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REVIEW 3 major objections 5 minor 106 references

Small-scale Lyman alpha forest cosmology with PRIYA: Constraints from XQ100 and KODIAQ-SQUAD one-dimensional flux power spectra

T0 review · 3 major / 5 minor · reviewed 2026-08-04 · deepseek-v4-flash

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Pith's one-line read The XQ100 quasar spectra, modeled with the PRIYA emulator, constrain the primordial power spectrum amplitude and tilt consistently with eBOSS and Planck—without any external IGM temperature data.

desk verdict Solid, useful Lyman-alpha P1D paper: the XQ100-eBOSS consistency holds and the KODIAQ-SQUAD LLS-selection-bias interpretation is the real result, but the cosmology-independent resolution correction is a genuine unquantified systematic that needs a sensitivity test. read the letter →

arxiv 2509.18271 v2 pith:5RSD7YX3 submitted 2025-09-22 astro-ph.CO astro-ph.GA

Ming-Feng Ho , Mahdi Qezlou , Simeon Bird , Yanhui Yang , Camille Avestruz , M.A. Fernandez , Vid Iršič This is my paper · ORCID
classification astro-ph.COastro-ph.GA
keywords Lyman-alphaforestfluxpowerspectrumprimordialintergalacticmediumheliumreionizationLyman-limitsystemshydrodynamicalsimulationsPRIYAemulator
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 aims to show that high-resolution Lyman-alpha forest spectra from the XQ100 survey, interpreted through the PRIYA simulation emulator, can simultaneously constrain the primordial power spectrum of density fluctuations and the thermal history of the intergalactic medium. The inferred amplitude and tilt of the primordial spectrum at the Lyman-alpha pivot scale agree with the eBOSS survey and Planck CMB measurements, though with wider uncertainties. Crucially, this agreement is reached without using external measurements of the IGM temperature, implying that the small-scale flux power spectrum carries its own thermal information. The companion KODIAQ-SQUAD dataset, by contrast, yields a biased high amplitude that the paper traces to a selection preference for high-column-density absorbers (Lyman-limit systems), which mimic the spectral effect of a larger primordial amplitude. The paper therefore identifies Lyman-limit system contamination as the main obstacle to cosmological inference on small scales.

What carries the argument

The PRIYA multi-fidelity emulator—a machine-learning model interpolating between low- and high-resolution hydrodynamical Lyman-alpha simulations to predict the 1D flux power spectrum at few-percent accuracy from k=0.003 to 0.06 s/km—carries the argument, together with a four-parameter template for high-column-density absorbers (damped Lyman-alpha systems, sub-DLAs, and Lyman-limit systems). The resolution correction that extends the emulator to small scales is a cosmology-independent ratio applied to k=0.02-0.06 s/km bins.

What would settle it

Run the two highest-resolution small-box simulations (2x512³ and 2x768³ in 15 Mpc/h) at the extremes of the emulator's A_P and thermal parameter ranges and recompute the ratio used to correct k=0.02-0.06 s/km; if the ratio changes by more than the stated ~1% at any varied parameter, the cosmology-independent assumption fails and the XQ100 posteriors would need revision.

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Extended reading notes

Core claim

The central claim is that the one-dimensional flux power spectrum (P1D) of the Lyman-alpha forest measured from high-resolution quasar spectra, when modeled with an emulator built on the PRIYA simulation suite, contains enough information to jointly constrain the primordial power spectrum parameters (A_P, n_P) and the IGM thermal history set by inhomogeneous helium reionization. Applying the emulator to the XQ100 P1D yields (A_P, n_P) posteriors consistent with the eBOSS DR14 analysis and Planck, without any external temperature prior. The same analysis applied to the KODIAQ-SQUAD P1D returns a high A_P that the paper attributes to a redshift-dependent excess of Lyman-limit systems in that d

Load-bearing premise

The small-scale emulator assumes a single, cosmology-independent resolution correction—measured in a 15 Mpc/h box—applies to the full 120 Mpc/h simulation suite at every parameter combination; if that ratio depends on cosmology or volume, the inferred amplitude, tilt, and thermal parameters are shifted.

Editorial extensions

If this is right

  • XQ100-type high-resolution P1D can supply thermal-history constraints in joint fits with eBOSS or DESI, removing the need for external IGM temperature measurements.
  • Cosmological parameters from the small-scale forest are consistent with Planck and large-volume surveys, supporting the standard cosmological model at scales down to k~6 h/Mpc⁻¹.
  • Any future small-scale Lyman-alpha dark matter analysis must marginalize over Lyman-limit system contamination, since LLSs mimic a suppression of the linear power amplitude.
  • KODIAQ-SQUAD's biased selection function means its small-scale P1D should not be used alone for cosmology above k=0.045 s/km unless the selection bias is corrected.
  • The scale separation (thermal at high k, cosmology at low k) means joint fits can be designed to isolate the two information channels.
  • The paper's finding that imposing (A_P, n_P) priors barely changes the reduced chi-squared supports the claim that cosmological and thermal parameters are largely scale-separate.

Reading between the lines

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

  • If the scale separation holds, a dedicated high-resolution survey at z<3.2 with HI-blind selection could sharpen thermal constraints without requiring exotic cosmology—a testable prediction of the paper's picture.
  • The observed LLS excess in KODIAQ-SQUAD might be verified by stacking quasar spectra or cross-correlating with LLS catalogs to measure the selection function directly, something the paper leaves for future work.
  • The cosmology-independent resolution correction could be validated by running the highest-resolution small-box simulations at varied (A_P, n_P) or thermal parameters; if the ratio changes, the reported small-scale constraints would shift.
  • The paper's suggestion that τ0 absorbs LLS saturation implies that mean-flux measurements from high-resolution surveys should be interpreted with care when used to calibrate the UV background.
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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 / 5 minor

Summary. The paper presents a cosmological analysis of high-resolution Lyman-alpha forest 1D flux power spectra (P1D) from XQ100 and KODIAQ-SQUAD, using the PRIYA multi-fidelity simulation emulator extended to k = 0.003–0.06 s/km. The inference includes cosmological parameters (A_P, n_P, h, Omega_M h^2), hydrogen and helium reionization parameters, mean optical depth parameters, and a four-parameter HCD/LLS contamination template. The authors report that the XQ100 P1D alone, without external IGM temperature data, yields (A_P, n_P) constraints consistent with eBOSS DR14 and Planck, and provides thermal-history information comparable to the eBOSS+T0 baseline. In contrast, KODIAQ-SQUAD favors a high A_P and a high LLS abundance, which the authors attribute to selection bias toward dense absorbers; restricting the analysis to z = 3.4–4.2 and k < 0.045 s/km brings it into agreement with XQ100/eBOSS. They conclude that thermal and cosmological information in the P1D are largely scale-separated and that high-resolution P1D data can serve as thermal nuisance constraints in future DESI joint fits.

