Pith. sign in

REVIEW 2 major objections 5 minor 3 cited by

Constraints on the state of the IGM at $z\sim 8-10$ using redshifted 21-cm observations with LOFAR

T0 review · 2 major / 5 minor · reviewed 2026-08-16 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read With 140 hours of LOFAR data at redshifts 8.3–10.1, only extreme reionization histories — sparse, bright sources carving rare large ionized or heated regions — are disfavoured, leaving ordinary reionization models untouched.

desk verdict First interpretation of the new LOFAR multi-redshift upper limits, but the headline IGM bounds are mostly prior-driven, as the paper's own Appendix A control shows. read the letter →

arxiv 2505.00373 v1 pith:GSGCAO33 submitted 2025-05-01 astro-ph.CO

R. Ghara , S. Zaroubi , B. Ciardi , G. Mellema , S. K. Giri , F. G. Mertens , M. Mevius , L. V. E. Koopmans
show 16 more authors
I. T. Iliev A. Acharya S. A. Brackenhoff E. Ceccotti K. Chege I. Georgiev S. Ghosh I. Hothi C. Höfer Q. Ma S. Munshi A. R. Offringa A. K. Shaw V. N. Pandey S. Yatawatta M. Choudhury
This is my paper · ORCID
classification astro-ph.CO
keywords epochofreionization21-cmpowerspectrumLOFARintergalacticmediumBayesianinferenceradiativetransferexcessradiobackgroundIGMtemperatureandionizationconstraints
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 asks what the intergalactic medium (IGM) looked like at $z \sim 8$–$10$, using LOFAR's newest 140-hour upper limits on the 21-cm power spectrum at $z = 8.3$, $9.1$ and $10.1$. The authors build a database of $10^5$ reionization simulations with the one-dimensional radiative-transfer code GRIZZLY, explore five source parameters with a Bayesian exclusion likelihood, and report which IGM states are disfavoured rather than favoured. Their central finding is that only extreme reionization histories — a sparse population of bright sources that carve out rare, large ionized or heated regions — are excluded, and that a completely neutral and unheated IGM is still consistent with the data. In a model with an excess radio background, the 95 (68) per cent disfavoured credible intervals at $z = 9.1$ correspond to ionized and heated fractions below $0.46$ ($\lesssim 0.05$), gas temperatures below $44$ ($4$) K, and heated-region sizes below $14$ ($3$) $h^{-1}\,\mathrm{Mpc}$. The upshot is that the strongest current 21-cm measurement still cannot tell ordinary reionization apart from exotic scenarios, but the same machinery is ready to turn deeper limits into genuine constraints on the first billion years.

What carries the argument

The carrying mechanism is the pairing of a simulation database with an exclusion likelihood. GRIZZLY, a one-dimensional radiative-transfer code, converts $N$-body halo catalogs into 21-cm brightness-temperature cubes; here it is run for $10^5$ combinations of five source parameters — ionization efficiency $\zeta$, minimum UV-halo mass $M_{\rm min}$, minimum X-ray-halo mass $M_{\rm min,X}$, X-ray heating efficiency $f_X$, and excess-radio-background efficiency $A_r$ — building an interpolated grid of power spectra and derived IGM quantities. A Markov chain then evaluates, at every step, the likelihood that a model is excluded by the LOFAR limits, formed from the product of error functions comparing the observed upper limits with the interpolated model spectrum at the three largest observed scales, with a conservative 30 per cent modelling error added in quadrature and a Thomson-scattering optical-depth prior capping $x_{\rm HII}$. The reported IGM parameters ($x_{\rm HII}$, $T_{\rm K}$, $\delta T_b$, $f_{\rm heat}$, $R_{\rm heat}^{\rm peak}$, $\Delta R_{\rm heat}^{\rm FWHM}$) are read off the same interpolated database, which is why the IGM constraints inherit the source-prior dependence that Appendix A exposes.

What would settle it

Re-run the $10^5$-model database with a full three-dimensional radiative-transfer code on the same five-parameter grid and repeat the MCMC: if the model power spectra shift by more than the assumed 30 per cent modelling error at $k \approx 0.076$–$0.133\,h\,\mathrm{Mpc}^{-1}$ in any region of parameter space, the disfavoured intervals move. Observationally, the paper's own Appendix C provides a sharper test: the bias-corrected upper limit of $(25\,\mathrm{mK})^2$ at $k = 0.075\,h\,\mathrm{Mpc}^{-1}$, $z = 9.1$, already lies below the power spectrum of a completely neutral, unheated IGM, so independently verifying that bias correction would immediately remove the paper's last surviving extreme-but-allowed scenario.

Watch

Extended reading notes

Core claim

The paper claims that the LOFAR upper limits of Mertens et al. (2025) at $z = 8.3$, $9.1$ and $10.1$ exclude a well-defined but narrow set of intergalactic-medium states, namely the extreme end of the model space. In the model with a free excess radio background, the disfavoured models at $z = 9.1$ have, at 68 (95) per cent credibility, volume-averaged ionized fraction $x_{\rm HII} \lesssim 0.02$ ($0.46$), neutral-gas temperature $T_{\rm K} \lesssim 4.4$ ($44$) K, heated-region volume fraction $f_{\rm heat} \lesssim 0.05$ ($0.46$), and characteristic heated-region size $R_{\rm heat}^{\rm peak} \lesssim 3$ ($14$) $h^{-1}\,\mathrm{Mpc}$. The 68 per cent interval on the disfavoured models sits at an excess-radio-background efficiency $A_r \gtrsim 4.6$, i.e. an excess background more than 100 per cent of the CMB at 1.42 GHz, while the 95 per cent interval on $A_r$ spans the entire prior range. A completely neutral and unheated IGM at $z \approx 9$ remains consistent with the data. The authors present these numbers as probabilistic statements about models disfavoured by upper limits rather than detections, and they emphasize that the intervals inherit a strong dependence on the chosen source-parameter priors.

Load-bearing premise

The entire exclusion likelihood is computed from power spectra produced by GRIZZLY's one-dimensional radiative transfer, and the paper itself notes that the code's agreement with a full three-dimensional scheme is verified only for scenarios with gas much hotter than the CMB, not for models with significant spin-temperature fluctuations, so any systematic error there would shift the quoted disfavoured IGM states.

