1475-7516/2023/03/047 Mu˜ noz, J. B., Dvorkin, C., & Cyr-Racine, F.-Y. 2020, PhRvD, 101, 063526, doi: 10.1103/PhysRevD.101.063526

    work page doi:10.1088/1475-7516/2023/03/047 2023

  61. [61]

    and Greig, Bradley and Mesinger, Andrei and Mu\ noz, Julian B

    Murray, S., Greig, B., Mesinger, A., et al. 2020, The Journal of Open Source Software, 5, 2582, doi: 10.21105/joss.02582

    work page doi:10.21105/joss.02582 2020

  62. [62]

    O., Birrer, S., Gilman, D., et al

    Nadler, E. O., Birrer, S., Gilman, D., et al. 2021, ApJ, 917, 7, doi: 10.3847/1538-4357/abf9a3 O˜ norbe, J., Davies, F. B., Luki´ c, et al. 2019, MNRAS, 486, 4075, doi: 10.1093/mnras/stz984

    work page doi:10.3847/1538-4357/abf9a3 2021

  63. [63]

    2018, JCAP, 2018, 004, doi: 10.1088/1475-7516/2018/05/004

    Obuljen, A., Castorina, E., Villaescusa-Navarro, F., & Viel, M. 2018, JCAP, 2018, 004, doi: 10.1088/1475-7516/2018/05/004

    work page doi:10.1088/1475-7516/2018/05/004 2018

  64. [64]

    2010, ApJ, 723, 869, doi: 10.1088/0004-637X/723/1/869

    Ouchi, M., Shimasaku, K., Furusawa, H., et al. 2010, ApJ, 723, 869, doi: 10.1088/0004-637X/723/1/869

    work page doi:10.1088/0004-637x/723/1/869 2010

  65. [65]

    2020, JCAP, 2020, 038, doi: 10.1088/1475-7516/2020/04/038

    Palanque-Delabrouille, N., Y` eche, C., Sch¨ oneberg, N., et al. 2020, JCAP, 2020, 038, doi: 10.1088/1475-7516/2020/04/038

    work page doi:10.1088/1475-7516/2020/04/038 2020

  66. [66]

    2013, A&A, 559, A85, doi: 10.1051/0004-6361/201322130

    Palanque-Delabrouille, N., Y` eche, C., Borde, A., et al. 2013, A&A, 559, A85, doi: 10.1051/0004-6361/201322130

    work page doi:10.1051/0004-6361/201322130 2013

  67. [67]

    2019, MNRAS, 484, 933, doi: 10.1093/mnras/stz032 Planck Collaboration, Ade, P

    Park, J., Mesinger, A., Greig, B., & Gillet, N. 2019, MNRAS, 484, 933, doi: 10.1093/mnras/stz032 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2016, A&A, 594, A13, doi: 10.1051/0004-6361/201525830 19 Planck Collaboration, Aghanim, N., Akrami, Y., et al. 2020, A&A, 641, A6, doi: 10.1051/0004-6361/201833910

    work page doi:10.1093/mnras/stz032 2019

  68. [68]

    S., Keating, L

    Puchwein, E., Bolton, J. S., Keating, L. C., et al. 2023, MNRAS, 519, 6162, doi: 10.1093/mnras/stac3761 Ram´ ırez-P´ erez, C., P´ erez-R` afols, I., Font-Ribera, A., et al. 2024, MNRAS, 528, 6666, doi: 10.1093/mnras/stad3781

    work page doi:10.1093/mnras/stac3761 2023

  69. [69]

    2018, ApJL, 859, L18, doi: 10.3847/2041-8213/aac5e0

    Safarzadeh, M., Scannapieco, E., & Babul, A. 2018, ApJL, 859, L18, doi: 10.3847/2041-8213/aac5e0

    work page doi:10.3847/2041-8213/aac5e0 2018

  70. [70]

    2015, Proceedings of Science, 19, doi: 10.22323/1.215.0019

    Santos, M., Bull, P., Alonso, D., et al. 2015, Proceedings of Science, 19, doi: 10.22323/1.215.0019

    work page doi:10.22323/1.215.0019 2015

  71. [71]

    S., Fattahi, A., et al

    Sawala, T., Frenk, C. S., Fattahi, A., et al. 2016, MNRAS, 457, 1931, doi: 10.1093/mnras/stw145

    work page doi:10.1093/mnras/stw145 2016

  72. [72]

    Seo, H.-J., & Eisenstein, D. J. 2003, ApJ, 598, 720, doi: 10.1086/379122

    work page doi:10.1086/379122 2003

  73. [73]

    Seo, H.-J., & Hirata, C. M. 2016, MNRAS, 456, 3142, doi: 10.1093/mnras/stv2806

    work page doi:10.1093/mnras/stv2806 2016

  74. [74]

    2014, MNRAS, 438, 2664, doi: 10.1093/mnras/stt2392

    Sitwell, M., Mesinger, A., Ma, Y.-Z., & Sigurdson, K. 2014, MNRAS, 438, 2664, doi: 10.1093/mnras/stt2392

    work page doi:10.1093/mnras/stt2392 2014

  75. [75]

    2015, MNRAS, 453, 1843, doi: 10.1093/mnras/stv1751

    Sobacchi, E., & Mesinger, A. 2015, MNRAS, 453, 1843, doi: 10.1093/mnras/stv1751

    work page doi:10.1093/mnras/stv1751 2015

  76. [76]

    N., & Steinhardt, P

    Spergel, D. N., & Steinhardt, P. J. 2000, PhRvL, 84, 3760, doi: 10.1103/PhysRevLett.84.3760

    work page doi:10.1103/physrevlett.84.3760 2000

  77. [77]

    2024, A&A, 688, L26, doi: 10.1051/0004-6361/202450798

    Zhu, Y. 2024, A&A, 688, L26, doi: 10.1051/0004-6361/202450798

    work page doi:10.1051/0004-6361/202450798 2024

  78. [78]

    , year =

    Springel, V. 2005, MNRAS, 364, 1105, doi: 10.1111/j.1365-2966.2005.09655.x

    work page doi:10.1111/j.1365-2966.2005.09655.x 2005

  79. [79]

    Springel, V., Yoshida, N., & White, S. D. M. 2001, NewA, 6, 79, doi: 10.1016/S1384-1076(01)00042-2 Square Kilometre Array Cosmology Science Working Group (SKA Cosmology SWG), Bacon, D. J., Battye, R. A., et al. 2020, PASA, 37, e007, doi: 10.1017/pasa.2019.51 St¨ ucker, J., Angulo, R. E., Hahn, O., & White, S. D. M. 2022, MNRAS, 509, 1703, doi: 10.1093/mnr...

    work page doi:10.1016/s1384-1076(01)00042-2 2001

  80. [80]

    V., Klypin, A., et al

    Tinker, J., Kravtsov, A. V., Klypin, A., et al. 2008, ApJ, 688, 709, doi: 10.1086/591439 ˇDurovˇ c´ ıkov´ a, D., Eilers, A.-C., Chen, H., et al. 2024, ApJ, 969, 162, doi: 10.3847/1538-4357/ad4888

    work page internal anchor Pith review doi:10.1086/591439 2008

Showing first 80 references.