REVIEW 1 major objections 2 minor 1 cited by
HI Simulations for Cosmology with the SKA Observatory
T0 review · 1 major / 2 minor · reviewed 2026-06-25 · grok-4.3
Pith's one-line read Semi-analytical and empirical models agree on cosmic HI density but differ systematically in the HI-halo mass relation and its redshift evolution.
desk verdict A useful but narrow inter-model comparison of HI predictions that flags differences in halo relations without new methods or broad validation. read the letter →
The pith
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
The reading
What carries the argument
The direct comparison of semi-analytical models that self-consistently evolve baryonic components within dark matter merger trees against empirical schemes based on fast approximations for large ensemble studies.
What would settle it
New HI observations that either remove the reported systematic differences in the HI-halo mass relation across redshifts or produce substantially larger discrepancies than those identified in the comparison.
Extended reading notes
Core claim
By comparing the predictions from the different methods considered, we find overall consistency in integrated quantities such as Ω_HI, yet systematic differences in the detailed shape and scatter of the HI--halo mass relation and its redshift evolution. Semi-analytical models offer physically grounded predictions but depend on assumed prescriptions, while empirical methods provide flexibility and computational efficiency at the expense of robustness in extrapolated regions of the parameter space.
Load-bearing premise
The collection of semi-analytical and empirical models examined is representative enough of plausible physical assumptions to support general statements about differences between the two classes.
Editorial extensions
If this is right
- New HI measurements will supply critical observational constraints to refine and calibrate current simulation methodologies.
- Increasingly realistic HI simulations will help interpret data and guide survey design and analysis strategies.
- Integrated quantities such as the cosmic HI density remain robust across modeling approaches.
- The detailed HI-halo mass relation and its evolution require further calibration because different methods produce systematic variations in shape and scatter.
Reading between the lines
- If future data favor one class of models over the other in the scatter at fixed halo mass, that could guide which approach to prioritize for volume-limited forecasts.
- Empirical models might be adjusted using semi-analytical outputs in well-constrained regimes to combine speed with physical insight for very large mock catalogs.
- Differences in redshift evolution could alter predictions for how HI traces the growth of cosmic structure at higher redshifts.
Signed reviews
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript provides a comparative overview of semi-analytical and empirical methods for modeling neutral hydrogen (HI) distribution in the post-reionization Universe in preparation for SKAO surveys. It assesses how different physical and empirical assumptions affect predictions for key observables including the cosmic HI density Ω_HI, the HI mass function, and the HI-halo mass relation. The central finding is overall consistency across methods in integrated quantities such as Ω_HI, accompanied by systematic differences in the detailed shape, scatter, and redshift evolution of the HI-halo mass relation.
Significance. If the reported class-level differences hold after addressing model selection, the work would help quantify modeling uncertainties relevant to interpreting SKA precursor data from MeerKAT, ASKAP, and FAST and to guiding SKAO survey design. The explicit contrast between physically motivated but prescription-dependent semi-analytical models and computationally efficient but less robust empirical schemes identifies where future observations can provide calibration.
major comments (1)
- [Model selection and comparison sections] The headline claim of systematic differences between the semi-analytical and empirical classes (abstract and concluding discussion) is load-bearing for the paper's utility, yet rests on the untested assumption that the finite set of examined models spans the dominant physical variations within each class. The manuscript does not demonstrate coverage of key variants such as alternative feedback implementations or HI assignment schemes, leaving open the possibility that reported differences are model-specific rather than class-wide.
minor comments (2)
- The abstract would be strengthened by stating the exact number of models in each category and the redshift range over which the comparisons are performed.
- Figure captions comparing the HI-halo mass relation should explicitly label which curves correspond to semi-analytical versus empirical approaches and note any shared parameter choices.