Editorial extensions

If this is right

  • The completely neutral, unheated IGM at $z \approx 9$ remains consistent with the data; the paper estimates that 2–3 times more integration would be needed before LOFAR rules even that baseline scenario out.
  • The excluded models are extreme patchy-reionization and patchy-heating scenarios in which rare sources (minimum halo masses $\gtrsim 10^{10}\,M_\odot$) with large efficiencies create high-contrast, large ionized or heated regions; mainstream reionization histories are untouched.
  • An excess radio background of 100–207 per cent of the CMB at 1.42 GHz is disfavoured at 68 per cent credibility across $z = 8.3$–$10.1$, but the 95 per cent interval spans the whole prior range, so the radio-background question stays open.
  • Including other interferometers' upper limits — dominated by HERA at $z \approx 8$ and $10$ — substantially enlarges the disfavoured region, with HERA alone excluding a neutral, unheated IGM at $z \approx 8$ at $2\sigma$; LOFAR still dominates at $z \approx 9$.
  • The joint-redshift analysis gives a consistent redshift evolution of the disfavoured states ($x_{\rm HII} < 0.85$, $0.46$, $0.17$ at $z = 8.3$, $9.1$, $10.1$ at 95 per cent credibility), although it assumes redshift-independent source parameters and is dominated by the strongest limit.

Reading between the lines

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

  • The paper's own Appendix A control run — replacing the LOFAR likelihood with a constant — leaves the posteriors of $x_{\rm HII}$, $f_{\rm heat}$ and $T_{\rm K}$ nearly unchanged; a fair reading is that those three headline bounds are largely inherited from the source-parameter priors, while the information actually coming from the data sits in $\delta T_b$ and the heated-region size statistics.
  • Because the 95 per cent credible interval of the radio-background efficiency spans the full prior, the current data cannot separate a CMB-only sky from an excess-background sky; the paper cites the disputed ARCADE2 and LWA1 excess as the motivation for $A_r$, so a direct measurement of the sky-averaged radio temperature at tens of MHz would break this degeneracy more cheaply than additional 21-cm
  • The sharpest discriminating scale is $k \approx 0.076$–$0.133\,h\,\mathrm{Mpc}^{-1}$; if LOFAR reaches the factor-of-two sensitivity gain that the paper says is required to test the neutral-unheated baseline, the qualitative 'extreme models only' conclusion should harden into a quantitative floor on the global ionized fraction, a prediction checkable with the next round of limits.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

2 major / 5 minor

Summary. This paper uses the recent LOFAR upper limits on the 21-cm power spectrum at z = 8.3, 9.1 and 10.1 (Mertens et al. 2025) together with GRIZZLY simulations and a Bayesian MCMC framework to identify reionization models that are disfavoured by the data. The authors explore two source-model scenarios, one with no excess radio background (Ar = 0) and one with a variable excess radio background (Varying Ar), using both single-redshift and joint-redshift likelihoods. They derive credible intervals for the IGM parameters of the disfavoured models, with headline numbers at z = 9.1 in the Varying Ar case: xHII ≲ 0.02 (0.46), TK ≲ 4.4 (44) K, and fheat ≲ 0.05 (0.46) at 68 (95) per cent. The paper also repeats the analysis including upper limits from other interferometers and, in an appendix, applies the framework to the stronger upper limits of Acharya et al. (2024c).

Significance. If the quoted IGM intervals were genuinely set by the LOFAR upper limits, this would be an important step in using 21-cm observations to characterize the IGM during reionization. The paper is commendably transparent about its methodology: it uses a public MCMC sampler, provides an appendix that tests the effect of removing the LOFAR likelihood, and explicitly warns that the IGM constraints may be affected by source-parameter priors. However, the no-LOFAR control in Appendix A shows that for the Ar = 0 scenario the tight low-xHII and low-TK intervals are essentially unchanged when the LOFAR likelihood is replaced by a constant, so those particular bounds are not produced by the data. Because the abstract cites numbers from the Varying Ar scenario, for which no control is given, the central quantitative claim is not fully supported. The qualitative finding that the disfavoured models are extreme, with rare and large ionized or heated regions, is more robust and is a useful step toward exploiting 21-cm upper limits.

major comments (2)
  1. [Abstract; Sect. 3.2; Appendix A] The no-LOFAR control in Appendix A shows that for the Ar = 0 scenario the 68% (95%) disfavoured intervals for xHII and TK are xHII ≲ 0.024 (0.56) and TK ≲ 7.2 (618) K, whereas the LOFAR-based results in Table 5 are xHII ≲ 0.13 (0.55) and TK ≲ 7.3 (21) K. Thus the tight low-xHII and low-TK bounds are essentially the prior distribution of source parameters mapped through GRIZZLY, not a result of the LOFAR upper limits. The abstract's headline numbers, however, are taken from the Varying Ar scenario (Table 7), for which no corresponding control is presented. Given the Ar = 0 control, it is likely that the xHII and TK intervals in the Varying Ar case are also prior-dominated. The authors should either present the no-LOFAR control for the Varying Ar scenario, or explicitly state in the abstract and conclusions that the quantitative xHII, fheat and TK intervals are set by the source-parameter priors and are not direct LOFAR constraints.
  2. [Sect. 2.2.5, note 15] The authors state that "we do not have robust accuracy estimates of GRIZZLY for scenarios with TS fluctuations." The exclusion likelihood in Eqs. (3) and (4) is evaluated entirely from GRIZZLY power spectra, and the Varying Ar scenario is precisely one in which spin-temperature fluctuations can be significant because Tγ,eff can approach or exceed TS. A systematic error in GRIZZLY at the k-bins used in the analysis (0.076–0.133 h/Mpc) would directly shift the inferred disfavoured IGM parameter regions. The adopted 30% modelling error is added in quadrature per k-bin and does not account for possible correlated, shape-dependent errors across k-bins. I recommend a robustness test in which the modelling error is increased (e.g., to 50%) or a comparison with a 3D radiative-transfer scheme is carried out for a few representative Varying Ar models, in order to demonstrate that the qualitative and quantitative conclusions are stable.
minor comments (5)
  1. [Appendix A; Abstract] The abstract cites the IGM bounds from the Varying Ar case without referencing the prior-dominated nature established in Appendix A for the Ar = 0 case; a sentence in the abstract acknowledging that these numbers are strongly prior-dependent would be more accurate.
  2. [Figs. B.1–B.4] The axis labels in Figures B.1–B.4 use "Rpeak (cMpc)" and "RFWHM (cMpc)", while Table 3 and the main text define Rheat_peak and ΔRheat_FWHM in units of h⁻¹ Mpc; these units should be made consistent.
  3. [Fig. 3] The axis label "log10(Rheat_FHWM)" contains a typo; it should read "Rheat_FWHM".
  4. [Sect. 4] The text contains a typo: "databse" should be "database".
  5. [General] The term "disfavoured credible intervals" is non-standard because credible intervals usually describe a posterior distribution of the parameters. Since the posterior here is a prior-weighted distribution of models with high exclusion likelihood, the paper should more explicitly define this quantity at first use to avoid confusion with standard Bayesian constraints on the IGM.