Significance. If the central claims hold, this is a valuable demonstration that high-resolution P1D can simultaneously constrain the IGM thermal history and remain consistent with large-volume survey cosmology. The paper's strengths are its forward-modeling approach, the explicit validation of the likelihood on simulated data, the inclusion of a detailed HCD template, and multiple robustness checks (restricted k/z ranges, per-redshift tau_0, per-redshift alpha_LLS, MAP diagnostics). The paper is also appropriately cautious about the KODIAQ-SQUAD selection bias and about the interpretation of tau_0 as an effective nuisance parameter. The main technical risk is the unvalidated cosmology-independent resolution correction applied at exactly the scales that carry XQ100's thermal information; this is a load-bearing assumption that needs further support or sensitivity testing. Overall the manuscript is a solid contribution to the Lyman-alpha cosmology literature, conditional on resolving that point.

major comments (3)
  1. [§2.1] The resolution correction is assumed to be cosmology-independent. The emulator multiplies P1D for k = 0.02–0.06 s/km by the ratio of the two highest-resolution simulations from Ref. [63] (2×768^3 vs 2×512^3 in a 15 Mpc/h box), a ratio measured at effectively one thermodynamic/cosmological state. It is then applied to the entire prior range of Table 2, which includes large variations in HeII reionization parameters (alpha_q, z_HeII^i, z_HeII^f) and A_P. No test is shown that this ratio is universal, and its uncertainty is not propagated into the covariance of Eq. (3.1). Since the XQ100 thermal-history claim relies on k > 0.045 s/km (§5.1, Figs. 5 and 7), a parameter-dependent correction would bias the high-k bins that carry the thermal signal. I recommend either recomputing the resolution ratio at several corner points of the prior, or rerunning the inference with a deliberately varied co
  2. [§2.1 vs §3.5] There is an inconsistency in the stated k-range of the emulator vs the data cuts. Section 2.1 says the emulator predicts P1D for k = 0.003–0.06 s/km, but Section 3.5 and Table 3 use XQ100 data out to k = 0.064–0.065 s/km and KODIAQ-SQUAD out to k = 0.065 s/km. If the emulator is trained and LOO-CV-validated only up to k = 0.06, then the bins at 0.06–0.065 are outside the surrogate's domain. Please clarify whether the emulator actually covers k = 0.065, or truncate the data at k = 0.06 for consistency.
  3. [§3.1–3.2] The covariance matrix in Eq. (3.1) includes the data covariance and sample variance sigma_CV, but does not include the emulator interpolation error quoted in §2.1 (LOO-CV ~1–2%) or the resolution-correction uncertainty. While the emulator error is smaller than the diagonal statistical errors of XQ100 (~20%) and KODIAQ-SQUAD (~10%), a 1–2% systematic can bias the mean of the model when summed over many bins, and the resolution correction is an unmodeled systematic at high k. I recommend adding an emulator-error term to Eq. (3.1) or demonstrating via a sensitivity test that the posteriors are unaffected by this omission.
minor comments (5)
  1. [§2.2, Eq. (2.2)] The equation for tau_eff appears to have a redundant or misplaced tau_Kim(z) factor: the second line contains both the ratio term and a trailing tau_Kim(z), making the expression dimensionally confusing. Please rewrite for clarity.
  2. [§4.1 and Fig. 5 caption] The text in §4.1 states that LLSs have minimal damping wings, while the caption of Figure 5 attributes the large-scale boost from LLSs to 'damping wings of their absorption profiles.' These statements should be reconciled.
  3. [Abstract and §3.5] The abstract says the data probe 'down to k ~ 6 h Mpc^-1', but the analysis is primarily in s/km units. Consider stating the k-range in s/km consistently to avoid confusion.
  4. [Table 3] Several entries show double uncertainties (e.g., tau_0, n_P, A_P) without a clear definition of the two error levels. Please specify what the inner and outer errors represent (e.g., 68% and 95% credible intervals).
  5. [§5.4] The paper notes that XQ100 cannot robustly infer the peak IGM temperature at z ~ 3 because its redshift range starts at z = 3.4. This is an important limitation and should be stated earlier in the paper, ideally in the abstract or introduction.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: the analysis is a forward-model fit of an externally validated emulator to independent quasar-spectra data; self-citations are load-bearing but not circular.

full rationale

The paper's central claims are posterior constraints on cosmological and thermal parameters obtained by fitting the PRIYA emulator to the XQ100 and KODIAQ-SQUAD flux-power-spectrum measurements. These datasets are external to the PRIYA simulation suite, and the emulator is validated with leave-one-out cross-validation against high-fidelity simulations (Section 2.1, Figure 1), not by the data being fit. The consistency between XQ100 and eBOSS/Planck is therefore a genuine comparison between independent data sets, interpreted through a shared forward model, rather than a prediction that reduces to its inputs. The main self-citations (PRIYA Ref. [63], the eBOSS PRIYA analysis Ref. [74], and the multi-fidelity emulator Ref. [67]) are prior work by the same authors, but they provide the simulation model and emulator; they do not encode the XQ100 or KODIAQ-SQUAD measurements. The cosmology-independent resolution correction in Section 2.1 is an unvalidated transfer assumption that could bias high-k results, but it is a calibration from higher-resolution simulations, not a fitted parameter renamed as a prediction or a quantity defined in terms of the target result. The HCD template (Ref. [90]) is also external to the present fit. The paper explicitly acknowledges limitations of the resolution correction and HCD modeling (Sections 2.1, 3.6, 4.3.3), which strengthens rather than indicates circularity. Overall, the derivation chain is self-contained against external benchmarks, and no step reduces by construction to its own inputs. Score 1 reflects minor self-citation that is not load-bearing in a circular sense.