Simulated Author's Rebuttal
We thank the referee for the constructive report and the recommendation for major revision. We address the major comment point by point below, proposing targeted revisions to clarify the scope of our model comparison while preserving the paper's core findings on consistency in integrated quantities and differences in the HI-halo mass relation.
read point-by-point responses
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Referee: [Model selection and comparison sections] The headline claim of systematic differences between the semi-analytical and empirical classes (abstract and concluding discussion) is load-bearing for the paper's utility, yet rests on the untested assumption that the finite set of examined models spans the dominant physical variations within each class. The manuscript does not demonstrate coverage of key variants such as alternative feedback implementations or HI assignment schemes, leaving open the possibility that reported differences are model-specific rather than class-wide.
Authors: We agree that the manuscript should more explicitly address the rationale and limitations of model selection. The models examined are the primary state-of-the-art examples used in the SKAO preparation literature, chosen because they represent the dominant semi-analytical frameworks (varying in merger-tree evolution and baryonic prescriptions) and empirical schemes (differing in observable-based HI assignments) available at the time of writing. Nevertheless, we acknowledge that the comparison does not exhaustively sample all possible variants. In revision, we will add a dedicated paragraph to the model selection section discussing the criteria for inclusion, noting unexamined alternatives such as different AGN feedback implementations or alternative HI partitioning schemes, and qualifying that the reported class-level trends are based on the models considered. We will also revise the abstract and concluding discussion to state that systematic differences are observed among the examined models, while the consistency in Ω_HI holds across them. These changes will be made without expanding the model set, as the work is a comparative overview rather than a comprehensive parameter survey. revision: yes
Circularity Check
No circularity: inter-model comparison without derivation chain
full rationale
The paper is a comparative overview of existing semi-analytical and empirical HI modeling methods, reporting consistency in integrated quantities like Ω_HI and differences in the HI-halo mass relation shape and evolution. No new derivation, prediction, or first-principles result is claimed that reduces by construction to fitted inputs, self-citations, or ansatzes defined inside the paper. The central claims rest on direct inter-model comparisons rather than any load-bearing step that equates output to input. This is self-contained against external benchmarks and matches the expected honest non-finding for such survey-style work.
Assumptions & free parameters
Cite this review
Pith. "Pith review of HI Simulations for Cosmology with the SKA Observatory." pith.science (2026). https://pith.science/paper/2EVIXQNA
@misc{pith2026260625969,
author = {Pith},
title = {Pith review of: HI Simulations for Cosmology with the SKA Observatory},
year = {2026},
howpublished = {\url{https://pith.science/paper/2EVIXQNA}},
note = {Machine review of arXiv:2606.25969}
}
abstract
We present a comparative overview of state-of-the-art methods for modelling the distribution of neutral hydrogen (HI) in the post-reionization Universe, developed in preparation for upcoming SKAO cosmological surveys. Our aim is to assess how different physical and empirical assumptions reflect into predictions for key observables such as the cosmic HI density, the HI mass function, and the HI-halo mass relation. We consider both: (i) semi-analytical approaches that self-consistently evolve baryonic components within dark matter merger trees through physically motivated prescriptions and (ii) empirical schemes tailored to different observables and based on fast approximations designed for large ensemble studies. By comparing the predictions from the different methods considered, we find overall consistency in integrated quantities such as $\Omega_{\mathrm{HI}}$, yet systematic differences in the detailed shape and scatter of the HI--halo mass relation and its redshift evolution. Semi-analytical models offer physically grounded predictions but depend on assumed prescriptions, while empirical methods provide flexibility and computational efficiency at the expense of robustness in extrapolated regions of the parameter space. The increasing number of HI measurements from SKA precursors and pathfinders (including surveys with MeerKAT, ASKAP, and FAST) will provide critical observational constraints to refine and calibrate current simulation methodologies. In turn, increasingly realistic HI simulations play a key role in interpreting these data, guiding survey design and analysis strategies, in preparation for the advent of SKAO data.
Figures
Figures from the paper (2 more)
Forward citations
Cited by 1 Pith paper
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meer21cm: an Analysis Pipeline and Comprehensive Toolkit for HI Intensity Mapping
meer21cm is a publicly available Python toolkit for post-calibration analysis of single-dish HI intensity mapping surveys, achieving percent-level accuracy on simulated MeerKAT data in the k range 0.02-0.2 h/Mpc.
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Reviewed June 25, 2026 · model on record in the stance chip above.
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