Circularity Check

1 steps flagged · score 6.0 of 10

IGM-state bounds in the abstract are largely a prior pushforward: Appendix A's constant-likelihood control reproduces the xHII and TK credible intervals, so key 'LOFAR constraints' reduce to the chosen source priors.

  1. other [Appendix A (no-LOFAR control) vs Sec. 3.1 Table 5, Sec. 3.2 Table 7, and Abstract; see also Sec. 2.2.5 and Sec. 4.]
    "We fix to 0.5 the exclusion likelihood shown in Eqs. (3) and (4), independently from the LOFAR upper limits, but still use the priors on the maximum value of xHII, and we denote this as the no-LOFAR scenario. ... the posterior distribution of the disfavoured IGM parameter values is entirely determined by the chosen priors on the source parameters. ... The disfavoured models have xHII ≲ 0.024 (0.56), T K ≲ 7.2 (618) K, no constraints on fheat ... at 68 (95) per cent credible intervals for the Single-z no-LOFAR analysis case."

    The control sets Lex=0.5, removing all LOFAR information; the IGM posterior is then by construction the pushforward of the uniform source priors through GRIZZLY. For Ar=0 Single-z z=9.1 this no-LOFAR run gives xHII ≲ 0.024 (0.56) and TK ≲ 7.2 K at 68 (95)%, while the LOFAR-based Table 5 gives xHII ≲ 0.13 (0.55) and TK 68% ≲ 7.3 K. The 95% xHII and 68% TK limits are identical to the prior-only values; the paper itself says 'the constraints on xHII, fheat and T K are significantly affected by the chosen priors on the source parameters.' The abstract's Varying Ar headline xHII/TK intervals lie in the same prior-dominated regime (no Varying Ar control is shown), so these reported 'IGM constraints from LOFAR' reduce to the source-prior input.

full rationale

The paper's numerical IGM-state constraints are obtained by drawing source parameters from uniform priors and mapping them through GRIZZLY to derived IGM quantities. Appendix A demonstrates that with the LOFAR likelihood set to Lex=0.5, the xHII and TK credible intervals are nearly unchanged from the LOFAR-based values for the Ar=0 Single-z case; hence those specific constraints reduce by construction to the source-prior distribution and not to the 21-cm observations. The paper is transparent about this ('the constraints on xHII, fheat and T K are significantly affected by the chosen priors'), and the qualitative finding that only extreme models with rare, large regions are disfavoured may survive, so this is a partial circularity rather than a fabricated result. The self-citations to GRIZZLY and the earlier framework are not independently load-bearing here: GRIZZLY is the simulation engine, its validation limitations are disclosed, and the LOFAR data come from an observational analysis; those are correctness/robustness risks, not circularity. The central quantitative 'IGM constraints' in the abstract and Tables 5/7, however, are substantially a re-labelling of the source priors for the parameters the paper highlights, which merits a score of 6.

Assumptions & free parameters 6 free parameters · 7 assumptions · 0 invented entities

The central inference is conditional on the GRIZZLY source model and the chosen uniform prior ranges. The paper demonstrates in Appendix A that the constraints on xHII, fheat and TK are almost entirely prior-driven. No new physical entities are introduced; the excess radio background Ar is adopted from prior literature (Fialkov & Barkana 2019; Mondal et al. 2020) and motivated by LWA1 and ARCADE2 measurements.

free parameters (6)
  • log10(ionization efficiency zeta) prior range = [-3, 3]
    Uniform prior in log space; the disfavoured constraints on zeta and derived IGM limits depend on this range.
  • log10(X-ray efficiency fX) prior range = [-3, 3]
    Uniform prior; affects heating and the 21-cm power spectrum amplitude.
  • log10(Mmin) prior range = [9, 12] in log10(M/M_sun)
    Minimum mass of UV-emitting halos; the prior strongly controls whether models have rare, large bubbles.
  • log10(Mmin,X) prior range = [9, 12] in log10(M/M_sun)
    Minimum mass of X-ray-emitting halos; controls the rarity and size of heated regions.
  • Radio background efficiency Ar prior range = [0, 416]
    Excess radio background amplitude; the 68% disfavoured lower bound Ar > 4.6 is the basis for the claim of an excess above 100% of the CMB, while the 95% interval spans the full prior.
  • Modelling error fraction = 0.3 (30%)
    Ad hoc choice for Delta^2_m,err added in quadrature to the observational error; affects the width of the exclusion likelihood.
assumptions (7)
  • domain assumption GRIZZLY 1D radiative transfer accurately predicts 21-cm power spectra across the explored parameter space
    Section 2.2.5 note 15 states the comparison with C2RAY is limited to TS >> T_gamma scenarios and that robust accuracy estimates are lacking for TS-fluctuation scenarios. The exclusion likelihood depends directly on these simulated spectra.
  • domain assumption Spin temperature equals gas kinetic temperature (TS = TK)
    Section 2.2.3 assumes strong Ly-alpha coupling at z=8-10; if the coupling is weaker, the conversion between power spectrum amplitude and gas temperature is invalid.
  • domain assumption Source parameters are redshift independent
    Required for the Joint-z likelihood (Eq. 4); the paper cautions that the joint analysis should be interpreted with care (Sect. 2.2.5).
  • domain assumption Uniform excess radio background
    Section 2.2.2 states 'we adopt a uniform radio background, but the presence of inhomogeneities could enhance the amplitude of the 21-cm signal power spectrum above our estimates'.
  • ad hoc to paper Stepwise reionization history for the Thomson optical depth prior
    Section 2.2.5 assumes neutral until z_i, partially ionized at xHII_max until z=6, then fully ionized; yields xHII_max = 1, 0.79, 0.57 at z=8.3, 9.1, 10.1.
  • domain assumption Stellar mass fraction f_star = 0.02
    Section 2.2.2, fixed based on literature; the ionizing emissivity scales with stellar mass.
  • standard math WMAP cosmology (Omega_m=0.27, Omega_L=0.73, Omega_B=0.044, h=0.7)
    Used in Eq. (2) and in the N-body simulation; consistent with the simulation inputs.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Constraints on the state of the IGM at $z\sim 8-10$ using redshifted 21-cm observations with LOFAR." pith.science (2026). https://pith.science/paper/GSGCAO33