Assumptions & free parameters 15 free parameters · 8 assumptions · 0 invented entities

The model introduces no new particles, forces, or physical entities; it is a likelihood analysis with 15 fitted astrophysical and cosmological parameters. The most consequential ledger entries are the HCD template amplitudes (especially alpha_LLS) and the resolution correction, because the central XQ100/KODIAQ-SQUAD comparison depends on the simulation's small-scale fidelity, and the KODIAQ-SQUAD bias claim depends on the template's LLS normalization being reliable.

free parameters (15)
  • A_P = XQ100: <1.85e-9 (95% upper); KS: >2.26e-9 (95% lower); KS with eBOSS prior: (1.532+/-0.078)e-9
    Primordial power spectrum amplitude at pivot k=0.78 Mpc^-1; primary cosmological target, fitted to both datasets.
  • n_P = XQ100: 0.965+0.077/-0.030; KS: >1.01; KS with eBOSS prior: 0.992+/-0.014
    Scalar spectral index; fitted jointly with A_P.
  • tau_0 = XQ100: 1.108+0.035/-0.042; KS: 0.944+0.014/-0.017
    Mean optical depth normalization at z=3; nuisance parameter absorbing mean flux and residual HCD contamination.
  • d_tau0 = XQ100: -0.07+/-0.15; KS: 0.144+0.086/-0.044
    Redshift evolution slope of the effective optical depth; fitted nuisance parameter.
  • z_HeII_i = XQ100: not constrained; KS: >3.92; eBOSS: >4.00
    Start redshift of HeII reionization; thermal history parameter.
  • z_HeII_f = XQ100: <2.91; KS: >3.00
    End redshift of HeII reionization; thermal history parameter.
  • alpha_q = XQ100: 2.16+/-0.46; KS: <1.48
    Quasar spectral index controlling the HeII heating rate; thermal history parameter.
  • z_HI = XQ100: 7.28+0.55/-0.36; KS: <7.09
    Median redshift of hydrogen reionization; weakly constrained by P1D.
  • h (vscale) = XQ100: 0.698+/-0.010; KS: 0.695+/-0.011
    Hubble parameter; weakly constrained and mostly prior-driven (Gaussian prior mu=0.70, sigma=0.015).
  • Omega_M h^2 = XQ100: <0.143; KS: >0.143
    Matter density; weakly constrained by P1D.
  • epsilon_AGN = XQ100: 0.0495+/-0.0035; KS: 0.0483+/-0.0035
    AGN feedback thermal efficiency; constrained by Gaussian prior mu=0.05, sigma=0.005.
  • alpha_LLS = XQ100: <0.659; KS: 1.60+0.41/-0.49; KS with eBOSS prior: 2.79+/-0.41
    Amplitude of Lyman-limit system contamination relative to the HCD template; key nuisance parameter for the KODIAQ-SQUAD bias claim.
  • alpha_subDLA = XQ100: <0.200; KS: <0.171
    Sub-DLA contamination amplitude.
  • alpha_small-DLA = XQ100: <0.161; KS: <0.197
    Small-DLA contamination amplitude.
  • alpha_large-DLA = unconstrained
    Large-DLA contamination amplitude; poorly constrained because large DLAs are masked in both data and simulation.
assumptions (8)
  • domain assumption The linear primordial power spectrum is parameterized as P(k) = A_P (k / 0.78 Mpc^-1)^(n_P - 1) with a fixed pivot scale.
    Standard cosmological parameterization used in Section 2.2; assumes no running or other features in the primordial spectrum.
  • domain assumption The mean flux evolution follows the Kim et al. (2007) power law with free normalization and slope (Eq. 2.2).
    The optical depth model tau_eff is rescaled from the Kim07 redshift evolution; this empirical template is assumed to adequately capture the mean flux redshift dependence.
  • domain assumption The HCD template of Rogers et al. (2018), calibrated on Illustris simulations, describes the effect of LLS, sub-DLA, small-DLA, and large-DLA populations on the P1D.
    Used in Section 3.6 to marginalize HCD contamination. The template is external to PRIYA but has overlapping authorship; its accuracy for the real IGM is not independently verified in this paper.
  • domain assumption The HeII reionization model follows Upton Sanderbeck and Bird (2020), parameterized by z_HeII_i, z_HeII_f, and alpha_q.
    The thermal history of the IGM is generated by this specific inhomogeneous HeII reionization model; the paper does not test alternatives.
  • domain assumption The multi-fidelity emulator interpolates the P1D with ~1% accuracy at k=0.01-0.06 s/km and ~2% at z=4-4.2, and the applied resolution correction is cosmology-independent.
    Validated by leave-one-out cross-validation with only 3 HF simulations (Section 2.1); the correction ratio from small boxes is assumed to transfer to the 120 Mpc/h suite.
  • domain assumption Sample variance from the finite simulation box can be approximated by the averaged leave-one-out variance of the low-fidelity simulations (sigma_CV in Eq. 3.1).
    This approximation, inherited from Ref. [63], uses h-dependent bin shifts as a proxy for initial-phase sample variance.
  • domain assumption AGN feedback has negligible effect on the P1D at z>2 within current survey errors.
    Based on Ref. [63]; the paper uses a narrow Gaussian prior on epsilon_AGN and does not fit it freely.
  • domain assumption The KODIAQ-SQUAD selection function is biased toward DLAs and OVI absorbers, and the PRIYA LLS population is realistic enough to diagnose this bias.
    Used in Section 4.3.3 to interpret the high inferred alpha_LLS as a selection effect rather than a simulation failure; supported by CDDF comparisons but not by an explicit selection-function model.

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Cite this review

Pith. "Pith review of Small-scale Lyman alpha forest cosmology with PRIYA: Constraints from XQ100 and KODIAQ-SQUAD one-dimensional flux power spectra." pith.science (2026). https://pith.science/paper/5RSD7YX3

@misc{pith2026250918271,
  author       = {Pith},
  title        = {Pith review of: Small-scale Lyman alpha forest cosmology with PRIYA: Constraints from XQ100 and KODIAQ-SQUAD one-dimensional flux power spectra},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/5RSD7YX3}},
  note         = {Machine review of arXiv:2509.18271}
}
abstract

We present a new cosmological analysis of the small-scale Lyman alpha forest 1D flux power spectrum (P1D) using high-resolution quasar spectra from XQ100 and KODIAQ-SQUAD, interpreted through the PRIYA emulator. PRIYA is a suite of galaxy formation simulations spanning a range of cosmological and inhomogeneous HeII reionization parameters, enabling few-percent-level predictions of the P1D. These datasets, probing down to $k \sim 6\,h\,\mathrm{Mpc}^{-1}$ at $z = 2-5$, offer access to non-linear scales inaccessible to large-volume surveys like eBOSS. We find that the XQ100 P1D yields constraints on the primordial power spectrum parameters $(A_P, n_P)$ at pivot scale $k_0 = 0.78\,\mathrm{Mpc}^{-1}$ that are consistent with PRIYA results from eBOSS DR14 and Planck CMB, albeit with broader uncertainties. Notably, this is achieved without external IGM temperature data, showing that XQ100 alone provides stronger constraints on thermal history than eBOSS DR14. In contrast, the KODIAQ-SQUAD P1D favors a significantly higher $A_P$ value, driven by the selection bias toward high-column density absorbers (HCDs). We also find that the P1D at $k > 0.045\,\mathrm{s/km}$ is more sensitive to Lyman limit system contamination and thermal history. When imposing a prior on $(A_P, n_P)$, the reduced $\chi^2$ remains unchanged and the inferred mean IGM temperature is unaffected, suggesting that cosmological and thermal parameters are largely sensitive to different scales. The XQ100 P1D therefore provides complementary information on thermal nuisance parameters, which can be jointly fit with eBOSS or DESI P1D measurements to improve cosmological constraints.

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Works this paper leans on

106 extracted references · 95 linked inside Pith

  1. [63]

    S. Bird, M. Fernandez, M.-F. Ho, M. Qezlou, R. Monadi, Y. Ni et al.,PRIYA: a new suite of Lyman-αforest simulations for cosmology,JCAP2023(2023) 037 [2306.05471]

    arXiv 2023

  2. [1]

    Gunn and B.A

    J.E. Gunn and B.A. Peterson,On the Density of Neutral Hydrogen in Intergalactic Space., ApJ142(1965) 1633

    1965

  3. [2]

    Croft, D.H

    R.A.C. Croft, D.H. Weinberg, N. Katz and L. Hernquist,Recovery of the Power Spectrum of Mass Fluctuations from Observations of the LyαForest,ApJ495(1998) 44 [astro-ph/9708018]

    arXiv 1998

  4. [3]

    Theuns, A

    T. Theuns, A. Leonard, G. Efstathiou, F.R. Pearce and P.A. Thomas,P ˆ3M-SPH simulations of the Lyαforest,MNRAS301(1998) 478 [astro-ph/9805119]

    arXiv 1998

  5. [4]

    McDonald, J

    P. McDonald, J. Miralda-Escud´ e, M. Rauch, W.L.W. Sargent, T.A. Barlow, R. Cen et al., The Observed Probability Distribution Function, Power Spectrum, and Correlation Function of the Transmitted Flux in the LyαForest,ApJ543(2000) 1 [astro-ph/9911196]

    arXiv 2000

  6. [5]

    L. Hui, S. Burles, U. Seljak, R.E. Rutledge, E. Magnier and D. Tytler,On Estimating the QSO Transmission Power Spectrum,ApJ552(2001) 15 [astro-ph/0005049]

    arXiv 2001

  7. [6]

    M. Viel, S. Matarrese, H.J. Mo, M.G. Haehnelt and T. Theuns,Probing the intergalactic medium with the Lyαforest along multiple lines of sight to distant QSOs,MNRAS329(2002) 848 [astro-ph/0105233]

    arXiv 2002

  8. [7]

    Fan, M.A

    X. Fan, M.A. Strauss, R.H. Becker, R.L. White, J.E. Gunn, G.R. Knapp et al.,Constraining the Evolution of the Ionizing Background and the Epoch of Reionization with z ˜6 Quasars. II. A Sample of 19 Quasars,AJ132(2006) 117 [astro-ph/0512082]. – 31 – Parameter KODIAQ-SQUAD KODIAQ-SQUAD z= 2.6–4.2 z= 3.8–4.2 (eBOSS (Ap, nP ) prior) (eBOSS (Ap, nP ) prior) dτ...

    arXiv 2006

Show all 106 references
  1. [8]

    Viel and M.G

    M. Viel and M.G. Haehnelt,Cosmological and astrophysical parameters from the Sloan Digital Sky Survey flux power spectrum and hydrodynamical simulations of the Lymanαforest, MNRAS365(2006) 231 [astro-ph/0508177]

    2006 arXiv

  2. [10]

    McDonald, U

    P. McDonald, U. Seljak, S. Burles, D.J. Schlegel, D.H. Weinberg, R. Cen et al.,The Lyα Forest Power Spectrum from the Sloan Digital Sky Survey,ApJ Supplement163(2006) 80 [astro-ph/0405013]

    2006 arXiv

  3. [11]

    Palanque-Delabrouille, C

    N. Palanque-Delabrouille, C. Y` eche, A. Borde, J.-M. Le Goff, G. Rossi, M. Viel et al.,The one-dimensional Lyαforest power spectrum from BOSS,AAP559(2013) A85 [1306.5896]

    2013 arXiv

  4. [12]

    Slosar, V

    A. Slosar, V. Irˇ siˇ c, D. Kirkby, S. Bailey, N.G. Busca, T. Delubac et al.,Measurement of baryon acoustic oscillations in the Lyman-αforest fluctuations in BOSS data release 9,JCAP 2013(2013) 026 [1301.3459]

    2013 arXiv

  5. [13]

    Delubac, J.E

    T. Delubac, J.E. Bautista, N.G. Busca, J. Rich, D. Kirkby, S. Bailey et al.,Baryon acoustic oscillations in the Lyαforest of BOSS DR11 quasars,AAP574(2015) A59 [1404.1801]. – 32 – Figure 20. MCMC corner plot for the KODIAQ-SQUAD dataset using a mean flux model with independent...

    2015 arXiv

  6. [14]

    Chabanier, N

    S. Chabanier, N. Palanque-Delabrouille, C. Y` eche, J.-M. Le Goff, E. Armengaud, J. Bautista et al.,The one-dimensional power spectrum from the SDSS DR14 Lyαforests,JCAP2019 (2019) 017 [1812.03554]

    2019 arXiv

  7. [15]

    Abareshi, J

    B. Abareshi, J. Aguilar, S. Ahlen, S. Alam, D.M. Alexander, R. Alfarsy et al.,Overview of the Instrumentation for the Dark Energy Spectroscopic Instrument,AJ164(2022) 207 [2205.10939]

    2022 arXiv

  8. [16]

    Ravoux, M.L.A

    C. Ravoux, M.L.A. Karim, E. Armengaud, M. Walther, N. G¨ oksel Kara¸ caylı, P. Martini et al.,The Dark Energy Spectroscopic Instrument: One-dimensional power spectrum from first Lyman-αforest samples with Fast Fourier Transform,arXiv e-prints(2023) arXiv:2306.06311 – 33 – Figu...

    2023 arXiv

  9. [18]

    Kara¸ caylı, P

    N.G. Kara¸ caylı, P. Martini, J. Aguilar, S. Ahlen, E. Armengaud, S. Bailey et al.,DESI DR1 Lyα1D power spectrum: The optimal estimator measurement,arXiv e-prints(2025) arXiv:2505.07974 [2505.07974]

    2025 arXiv

  10. [19]

    Ravoux, M.-L

    C. Ravoux, M.-L. Abdul-Karim, J.-M. Le Goff, E. Armengaud, J.N. Aguilar, S. Ahlen et al., DESI DR1 Lyα1D power spectrum: The Fast Fourier Transform estimator measurement, arXiv e-prints(2025) arXiv:2505.09493 [2505.09493]. – 34 – 0.0 2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0 k [h/M...