@misc{pith2026250500373,
  author       = {Pith},
  title        = {Pith review of: Constraints on the state of the IGM at $z\sim 8-10$ using redshifted 21-cm observations with LOFAR},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/GSGCAO33}},
  note         = {Machine review of arXiv:2505.00373}
}
abstract

The power spectra of the redshifted 21-cm signal from the Epoch of Reionization (EoR) contain information about the ionization and thermal states of the intergalactic medium (IGM), and depend on the properties of the EoR sources. Recently, Mertens et al 2025 has analysed 10 nights of LOFAR high-band data and estimated upper limits on the 21-cm power spectrum at redshifts 8.3, 9.1 and 10.1. Here we use these upper limit results to constrain the properties of the IGM at those redshifts. We focus on the properties of the ionized and heated regions where the temperature is larger than that of the CMB. We model the 21-cm power spectrum with the code GRIZZLY, and use a Bayesian inference framework to explore the source parameters for uniform priors on their ranges. The framework also provides information about the IGM properties in the form of derived parameters. In a model which includes a radio background in excess of the CMB, the 95 (68) per cent credible intervals of disfavoured models at redshift 9.1 for the chosen priors correspond to IGM states with averaged ionization and heated fraction below 0.46 ($\lesssim 0.05$), an average gas temperature below 44 K (4 K), and a characteristic size of the heated region $\lesssim 14 ~h^{-1} ~\mathrm{Mpc}$ ($\lesssim 3 ~h^{-1} ~\mathrm{Mpc}$). The 68 per cent credible interval suggests an excess radio background which is more than 100 per cent of the CMB at 1.42 GHz, while the 95 per cent credible interval of the radio background efficiency parameter spans the entire prior range. The behaviour of the credible intervals is similar at all redshifts. The models disfavoured by the LOFAR upper limits are extreme ones, as they are mainly driven by rare and large ionized or heated regions.

Figures

Figures reproduced from arXiv: 2505.00373 by the authors.

Figure 1
Figure 1. A set of 1000 power spectra randomly chosen out of the 105 sim￾ulated ones. Panels from top to bottom refer to z = 8.3, 9.1 and 10.1, re￾spectively. These power spectra correspond to the scenario with no addi￾tional radio background other than the CMB (Ar = 0). The down arrow points refer to the recent LOFAR 1σ upper limit (∆ 2 21(k,z)±∆ 2 21,err (k,z)) from Mertens et al. (2025). As a reference, the dashed line cor… view at source ↗
Figure 2
Figure 2. Histogram of the disfavoured values of the source parameters for the scenario with Ar = 0. These correspond to the models with power spectra values larger than ∆ 2 21(k,z)−∆ 2 21,err (k,z) in at least one k−bin, i.e. which have a high probability of being ruled out by the recent LOFAR 1σ upper limits (∆ 2 21(k,z) ± ∆ 2 21,err (k,z)) from Mertens et al. (2025). heated IGM, obtained assuming constant values of xHI = 1… view at source ↗
Figure 3
Figure 3. Histogram of the disfavoured values of the IGM parameters for the scenario with Ar = 0. These correspond to the same set of models considered in [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figures from the paper (7 more)
Figure 4
Figure 4. Figure 4: Posterior distribution of the source parameters of the models which are disfavoured by the LOFAR upper limits from Mertens et al. (2025) at z = 9.1 for the Ar = 0 scenario. Red refers to the case when each redshift is considered separately (Single-z) at z =9.1, while b…
Figure 6
Figure 6. Figure 6: Posterior distribution of the IGM parameters of the models which are disfavoured by the LOFAR upper limits from Mertens et al. (2025) at z = 9.1 for the Ar = 0 scenario. Red refers to the case when z = 9.1 is considered separately (Single-z), while blue represents the …
Figure 7
Figure 7. Figure 7: shows the posterior distribution of the five param￾eters for the disfavoured models at z = 9.1. For the Single-z approach, the 68 per cent disfavoured credible intervals limits are ζ ≲ 2.4, Mmin ≳ 1.7 × 1010 M⊙, Mmin,X ≳ 1.6 × 1010 M⊙, fX ≲ 5.2 and Ar ≳ 4.6 (see [PITH…
Figure 8
Figure 8. Figure 8: Posterior distribution of the IGM parameters of the models which are disfavoured by the LOFAR upper limits from Mertens et al. (2025) at z = 9.1 for the Varying Ar scenario. Red refers to the case when each redshift is considered separately (Single-z), while blue repre…
Figure 10
Figure 10. Figure 10: Marginalized probability distribution of the disfavoured mod￾els’ source parameters at z ∼ 8, 9 and 10 when including upper limits from different radio interferometric observations. The results are for the Ar = 0 scenario. The black, red and green curves refer to the …
Figure 9
Figure 9. Figure 9: A set of 1000 power spectra randomly chosen out of the 105 simulated ones for the scenario with no additional radio background other than the CMB (Ar = 0). Panels from top to bottom refer to z = 8.3, 9.1 and 10.1, respectively. The dashed lines correspond to the power …
Figure 11
Figure 11. Figure 11: Marginalized probability distribution of the IGM parameters of the disfavoured models at z ∼ 9 when including upper limits from different radio interferometric observations. The results are for the Ar = 0 scenario. The red and blue curves refer to the Single-z and Joi…

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. When galaxies burst II. Implications of enhanced burstiness for the 21-cm Cosmic Dawn signal

    astro-ph.CO 2026-07 conditional novelty 6.0 of 10

    Bursty star formation adds a shot-noise-like term to the Cosmic Dawn 21-cm power spectrum, boosting it by factors of a few at the Wouthuysen-Field trough and strongly on small scales at high redshift.

  2. Rapid late-time reionization: constraints and cosmological implications

    astro-ph.CO 2025-08 conditional novelty 6.0 of 10

    Reionization is inferred to be rapid and late (midpoint z≈7, duration Δz50≈1.1), yielding an optical depth τ=0.0492 from Lyman-alpha + BAO + BBN, independent of CMB data.

  3. Improved upper limits on the 21-cm signal power spectrum at $z=17.0$ and $z=20.3$ from an optimal field observed with NenuFAR

    astro-ph.CO 2025-07 conditional novelty 6.0 of 10

    NenuFAR observations of the NT04 field set the deepest 21-cm power spectrum upper limits to date at z=20.3 and z=17.0, with the z=20.3 limit more than an order of magnitude deeper than any previous Cosmic Dawn limit.

Reference graph

Works this paper leans on

150 extracted references · 60 canonical work pages · cited by 3 Pith papers

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archiveprefix author booktitle chapter edition editor howpublished institution eprint journal key month note number organization pages publisher school series title type volume year label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts #0 'before.all := #1 ...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 global.max substring 't := if while FUNCTION word.in bbl.in " " * FUNCTION format....

  3. [3]

    Abdurashidova, T. H. C. Z., Adams, T., Aguirre, J. E., et al. 2023, The Astrophysical Journal, 945, 124

    2023

  4. [4]

    E., Alexander , P., et al

    Abdurashidova , Z., Aguirre , J. E., Alexander , P., et al. 2022, , 924, 51

    2022

  5. [5]

    K., et al

    Acharya , A., Ma , Q.-b., Giri , S. K., et al. 2024 a , arXiv e-prints, arXiv:2410.11620

    arXiv 2024

  6. [6]

    2024 b , , 527, 7835

    Acharya , A., Mertens , F., Ciardi , B., et al. 2024 b , , 527, 7835

    2024

  7. [7]

    2024 c , , 534, L30

    Acharya , A., Mertens , F., Ciardi , B., et al. 2024 c , , 534, L30

    2024

  8. [8]

    S., Parsons , A

    Ali , Z. S., Parsons , A. R., Zheng , H., et al. 2015, , 809, 61

    2015

Show all 150 references
  1. [9]

    P., Mazzucchelli , C., et al

    Ba \ n ados , E., Venemans , B. P., Mazzucchelli , C., et al. 2018, , 553, 473

    2018

  2. [10]

    2018, , 555, 71

    Barkana , R. 2018, , 555, 71

    2018

  3. [11]

    & Loeb , A

    Barkana , R. & Loeb , A. 2001, , 349, 125

    2001

  4. [12]

    & Loeb , A

    Barkana , R. & Loeb , A. 2005, , 626, 1

    2005

  5. [13]

    F., & Pober , J

    Barry , N., Hazelton , B., Sullivan , I., Morales , M. F., & Pober , J. C. 2016, , 461, 3135

    2016

  6. [14]

    M., et al

    Barry , N., Wilensky , M., Trott , C. M., et al. 2019, , 884, 1

    2019

  7. [15]

    P., Hazelton , B

    Beardsley , A. P., Hazelton , B. J., Sullivan , I. S., et al. 2016, , 833, 102

    2016

  8. [16]

    D., Bolton, J

    Becker, G. D., Bolton, J. S., Madau, P., et al. 2015, MNRAS, 447, 3402

    2015

  9. [17]

    D., Davies , F

    Becker , G. D., Davies , F. B., Furlanetto , S. R., et al. 2018, , 863, 92

    2018

  10. [18]

    Behroozi , P. S. & Silk , J. 2015, , 799, 32

    2015

  11. [19]

    K., & Samui , S

    Bera , A., Ghara , R., Chatterjee , A., Datta , K. K., & Samui , S. 2023, Journal of Astrophysics and Astronomy, 44, 10

    2023

  12. [20]

    Bernardi , G., Zwart , J. T. L., Price , D., et al. 2016, , 461, 2847

    2016

  13. [21]

    & Brown , M

    Bonaldi , A. & Brown , M. L. 2015, , 447, 1973

    2015

  14. [22]

    Bowman , J. D. & Rogers , A. E. E. 2010, , 468, 796

    2010

  15. [23]

    D., Rogers , A

    Bowman , J. D., Rogers , A. E. E., Monsalve , R. A., Mozdzen , T. J., & Mahesh , N. 2018, , 555, 67

    2018

  16. [24]

    F., Tauscher , K., Rapetti , D., & Burns , J

    Bradley , R. F., Tauscher , K., Rapetti , D., & Burns , J. O. 2019, , 874, 153

    2019

  17. [25]

    2023, The Astrophysical Journal Letters, 948, L14

    Castellano, M., Fontana, A., Treu, T., et al. 2023, The Astrophysical Journal Letters, 948, L14

    2023

  18. [26]

    R., Koopmans , L

    Ceccotti , E., Offringa , A. R., Koopmans , L. V. E., et al. 2025, arXiv e-prints, arXiv:2502.18459

    2025 arXiv

  19. [27]

    B., et al

    Chapman , E., Zaroubi , S., Abdalla , F. B., et al. 2016, , 458, 2928

    2016

  20. [28]

    R., & Hutter , A

    Chatterjee , A., Dayal , P., Choudhury , T. R., & Hutter , A. 2019, , 487, 3560

    2019

  21. [29]

    R., & Schneider , R

    Chatterjee , A., Dayal , P., Choudhury , T. R., & Schneider , R. 2020, , 496, 1445

    2020

  22. [30]

    R., Kolopanis , M., et al

    Cheng , C., Parsons , A. R., Kolopanis , M., et al. 2018, , 868, 26

    2018

  23. [31]

    2024, arXiv e-prints, arXiv:2407.03523

    Choudhury , M., Ghara , R., Zaroubi , S., et al. 2024, arXiv e-prints, arXiv:2407.03523

    2024 arXiv

  24. [32]

    Cohen , A., Fialkov , A., Barkana , R., & Monsalve , R. A. 2020, , 495, 4845

    2020

  25. [33]

    D., & Carilli , C

    Datta , A., Bowman , J. D., & Carilli , C. L. 2010, , 724, 526

    2010

  26. [34]

    K., Bharadwaj , S., & Choudhury , T

    Datta , K. K., Bharadwaj , S., & Choudhury , T. R. 2007, , 382, 809

    2007

  27. [35]

    de Lera Acedo , E., de Villiers , D. I. L., Razavi-Ghods , N., et al. 2022, Nature Astronomy, 6, 984

    2022

  28. [36]

    R., Parsons , A

    DeBoer , D. R., Parsons , A. R., Aguirre , J. E., et al. 2017, Publications of the Astronomical Society of the Pacific, 129, 045001

    2017

  29. [37]

    T., McLeod, D

    Donnan, C. T., McLeod, D. J., Dunlop, J. S., et al. 2022, , 518, 6011–6040

    2022

  30. [38]