    2025

  11. [20]

    Adame, J

    A.G. Adame, J. Aguilar, S. Ahlen, S. Alam, D.M. Alexander, M. Alvarez et al.,DESI 2024 IV: Baryon Acoustic Oscillations from the Lyman alpha forest,JCAP2025(2025) 124 [2404.03001]

    2024 arXiv

  12. [21]

    Abdul-Karim, J

    DESI Collaboration, M. Abdul-Karim, J. Aguilar, S. Ahlen, C. Allende Prieto, O. Alves et al.,DESI DR2 Results I: Baryon Acoustic Oscillations from the Lyman Alpha Forest,arXiv e-prints(2025) arXiv:2503.14739 [2503.14739]

    2025 arXiv

  13. [22]

    Viel, M.G

    M. Viel, M.G. Haehnelt and V. Springel,Inferring the dark matter power spectrum from the Lymanαforest in high-resolution QSO absorption spectra,MNRAS354(2004) 684 [astro-ph/0404600]

    2004 arXiv

  14. [23]

    McDonald, U

    P. McDonald, U. Seljak, R. Cen, D. Shih, D.H. Weinberg, S. Burles et al.,The Linear Theory Power Spectrum from the LyαForest in the Sloan Digital Sky Survey,ApJ635(2005) 761 [astro-ph/0407377]

    2005 arXiv

  15. [24]

    Viel, M.G

    M. Viel, M.G. Haehnelt and A. Lewis,The Lymanαforest and WMAP year three,MNRAS 370(2006) L51 [astro-ph/0604310]

    2006 arXiv

  16. [25]

    Seljak, A

    U. Seljak, A. Makarov, P. McDonald, S.F. Anderson, N.A. Bahcall, J. Brinkmann et al., Cosmological parameter analysis including SDSS Lyαforest and galaxy bias: Constraints on the primordial spectrum of fluctuations, neutrino mass, and dark energy,Phys. Rev. D71 (2005) 103515 [...

    2005 arXiv

  17. [26]

    Seljak, A

    U. Seljak, A. Slosar and P. McDonald,Cosmological parameters from combining the Lyman-α forest with CMB, galaxy clustering and SN constraints,JCAP2006(2006) 014 [astro-ph/0604335]

    2006 arXiv

  18. [27]

    Y` eche, N

    C. Y` eche, N. Palanque-Delabrouille, J. Baur and H. du Mas des Bourboux,Constraints on neutrino masses from Lyman-alpha forest power spectrum with BOSS and XQ-100,JCAP 2017(2017) 047 [1702.03314]. – 35 –

    2017 arXiv

  19. [28]

    Palanque-Delabrouille, C

    N. Palanque-Delabrouille, C. Y` eche, N. Sch¨ oneberg, J. Lesgourgues, M. Walther, S. Chabanier et al.,Hints, neutrino bounds, and WDM constraints from SDSS DR14 Lyman-αand Planck full-survey data,JCAP2020(2020) 038 [1911.09073]

    2020 arXiv

  20. [29]

    Garny, T

    M. Garny, T. Konstandin, L. Sagunski and M. Viel,Neutrino mass bounds from confronting an effective model with BOSS Lyman-αdata,JCAP2021(2021) 049 [2011.03050]

    2021 arXiv

  21. [30]

    Bolton, M

    J.S. Bolton, M. Viel, T.S. Kim, M.G. Haehnelt and R.F. Carswell,Possible evidence for an inverted temperature-density relation in the intergalactic medium from the flux distribution of the Lyαforest,MNRAS386(2008) 1131 [0711.2064]

    2008 arXiv

  22. [31]

    Bolton, G.D

    J.S. Bolton, G.D. Becker, M.G. Haehnelt and M. Viel,A consistent determination of the temperature of the intergalactic medium at redshift z = 2.4,MNRAS438(2014) 2499 [1308.4411]

    2014 arXiv

  23. [32]

    Nasir, J.S

    F. Nasir, J.S. Bolton and G.D. Becker,Inferring the IGM thermal history during reionization with the Lymanαforest power spectrum at redshiftz≃5,MNRAS463(2016) 2335 [1605.04155]

    2016 arXiv

  24. [33]

    Walther, J

    M. Walther, J. O˜ norbe, J.F. Hennawi and Z. Luki´ c,New Constraints on IGM Thermal Evolution from the LyαForest Power Spectrum,ApJ872(2019) 13 [1808.04367]

    2019 arXiv

  25. [35]

    X. Wu, M. McQuinn, R. Kannan, A. D’Aloisio, S. Bird, F. Marinacci et al.,Imprints of temperature fluctuations on the z∼5 Lyman-αforest: a view from radiation-hydrodynamic simulations of reionization,MNRAS490(2019) 3177 [1907.04860]

    2019 arXiv

  26. [36]

    Gaikwad, R

    P. Gaikwad, R. Srianand, M.G. Haehnelt and T.R. Choudhury,A consistent and robust measurement of the thermal state of the IGM at 2≤z≤4 from a large sample of Lyαforest spectra: evidence for late and rapid He II reionization,MNRAS506(2021) 4389 [2009.00016]

    2021 arXiv

  27. [37]

    Villasenor, B

    B. Villasenor, B. Robertson, P. Madau and E. Schneider,Inferring the Thermal History of the Intergalactic Medium from the Properties of the Hydrogen and Helium LyαForest,ApJ933 (2022) 59 [2111.00019]

    2022 arXiv

  28. [38]

    Hui and N.Y

    L. Hui and N.Y. Gnedin,Equation of state of the photoionized intergalactic medium,MNRAS 292(1997) 27 [astro-ph/9612232]

    1997 arXiv

  29. [39]

    McQuinn, A

    M. McQuinn, A. Lidz, M. Zaldarriaga, L. Hernquist, P.F. Hopkins, S. Dutta et al.,He II Reionization and its Effect on the Intergalactic Medium,ApJ694(2009) 842 [0807.2799]

    2009 arXiv

  30. [40]

    Upton Sanderbeck, A

    P.R. Upton Sanderbeck, A. D’Aloisio and M.J. McQuinn,Models of the thermal evolution of the intergalactic medium after reionization,MNRAS460(2016) 1885 [1511.05992]

    2016 arXiv

  31. [41]

    Upton Sanderbeck and S

    P. Upton Sanderbeck and S. Bird,Inhomogeneous He II reionization in hydrodynamic simulations,MNRAS496(2020) 4372 [2002.05733]