    & Taylor , G

    Dowell , J. & Taylor , G. B. 2018, , 858, L9

    2018

  31. [39]

    Draine , B. T. & Miralda-Escud \'e , J. 2018, , 858, L10

    2018

  32. [40]

    W., Anderson , M

    Eastwood , M. W., Anderson , M. M., Monroe , R. M., et al. 2019, , 158, 84

    2019

  33. [41]

    W., de Gasperin , F., & Rafferty , D

    Edler , H. W., de Gasperin , F., & Rafferty , D. 2021, , 652, A37

    2021

  34. [42]

    B., Ciardi , B., Graziani , L., et al

    Eide , M. B., Ciardi , B., Graziani , L., et al. 2020, , 498, 6083

    2020

  35. [43]

    B., & Hennawi , J

    Eilers , A.-C., Davies , F. B., & Hennawi , J. F. 2018, , 864, 53

    2018

  36. [44]

    S., Liu, A., & Hewitt, J

    Ewall-Wice, A., Dillon, J. S., Liu, A., & Hewitt, J. 2017, Monthly Notices of the Royal Astronomical Society, 470, 1849

    2017

  37. [45]

    2016, , 458, 2710

    Ewall-Wice , A., Hewitt , J., Mesinger , A., et al. 2016, , 458, 2710

    2016

  38. [46]

    A., Becker , R

    Fan , X., Strauss , M. A., Becker , R. H., et al. 2006, , 132, 117

    2006

  39. [47]

    & Barkana , R

    Fialkov , A. & Barkana , R. 2019, , 486, 1763

    2019

  40. [48]

    2018, Physical Review Letters, 121, 011101

    Fialkov , A., Barkana , R., & Cohen , A. 2018, Physical Review Letters, 121, 011101

    2018

  41. [49]

    J., Kogut , A., Levin , S., et al

    Fixsen , D. J., Kogut , A., Levin , S., et al. 2011, , 734, 5

    2011

  42. [50]

    R., Oh , S

    Furlanetto , S. R., Oh , S. P., & Briggs , F. H. 2006, , 433, 181

    2006

  43. [51]

    Gan , H., Koopmans , L. V. E., Mertens , F. G., et al. 2022, , 663, A9

    2022

  44. [52]

    G., Koopmans , L

    Gan , H., Mertens , F. G., Koopmans , L. V. E., et al. 2023, , 669, A20

    2023

  45. [53]

    Gao , L.-Y., Koopmans , L. V. E., Mertens , F. G., et al. 2024, arXiv e-prints, arXiv:2412.16853

    2024 arXiv

  46. [54]

    K., Mertens , F

    Gehlot , B. K., Mertens , F. G., Koopmans , L. V. E., et al. 2019, , 488, 4271

    2019

  47. [55]

    R., & Datta , K

    Ghara , R., Choudhury , T. R., & Datta , K. K. 2015 a , , 447, 1806

    2015

  48. [56]

    R., & Datta , K

    Ghara , R., Choudhury , T. R., & Datta , K. K. 2016, , 460, 827

    2016

  49. [57]

    R., Datta , K

    Ghara , R., Choudhury , T. R., Datta , K. K., & Choudhuri , S. 2017, , 464, 2234

    2017

  50. [58]

    K., & Choudhury , T

    Ghara , R., Datta , K. K., & Choudhury , T. R. 2015 b , , 453, 3143

    2015

  51. [59]

    K., Ciardi , B., Mellema , G., & Zaroubi , S

    Ghara , R., Giri , S. K., Ciardi , B., Mellema , G., & Zaroubi , S. 2021, , 503, 4551

    2021

  52. [60]

    K., Mellema , G., et al

    Ghara , R., Giri , S. K., Mellema , G., et al. 2020, , 493, 4728

    2020

  53. [61]

    & Mellema , G

    Ghara , R. & Mellema , G. 2020, , 492, 634

    2020

  54. [62]

    K., et al

    Ghara , R., Mellema , G., Giri , S. K., et al. 2018, , 476, 1741

    2018

  55. [63]

    2022, , 2022, 055

    Ghara , R., Mellema , G., & Zaroubi , S. 2022, , 2022, 055

    2022

  56. [64]

    K., Zaroubi , S., et al

    Ghara , R., Shaw , A. K., Zaroubi , S., et al. 2024, , 687, A252

    2024

  57. [65]

    S., & Chengalur , J

    Ghosh , A., Prasad , J., Bharadwaj , S., Ali , S. S., & Chengalur , J. N. 2012, , 426, 3295

    2012

  58. [66]

    K., D'Aloisio , A., Mellema , G., et al

    Giri , S. K., D'Aloisio , A., Mellema , G., et al. 2019 a , , 2019, 058

    2019

  59. [67]

    K., Mellema , G., Aldheimer , T., Dixon , K

    Giri , S. K., Mellema , G., Aldheimer , T., Dixon , K. L., & Iliev , I. T. 2019 b , , 489, 1590

    2019

  60. [68]

    Greig , B., Mesinger , A., Koopmans , L. V. E., et al. 2021, , 501, 1

    2021

  61. [69]

    2009, , 397, 1138

    Harker , G., Zaroubi , S., Bernardi , G., et al. 2009, , 397, 1138

    2009

  62. [70]

    T., et al

    Harnois-D \'e raps , J., Pen , U.-L., Iliev , I. T., et al. 2013, , 436, 540

    2013

  63. [71]

    D., & Puchwein , E

    Hills , R., Kulkarni , G., Meerburg , P. D., & Puchwein , E. 2018, , 564, E32

    2018

  64. [72]

    2013, , 208, 19

    Hinshaw , G., Larson , D., Komatsu , E., et al. 2013, , 208, 19

    2013

  65. [73]

    R., et al

    Hothi , I., Chapman , E., Pritchard , J. R., et al. 2021, , 500, 2264

    2021

  66. [74]

    M., Cowie , L

    Hu , E. M., Cowie , L. L., Barger , A. J., et al. 2010, , 725, 394

    2010

  67. [75]

    R., & Nath , B

    Islam , N., Ghara , R., Paul , B., Choudhury , T. R., & Nath , B. B. 2019, , 487, 2785

    2019

  68. [76]

    2010, , 409, 1647

    Jeli \'c , V., Zaroubi , S., Labropoulos , P., et al. 2010, , 409, 1647

    2010

  69. [77]

    S., Parsons , A

    Kern , N. S., Parsons , A. R., Dillon , J. S., et al. 2019, , 884, 105

    2019

  70. [78]