    2020 arXiv

  32. [42]

    M. Viel, J. Lesgourgues, M.G. Haehnelt, S. Matarrese and A. Riotto,Constraining warm dark matter candidates including sterile neutrinos and light gravitinos with WMAP and the Lyman-αforest,Phys. Rev. D71(2005) 063534 [astro-ph/0501562]

    2005 arXiv

  33. [43]

    Viel, G.D

    M. Viel, G.D. Becker, J.S. Bolton and M.G. Haehnelt,Warm dark matter as a solution to the small scale crisis: New constraints from high redshift Lyman-αforest data,Phys. Rev. D88 (2013) 043502 [1306.2314]

    2013 arXiv

  34. [44]

    Irˇ siˇ c, M

    V. Irˇ siˇ c, M. Viel, M.G. Haehnelt, J.S. Bolton, S. Cristiani, G.D. Becker et al.,New constraints on the free-streaming of warm dark matter from intermediate and small scale Lyman-αforest data,Phys. Rev. D96(2017) 023522 [1702.01764]. – 36 –

    2017 arXiv

  35. [45]

    Garzilli, A

    A. Garzilli, A. Magalich, O. Ruchayskiy and A. Boyarsky,How to constrain warm dark matter with the Lyman-αforest,MNRAS502(2021) 2356 [1912.09397]

    2021 arXiv

  36. [46]

    Villasenor, B

    B. Villasenor, B. Robertson, P. Madau and E. Schneider,New constraints on warm dark matter from the Lyman-αforest power spectrum,PRD108(2023) 023502 [2209.14220]

    2023 arXiv

  37. [47]

    Rogers and H.V

    K.K. Rogers and H.V. Peiris,General framework for cosmological dark matter bounds using N -body simulations,Phys. Rev. D103(2021) 043526 [2007.13751]

    2021 arXiv

  38. [48]

    Rogers and H.V

    K.K. Rogers and H.V. Peiris,Strong Bound on Canonical Ultralight Axion Dark Matter from the Lyman-Alpha Forest,Phys. Rev. L126(2021) 071302 [2007.12705]

    2021 arXiv

  39. [49]

    Font-Ribera, P

    A. Font-Ribera, P. McDonald and A. Slosar,How to estimate the 3D power spectrum of the Lyman-αforest,JCAP2018(2018) 003 [1710.11036]

    2018 arXiv

  40. [50]

    de Belsunce, O.H.E

    R. de Belsunce, O.H.E. Philcox, V. Irˇ siˇ c, P. McDonald, J. Guy and N. Palanque-Delabrouille, The 3D Lyman-αforest power spectrum from eBOSS DR16,MNRAS533(2024) 3756 [2403.08241]

    2024 arXiv

  41. [51]

    Kara¸ caylı and C.M

    N.G. Kara¸ caylı and C.M. Hirata,Light in the dark forest – I. An efficient optimal estimator for 3D Lyman-alpha forest power spectrum,arXiv e-prints(2025) arXiv:2503.15619 [2503.15619]

    2025 arXiv

  42. [52]

    Kara¸ caylı, P

    N.G. Kara¸ caylı, P. Martini, J. Guy, C. Ravoux, M.L. Abdul Karim, E. Armengaud et al., Optimal 1D Lyαforest power spectrum estimation - III. DESI early data,MNRAS528 (2024) 3941 [2306.06316]

    2024 arXiv

  43. [53]

    Irˇ siˇ c, M

    V. Irˇ siˇ c, M. Viel, T.A.M. Berg, V. D’Odorico, M.G. Haehnelt, S. Cristiani et al.,The Lyman αforest power spectrum from the XQ-100 Legacy Survey,MNRAS466(2017) 4332 [1702.01761]

    2017 arXiv

  44. [54]

    A. Day, D. Tytler and B. Kambalur,Power spectrum of the flux in the Lyman-alpha forest from high-resolution spectra of 87 QSOs,MNRAS489(2019) 2536

    2019

  45. [55]

    Kara¸ caylı, N

    N.G. Kara¸ caylı, N. Padmanabhan, A. Font-Ribera, V. Irˇ siˇ c, M. Walther, D. Brooks et al., Optimal 1D Lyαforest power spectrum estimation - II. KODIAQ, SQUAD, and XQ-100, MNRAS509(2022) 2842 [2108.10870]

    2022 arXiv

  46. [56]

    Esposito, V

    M. Esposito, V. Irˇ siˇ c, M. Costanzi, S. Borgani, A. Saro and M. Viel,Weighing cosmic structures with clusters of galaxies and the intergalactic medium,MNRAS515(2022) 857 [2202.00974]

    2022 arXiv

  47. [57]

    Boera, G.D

    E. Boera, G.D. Becker, J.S. Bolton and F. Nasir,Revealing Reionization with the Thermal History of the Intergalactic Medium: New Constraints from the LyαFlux Power Spectrum, ApJ872(2019) 101 [1809.06980]

    2019 arXiv

  48. [58]

    Wilson, V

    B. Wilson, V. Irˇ siˇ c and M. McQuinn,A measurement of the Lyβforest power spectrum and its cross with the Lyαforest in X-Shooter XQ-100,MNRAS509(2022) 2423 [2106.04837]

    2022 arXiv

  49. [59]

    Walther, N

    M. Walther, N. Sch¨ oneberg, S. Chabanier, E. Armengaud, J. Sexton, C. Y` eche et al., Emulating the Lyman-Alpha forest 1D power spectrum from cosmological simulations: new models and constraints from the eBOSS measurement,JCAP2025(2025) 099 [2412.05372]

    2025 arXiv

  50. [60]

    Cabayol-Garcia, J

    L. Cabayol-Garcia, J. Chaves-Montero, A. Font-Ribera and C. Pedersen,A neural network emulator for the Lyman-αforest 1D flux power spectrum,MNRAS525(2023) 3499 [2305.19064]

    2023 arXiv

  51. [61]

    Bird, K.K

    S. Bird, K.K. Rogers, H.V. Peiris, L. Verde, A. Font-Ribera and A. Pontzen,An emulator for the Lyman-αforest,JCAP2019(2019) 050 [1812.04654]

    2019 arXiv

  52. [62]

    Z. Jin, M. Wolfson, J.F. Hennawi and D. Gonz´ alez-Hern´ andez,Neural network emulator to constrain the high-z IGM thermal state from Lyman-αforest flux autocorrelation function, MNRAS536(2025) 2277 [2410.06505]. – 37 –

    2025 arXiv

  53. [64]

    Perdikaris, M

    P. Perdikaris, M. Raissi, A. Damianou, N.D. Lawrence and G.E. Karniadakis,Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling,Proceedings of the Royal Society of London Series A473(2017) 20160751

    2017

  54. [65]

    Peherstorfer, K

    B. Peherstorfer, K. Willcox and M. Gunzburger,Survey of multifidelity methods in uncertainty propagation, inference, and optimization,SIAM Review60(2018) 550 [https://doi.org/10.1137/16M1082469]

    2018 doi

  55. [66]

    M.-F. Ho, S. Bird and C.R. Shelton,Multifidelity emulation for the matter power spectrum using Gaussian processes,MNRAS509(2022) 2551 [2105.01081]

    2022 arXiv

  56. [67]

    Fernandez, M.-F

    M.A. Fernandez, M.-F. Ho and S. Bird,A multifidelity emulator for the Lyman-αforest flux power spectrum,MNRAS517(2022) 3200 [2207.06445]

    2022 arXiv

  57. [68]

    Y. Yang, S. Bird and M.-F. Ho,Ten-parameter simulation suite for cosmological emulation beyondΛCDM,PRD111(2025) 083529 [2501.06296]

    2025 arXiv

  58. [69]

    Diao and Y

    K. Diao and Y. Mao,Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network,arXiv e-prints(2025) arXiv:2502.04246 [2502.04246]

    2025 arXiv

  59. [70]

    Tillman, B

    M.T. Tillman, B. Burkhart, S. Tonnesen, S. Bird and G.L. Bryan,The Effects of Active Galactic Nuclei Feedback on the LyαForest Flux Power Spectrum,ApJ980(2025) 72 [2410.05383]

    2025 arXiv

  60. [71]

    M.-F. Ho, S. Bird, M.A. Fernandez and C.R. Shelton,MF-Box: multifidelity and multiscale emulation for the matter power spectrum,MNRAS526(2023) 2903 [2306.03144]

    2023 arXiv

  61. [72]

    Y. Yang, S. Bird, M.-F. Ho and M. Qezlou,Ten-dimensional neural network emulator for the nonlinear matter power spectrum,arXiv e-prints(2025) arXiv:2507.07177 [2507.07177]

    2025

  62. [73]

    Y. Yang, S. Bird, M.-F. Ho and M. Qezlou,Design and optimization of neural networks for multifidelity cosmological emulation,arXiv e-prints(2025) arXiv:2507.07184 [2507.07184]

    2025

  63. [74]

    Fernandez, S

    M.A. Fernandez, S. Bird and M.-F. Ho,Cosmological constraints from the eBOSS Lyman-α forest using the PRIYA simulations,JCAP2024(2024) 029 [2309.03943]

    2024 arXiv

  64. [75]

    Bolton and G.D

    J.S. Bolton and G.D. Becker,Resolving the high redshift Lyαforest in smoothed particle hydrodynamics simulations,MNRAS398(2009) L26 [0906.2861]

    2009 arXiv

  65. [76]

    Zhu, G.D

    Y. Zhu, G.D. Becker, S.E.I. Bosman, L.C. Keating, V. D’Odorico, R.L. Davies et al.,Long Dark Gaps in the LyβForest at z ¡ 6: Evidence of Ultra-late Reionization from XQR-30 Spectra,ApJ932(2022) 76 [2205.04569]

    2022 arXiv

  66. [77]

    Kim, J.S

    T.S. Kim, J.S. Bolton, M. Viel, M.G. Haehnelt and R.F. Carswell,An improved measurement of the flux distribution of the Lyαforest in QSO absorption spectra: the effect of continuum fitting, metal contamination and noise properties,MNRAS382(2007) 1657 [0711.1862]

    2007 arXiv

  67. [78]

    Becker, P.C

    G.D. Becker, P.C. Hewett, G. Worseck and J.X. Prochaska,A refined measurement of the mean transmitted flux in the Lyαforest over2< z <5using composite quasar spectra, MNRAS430(2013) 2067 [1208.2584]

    2013 arXiv

  68. [79]

    Torrado and A

    J. Torrado and A. Lewis,Cobaya: code for Bayesian analysis of hierarchical physical models, JCAP2021(2021) 057 [2005.05290]

    2021 arXiv

  69. [80]

    Cobaya: Bayesian analysis in cosmology

    J. Torrado and A. Lewis, “Cobaya: Bayesian analysis in cosmology.” Astrophysics Source Code Library, record ascl:1910.019, Oct., 2019

    1910

  70. [81]

    Lewis,Efficient sampling of fast and slow cosmological parameters,Phys

    A. Lewis,Efficient sampling of fast and slow cosmological parameters,Phys. Rev. D87(2013) 103529 [1304.4473]. – 38 –

    2013 arXiv

  71. [82]

    L´ opez, V

    S. L´ opez, V. D’Odorico, S.L. Ellison, G.D. Becker, L. Christensen, G. Cupani et al.,XQ-100: A legacy survey of one hundred 3.5≲z≲4.5 quasars observed with VLT/X-shooter,AAP 594(2016) A91 [1607.08776]

    2016 arXiv

  72. [83]

    Lehner, J.M

    N. Lehner, J.M. O’Meara, A.J. Fox, J.C. Howk, J.X. Prochaska, V. Burns et al.,Galactic and Circumgalactic O VI and its Impact on the Cosmological Metal and Baryon Budgets at 2 ¡ z ≲3.5,ApJ788(2014) 119 [1401.1811]

    2014 arXiv

  73. [84]

    O’Meara, N

    J.M. O’Meara, N. Lehner, J.C. Howk, J.X. Prochaska, A.J. Fox, M.A. Swain et al.,The First Data Release of the KODIAQ Survey,AJ150(2015) 111 [1505.03529]

    2015 arXiv

  74. [86]

    Murphy, G.G

    M.T. Murphy, G.G. Kacprzak, G.A.D. Savorgnan and R.F. Carswell,The UVES Spectral Quasar Absorption Database (SQUAD) data release 1: the first 10 million seconds,MNRAS 482(2019) 3458 [1810.06136]

    2019 arXiv

  75. [87]

    Vernet, H

    J. Vernet, H. Dekker, S. D’Odorico, L. Kaper, P. Kjaergaard, F. Hammer et al.,X-shooter, the new wide band intermediate resolution spectrograph at the ESO Very Large Telescope, AAP536(2011) A105 [1110.1944]

    2011 arXiv

  76. [88]

    Vogt, S.L

    S.S. Vogt, S.L. Allen, B.C. Bigelow, L. Bresee, B. Brown, T. Cantrall et al.,HIRES: the high-resolution echelle spectrometer on the Keck 10-m Telescope, inInstrumentation in Astronomy VIII, D.L. Crawford and E.R. Craine, eds., vol. 2198 ofSociety of Photo-Optical Instrumentati...