    S., Parsons , A

    Kern , N. S., Parsons , A. R., Dillon , J. S., et al. 2020, , 888, 70

    2020

  71. [79]

    C., Cheng , C., et al

    Kolopanis , M., Jacobs , D. C., Cheng , C., et al. 2019, , 883, 133

    2019

  72. [80]

    2015, in Proceedings of Advancing Astrophysics with the Square Kilometre Array — PoS(AASKA14), AASKA14 (Sissa Medialab)

    Koopmans, L., Pritchard, J., Mellema, G., et al. 2015, in Proceedings of Advancing Astrophysics with the Square Kilometre Array — PoS(AASKA14), AASKA14 (Sissa Medialab)

    2015

  73. [81]

    M., Zaroubi , S., & Abdalla , F

    Krause , F., Thomas , R. M., Zaroubi , S., & Abdalla , F. B. 2018, , 64, 9

    2018

  74. [82]

    & Bridle , S

    Lewis , A. & Bridle , S. 2002, , 66, 103511

    2002

  75. [83]

    R., & Trott , C

    Liu , A., Parsons , A. R., & Trott , C. M. 2014, , 90, 023019

    2014

  76. [84]

    2023, , 522, 3284

    Ma , Q.-B., Ghara , R., Ciardi , B., et al. 2023, , 522, 3284

    2023

  77. [85]

    Madau , P., Meiksin , A., & Rees , M. J. 1997, , 475, 429

    1997

  78. [86]

    R., Mellema , G., et al

    Mao , Y., Shapiro , P. R., Mellema , G., et al. 2012, , 422, 926

    2012

  79. [87]

    2015, Advancing Astrophysics with the Square Kilometre Array (AASKA14), 10

    Mellema , G., Koopmans , L., Shukla , H., et al. 2015, Advancing Astrophysics with the Square Kilometre Array (AASKA14), 10

    2015

  80. [88]

    Mellema , G., Koopmans , L. V. E., Abdalla , F. A., et al. 2013, Experimental Astronomy, 36, 235

    2013

  81. [89]

    G., Bobin , J., & Carucci , I

    Mertens , F. G., Bobin , J., & Carucci , I. P. 2024, , 527, 3517

    2024

  82. [90]

    G., Ghosh , A., & Koopmans , L

    Mertens , F. G., Ghosh , A., & Koopmans , L. V. E. 2018, , 478, 3640

    2018

  83. [91]

    G., Mevius , M., Koopmans , L

    Mertens , F. G., Mevius , M., Koopmans , L. V. E., et al. 2020, , 493, 1662

    2020

  84. [92]

    G., Mevius , M., Koopmans , L

    Mertens , F. G., Mevius , M., Koopmans , L. V. E., et al. 2025, arXiv e-prints, arXiv:2503.05576

    2025 arXiv

  85. [93]

    & Furlanetto , S

    Mesinger , A. & Furlanetto , S. 2007, , 669, 663

    2007

  86. [94]

    Mevius , M., Mertens , F., Koopmans , L. V. E., et al. 2022, , 509, 3693

    2022

  87. [95]

    N., et al

    Mevius , M., van der Tol , S., Pandey , V. N., et al. 2016, Radio Science, 51, 927

    2016

  88. [96]

    2012, , 419, 2095

    Mineo , S., Gilfanov , M., & Sunyaev , R. 2012, , 419, 2095

    2012

  89. [97]

    B., Furlanetto , S

    Mirocha , J., Mu \ n oz , J. B., Furlanetto , S. R., Liu , A., & Mesinger , A. 2022, , 514, 2010

    2022

  90. [98]

    2020, , 498, 4178

    Mondal , R., Fialkov , A., Fling , C., et al. 2020, , 498, 4178

    2020

  91. [99]

    A., Altamirano, C., Bidula, V., et al

    Monsalve, R. A., Altamirano, C., Bidula, V., et al. 2024, Monthly Notices of the Royal Astronomical Society, 530, 4125–4147

    2024

  92. [100]

    A., Fialkov , A., Bowman , J

    Monsalve , R. A., Fialkov , A., Bowman , J. D., et al. 2019, , 875, 67

    2019

  93. [101]

    A., Rogers , A

    Monsalve , R. A., Rogers , A. E. E., Bowman , J. D., & Mozdzen , T. J. 2017, , 835, 49

    2017

  94. [102]

    M., Mason, C

    Morales, A. M., Mason, C. A., Bruton, S., et al. 2021, ApJ, 919, 120

    2021

  95. [103]

    J., Warren , S

    Mortlock , D. J., Warren , S. J., Venemans , B. P., et al. 2011, , 474, 616

    2011

  96. [104]

    Mu \ n oz , J. B. & Loeb , A. 2018, , 557, 684

    2018

  97. [105]

    G., Koopmans , L

    Munshi , S., Mertens , F. G., Koopmans , L. V. E., et al. 2025, arXiv e-prints, arXiv:2503.21728

    2025 arXiv

  98. [106]

    G., Koopmans , L

    Munshi , S., Mertens , F. G., Koopmans , L. V. E., et al. 2024, , 681, A62

    2024

  99. [107]

    2019, , 2019, 051

    Nebrin , O., Ghara , R., & Mellema , G. 2019, , 2019, 051

    2019

  100. [108]

    R., Mertens, F., & Koopmans, L

    Offringa, A. R., Mertens, F., & Koopmans, L. V. E. 2019, Monthly Notices of the Royal Astronomical Society, 484, 2866

    2019

  101. [109]

    G., Bandura , K., et al

    Paciga , G., Albert , J. G., Bandura , K., et al. 2013, , 433, 639

    2013

  102. [110]

    2019, , 484, 933

    Park, J., Mesinger, A., Greig, B., & Gillet, N. 2019, , 484, 933

    2019

  103. [111]

    R., Liu , A., Aguirre , J

    Parsons , A. R., Liu , A., Aguirre , J. E., et al. 2014, , 788, 106

    2014

  104. [112]

    H., Yatawatta , S., Koopmans , L

    Patil , A. H., Yatawatta , S., Koopmans , L. V. E., et al. 2017, , 838, 65

    2017

  105. [113]

    H., Yatawatta, S., Zaroubi, S., et al

    Patil, A. H., Yatawatta, S., Zaroubi, S., et al. 2016, Monthly Notices of the Royal Astronomical Society, 463, 4317

    2016

  106. [114]

    2015, , 801, 138

    Patra , N., Subrahmanyan , R., Sethi , S., Udaya Shankar , N., & Raghunathan , A. 2015, , 801, 138

    2015

  107. [115]

    C., et al

    Philip, L., Abdurashidova, Z., Chiang, H. C., et al. 2018, Probing Radio Intensity at high-Z from Marion: 2017 Instrument

    2018

  108. [116]

    2020, , 641, A6

    Planck Collaboration , Aghanim , N., Akrami , Y., et al. 2020, , 641, A6

    2020

  109. [117]

    C., Greenhill , L

    Price , D. C., Greenhill , L. J., Fialkov , A., et al. 2018, , 478, 4193

    2018

  110. [118]

    Pritchard , J. R. & Loeb , A. 2012, Reports on Progress in Physics, 75, 086901

    2012

  111. [119]

    2020, , 499, 5993

    Reis , I., Fialkov , A., & Barkana , R. 2020, , 499, 5993

    2020

  112. [120]

    E., Dixon , K

    Ross , H. E., Dixon , K. L., Ghara , R., Iliev , I. T., & Mellema , G. 2019, , 487, 1101

    2019

  113. [121]

    E., Giri , S

    Ross , H. E., Giri , S. K., Mellema , G., et al. 2021, , 506, 3717

    2021

  114. [122]

    K., & Schneider , A

    Schaeffer , T., Giri , S. K., & Schneider , A. 2024, , 110, 023543

    2024

  115. [123]

    K., & Mirocha , J

    Schneider , A., Giri , S. K., & Mirocha , J. 2021, , 103, 083025

    2021

  116. [124]

    R., Giroux , M

    Shapiro , P. R., Giroux , M. L., & Babul , A. 1994, , 427, 25

    1994

  117. [125]

    T., Subrahmanyan , R., et al

    Singh , S., Jishnu , N. T., Subrahmanyan , R., et al. 2022, Nature Astronomy, 6, 607

    2022

  118. [126]

    & Subrahmanyan , R

    Singh , S. & Subrahmanyan , R. 2019, , 880, 26

    2019

  119. [127]

    2017, , 845, L12

    Singh , S., Subrahmanyan , R., Udaya Shankar , N., et al. 2017, , 845, L12

    2017

  120. [128]

    & Mesinger , A

    Sobacchi , E. & Mesinger , A. 2013, , 432, L51

    2013

  121. [129]

    E., Wayth , R

    Sokolowski , M., Tremblay , S. E., Wayth , R. B., et al. 2015, , 32, e004

    2015

  122. [130]

    Spinelli, M., Bernardi, G., & Santos, M. G. 2018, Monthly Notices of the Royal Astronomical Society, 479, 275

    2018

  123. [131]

    & Hernquist , L

    Springel , V. & Hernquist , L. 2003, , 339, 312

    2003

  124. [132]

    & Cowsik , R

    Subrahmanyan , R. & Cowsik , R. 2013, , 776, 42

    2013

  125. [133]

    & Furlanetto , S

    Sun , G. & Furlanetto , S. R. 2016, , 460, 417

    2016

  126. [134]

    P., Chen , Z., et al

    Tang , M., Stark , D. P., Chen , Z., et al. 2023, , 526, 1657

    2023

  127. [135]

    Thomas , R. M. & Zaroubi , S. 2008, , 384, 1080

    2008

  128. [136]

    Thomas , R. M. & Zaroubi , S. 2011, , 410, 1377

    2011

  129. [137]

    M., Zaroubi , S., Ciardi , B., et al

    Thomas , R. M., Zaroubi , S., Ciardi , B., et al. 2009, , 393, 32

    2009

  130. [138]

    J., Goeke , R., Bowman , J

    Tingay , S. J., Goeke , R., Bowman , J. D., et al. 2013, Publications of the Astronomical Society of Australia (PASA), 30, 7

    2013

  131. [139]

    M., Jordan , C

    Trott , C. M., Jordan , C. H., Midgley , S., et al. 2020, , 493, 4711

    2020

  132. [140]

    P., Wise, M

    van Haarlem, M. P., Wise, M. W., Gunst, A. W., et al. 2013, Astronomy & Astrophysics, 556, A2

    2013

  133. [141]

    P., Ba \ n ados , E., Decarli , R., et al

    Venemans , B. P., Ba \ n ados , E., Decarli , R., et al. 2015, , 801, L11

    2015

  134. [142]

    E., et al

    Virtanen , P., Gommers , R., Oliphant , T. E., et al. 2020, Nature Methods, 17, 261

    2020

  135. [143]

    C., Natarajan , A., J \'a uregui Garc \' a , J

    Voytek , T. C., Natarajan , A., J \'a uregui Garc \' a , J. M., Peterson , J. B., & L \'o pez-Cruz , O. 2014, , 782, L9

    2014

  136. [144]

    A., Iliev, I

    Watson, W. A., Iliev, I. T., D’Aloisio, A., et al. 2013, , 433, 1230

    2013

  137. [145]

    & Zarantonello, S

    Weiser, A. & Zarantonello, S. E. 1988, Mathematics of Computation, 50, 189

    1988

  138. [146]

    J., Morales, M

    Wilensky, M. J., Morales, M. F., Hazelton, B. J., et al. 2019, Publications of the Astronomical Society of the Pacific, 131, 114507

    2019

  139. [147]

    2024, Nature Astronomy, 8, 384–396

    Witten, C., Laporte, N., Martin-Alvarez, S., et al. 2024, Nature Astronomy, 8, 384–396

    2024

  140. [148]

    & Banerjee, P

    Yatawatta, S. & Banerjee, P. 2011, 2011 XXXth URSI General Assembly and Scientific Symposium

    2011

  141. [149]

    2013, in Astrophysics and Space Science Library, Vol

    Zaroubi , S. 2013, in Astrophysics and Space Science Library, Vol. 396, The First Galaxies, ed. T. Wiklind , B. Mobasher , & V. Bromm , 45

    2013

  142. [150]

    The Impact of the Ionosphere on Ground-based Detection of the Global Epoch of Reionization Signal

    @ARTICLE Sokolowski2015ApJ...813...18S, author = Sokolowski , M. and Wayth , R. B. and Tremblay , S. E. and Tingay , S. J. and Waterson , M. and Tickner , J. and Emrich , D. and Schlagenhaufer , F. and Kenney , D. and Padhi , S. , title = " The Impact of the Ionosphere on Grou...

    2015 arXiv

Pith tools

Reviewed August 16, 2026 · model on record in the stance chip above.