    1994

  77. [89]

    Dekker, S

    H. Dekker, S. D’Odorico, A. Kaufer, B. Delabre and H. Kotzlowski,Design, construction, and performance of UVES, the echelle spectrograph for the UT2 Kueyen Telescope at the ESO Paranal Observatory, inOptical and IR Telescope Instrumentation and Detectors, M. Iye and A.F. Moorw...

    2000

  78. [90]

    Rogers, S

    K.K. Rogers, S. Bird, H.V. Peiris, A. Pontzen, A. Font-Ribera and B. Leistedt,Simulating the effect of high column density absorbers on the one-dimensional Lymanαforest flux power spectrum,MNRAS474(2018) 3032 [1706.08532]

    2018 arXiv

  79. [91]

    Aghanim, Y

    Planck Collaboration, N. Aghanim, Y. Akrami, M. Ashdown, J. Aumont, C. Baccigalupi et al.,Planck 2018 results. VI. Cosmological parameters,Astron. Astrophys.641(2020) A6 [1807.06209]

    2018 arXiv

  80. [92]

    M.-F. Ho, S. Bird and R. Garnett,Damped Lyman-αabsorbers from Sloan digital sky survey DR16Q with Gaussian processes,MNRAS507(2021) 704 [2103.10964]

    2021 arXiv

  81. [93]

    Altay, T

    G. Altay, T. Theuns, J. Schaye, N.H.M. Crighton and C. Dalla Vecchia,Through Thick and Thin—H I Absorption in Cosmological Simulations,ApJL737(2011) L37 [1012.4014]

    2011 arXiv

  82. [94]

    Zafar, C

    T. Zafar, C. P´ eroux, A. Popping, B. Milliard, J.M. Deharveng and S. Frank,The ESO UVES advanced data products quasar sample. II. Cosmological evolution of the neutral gas mass density,AAP556(2013) A141 [1307.0602]

    2013 arXiv

  83. [95]

    Prochaska, J.M

    J.X. Prochaska, J.M. O’Meara and G. Worseck,A Definitive Survey for Lyman Limit Systems at z ˜3.5 with the Sloan Digital Sky Survey,ApJ718(2010) 392 [0912.0292]

    2010 arXiv

  84. [96]

    Rudie, C.C

    G.C. Rudie, C.C. Steidel, M. Pettini, R.F. Trainor, A.L. Strom, C.B. Hummels et al.,Column Density, Kinematics, and Thermal State of Metal-bearing Gas within the Virial Radius of z∼ 2 Star-forming Galaxies in the Keck Baryonic Structure Survey,ApJ885(2019) 61 [1903.00004]

    2019 arXiv

  85. [97]

    Kohler and N.Y

    K. Kohler and N.Y. Gnedin,Lyman Limit Systems in Cosmological Simulations,ApJ655 (2007) 685 [astro-ph/0605032]. – 39 –

    2007 arXiv

  86. [98]

    J. Fan, H. Zhu, C. Avestruz and N.Y. Gnedin,Cosmic Reionization on Computers: Statistics, Physical Properties, and Environments of Lyman Limit Systems at z∼6,ApJ963(2024) 45 [2212.07033]

    2024 arXiv

  87. [99]

    Georgiev, G

    I. Georgiev, G. Mellema and S.K. Giri,The forest at EndEoR: the effect of Lyman limit systems on the end of reionization,MNRAS536(2025) 3689 [2405.04273]

    2025 arXiv

  88. [100]

    McQuinn, S.P

    M. McQuinn, S.P. Oh and C.-A. Faucher-Gigu` ere,On Lyman-limit Systems and the Evolution of the Intergalactic Ionizing Background,ApJ743(2011) 82 [1101.1964]

    2011 arXiv

  89. [101]

    D’Aloisio, M

    A. D’Aloisio, M. McQuinn, H. Trac, C. Cain and A. Mesinger,Hydrodynamic Response of the Intergalactic Medium to Reionization,ApJ898(2020) 149 [2002.02467]

    2020 arXiv

  90. [102]

    O’Meara, N

    J.M. O’Meara, N. Lehner, J.C. Howk, J.X. Prochaska, A.J. Fox, M.S. Peeples et al.,The Second Data Release of the KODIAQ Survey,AJ154(2017) 114 [1707.07905]

    2017 arXiv

  91. [103]

    Fumagalli, S

    M. Fumagalli, S. Fotopoulou and L. Thomson,Detecting neutral hydrogen at z≳3 in large spectroscopic surveys of quasars,MNRAS498(2020) 1951 [2009.03322]

    2020 arXiv

  92. [104]

    Rogers and V

    K.K. Rogers and V. Poulin,5σtension between Planck cosmic microwave background and eBOSS Lyman-alpha forest and constraints on physics beyondΛCDM,Physical Review Research7(2025) L012018 [2311.16377]

    2025 arXiv

  93. [105]

    Brodzeller, M

    A. Brodzeller, M. Wolfson, D.M. Santos, M. Ho, T. Tan, M.M. Pieri et al.,Construction of the Damped LyαAbsorber Catalog for DESI DR2 LyαBAO,arXiv e-prints(2025) arXiv:2503.14740 [2503.14740]

    2025 arXiv

  94. [106]

    Irˇ siˇ c, M

    V. Irˇ siˇ c, M. Viel, M.G. Haehnelt, J.S. Bolton, M. Molaro, E. Puchwein et al.,Unveiling dark matter free streaming at the smallest scales with the high redshift Lyman-alpha forest,PRD 109(2024) 043511 [2309.04533]

    2024 arXiv

  95. [107]

    Bruna and S

    J. Bruna and S. Mallat,Invariant Scattering Convolution Networks,arXiv e-prints(2012) arXiv:1203.1513 [1203.1513]

    2012 arXiv

  96. [108]

    Anden and S

    J. Anden and S. Mallat,Deep Scattering Spectrum,IEEE Transactions on Signal Processing 62(2014) 4114 [1304.6763]

    2014 arXiv

  97. [109]

    Andreux, T

    M. Andreux, T. Angles, G. Exarchakis, R. Leonarduzzi, G. Rochette, L. Thiry et al.,Kymatio: Scattering Transforms in Python,arXiv e-prints(2018) arXiv:1812.11214 [1812.11214]

    2018 arXiv

  98. [110]

    Tohfa, S

    H.M. Tohfa, S. Bird, M.-F. Ho, M. Qezlou and M. Fernandez,Forecast Cosmological Constraints with the 1D Wavelet Scattering Transform and the Lyman-αForest,PRL132 (2024) 231002 [2310.06010]. – 40 –

    2024

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