Pith. sign in

REVIEW 2 minor 2 cited by

Methodological Frontiers in 21-cm Intensity Mapping: the Treatment of Systematics and Foreground Contamination

T0 review · 0 major / 2 minor · reviewed 2026-06-26 · grok-4.3

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

Pith's one-line read Developing robust algorithms for instrumental effects and sky-model uncertainties is essential to exploit the cosmological potential of HI intensity-mapping surveys with SKA-Mid.

desk verdict This is a competent review chapter that gathers simulation results on map-making and component separation for 21cm intensity mapping but adds no new methods or tests. read the letter →

arxiv 2606.27244 v1 pith:M34FIPMA submitted 2026-06-25 astro-ph.CO

Marta Spinelli , Matilde Barberi-Squarotti , José Luis Bernal , Somnath Bharadwaj , Victor Bonjean , Philip Bull , Carmelita Carbone , Isabella P. Carucci
show 24 more authors
Stefano Camera Suman Chatterjee Tianyue Chen Zhaoting Chen Samir Choudhuri Devin Crichton Steven Cunnington Bianca De Caro Khandakar Md Asif Elahi Jose Fonseca Athanasia Gkogkou Abhik Ghosh Keith Grainge Wenkai Hu Melis O. Irfan Yichao Li Siyambonga Matshawule Geoff Murphy Simon Prunet Mario G. Santos Jean-Luc Starck Jingying Wang Laura Wolz Zheng Zhang
This is my paper · ORCID
classification astro-ph.CO
keywords 21-cmintensitymappingforegroundcontaminationinstrumentalsystematicscomponentseparationmap-makingSKA-MidHIcosmology
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 reviews recent advances in map-making and component-separation techniques for 21-cm intensity mapping. It focuses on handling telescope-specific systematics such as beam response and correlated noise, tested in controlled simulation environments. Isolating the faint 21 cm signal from much stronger astrophysical foregrounds is challenging but necessary for using HI as a cosmological probe up to redshift 3 with SKA-Mid. The review provides a framework for assessing strengths and limitations of different approaches to prepare for real observations.

What carries the argument

Map-making and component-separation techniques that account for beam response, correlated noise, and sky-model uncertainties.

What would settle it

A direct comparison of foreground removal performance between the reviewed simulation-based methods and actual SKA-Mid observations that reveals large discrepancies due to unmodeled effects.

Watch

Extended reading notes

Core claim

The distribution of neutral hydrogen traces large-scale structure, but extracting the 21 cm signal requires overcoming foregrounds orders of magnitude stronger and instrumental systematics. Advances in data-analysis techniques, particularly map-making and component separation tailored to SKA-Mid specifics, have been developed and tested in simulations over the past decade.

Load-bearing premise

That results from controlled simulation environments accurately predict performance on real SKA-Mid observations, where unmodeled sky-model uncertainties and instrumental effects may differ from the simulated cases.

Editorial extensions

If this is right

  • These techniques enable isolation of the 21 cm signal without introducing biases in cosmological measurements.
  • Simulations offer a framework to evaluate and improve different data-analysis approaches before real data arrives.
  • Accurate handling of systematics supports use of HI intensity mapping to probe dark matter and dark energy.
  • Ongoing innovations in these methods are required to maximize the scientific return from SKA-Mid surveys.

Reading between the lines

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

  • Methods that perform well in simulations may require additional calibration steps when applied to real data containing effects absent from the models.
  • Combining these intensity-mapping techniques with other large-scale structure probes could tighten constraints on cosmological parameters.
  • The same simulation-testing approach could be adapted for other radio intensity-mapping experiments beyond SKA.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Request a human review

A listed scientist reviews the paper for a fee and the review publishes here regardless of verdict. See the reviewers or get listed.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

0 major / 2 minor

Summary. The manuscript is a review chapter summarizing recent advances in map-making and component-separation techniques for single-dish 21-cm intensity mapping with SKA-Mid. It emphasizes challenges from astrophysical foregrounds (orders of magnitude brighter than the HI signal) and instrumental systematics such as beam response and correlated noise. The review focuses exclusively on results obtained in controlled simulation environments and concludes that developing robust algorithms to handle instrumental effects and sky-model uncertainties is a crucial preparatory step for exploiting the cosmological potential of HI intensity-mapping surveys.

Significance. If the review accurately and comprehensively captures the simulation-based literature, it provides a useful consolidated framework for assessing the strengths and limitations of different foreground-mitigation and systematics-handling approaches. This is valuable for the 21-cm community preparing for SKA-Mid observations, even though the paper presents no new derivations, quantitative forecasts, or real-data results.

minor comments (2)
  1. [Abstract] Abstract: the statement that the 21 cm signal is 'several orders of magnitude weaker' than foregrounds would benefit from a specific numerical range (e.g., 10^4–10^6) with a supporting reference to set expectations for readers.
  2. The manuscript should explicitly state the time period covered by the 'past decade' review (e.g., 2014–2024) and list the key simulation pipelines or codes whose results are synthesized, to improve reproducibility of the literature survey.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for their positive assessment of the manuscript as a useful consolidated framework for the 21-cm community and for recommending minor revision. No specific major comments were provided in the report.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: review paper with no derivations or predictions

full rationale

This is a literature review summarizing map-making and component-separation methods tested in controlled simulations. It contains no original equations, derivations, fitted parameters, or quantitative predictions that could reduce to inputs by construction. The central claim—that developing robust algorithms is a crucial preparatory step—is a qualitative statement about the field, not a result derived from any internal logic or self-citation chain. No load-bearing steps match the enumerated circularity patterns.

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

As an abstract-only review of existing methods, no new free parameters, axioms, or invented entities are introduced by this paper itself; it relies on standard assumptions from radio astronomy and cosmology literature.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Methodological Frontiers in 21-cm Intensity Mapping: the Treatment of Systematics and Foreground Contamination." pith.science (2026). https://pith.science/paper/M34FIPMA

@misc{pith2026260627244,
  author       = {Pith},
  title        = {Pith review of: Methodological Frontiers in 21-cm Intensity Mapping: the Treatment of Systematics and Foreground Contamination},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/M34FIPMA}},
  note         = {Machine review of arXiv:2606.27244}
}
abstract

The distribution of neutral hydrogen (HI) in the post-reionization universe traces the cosmic large-scale structure and therefore serves as a powerful cosmological probe. An efficient way to measure its distribution over wide sky areas and redshift ranges is through single-dish intensity mapping, which exploits the autocorrelation signal of each dish in a telescope array while scanning the same sky patch. Thanks to its broad frequency coverage and technical capabilities, SKA-Mid will enable measurements of the integrated 21 cm emission from HI up to redshift $z\sim3$, making single-dish intensity mapping a key observable for probing dark matter and dark energy. Isolating the faint 21 cm cosmological signal without introducing biases is, however, challenging. The 21 cm signal is several orders of magnitude weaker than the astrophysical foregrounds, and its analysis is further affected by instrumental systematics. Overcoming these difficulties requires detailed modelling together with continuous improvements and innovations in data-analysis techniques. Over the past decade, the international community has developed and tested new methods to address current observational challenges and prepare for forthcoming SKA-Mid observations. This chapter reviews recent advances in map-making and component-separation techniques, with particular emphasis on telescope-specific systematics such as beam response and correlated noise. We focus on results obtained in controlled simulation environments, providing a valuable framework for assessing the strengths and limitations of different approaches. Developing robust algorithms capable of accurately handling instrumental effects and sky-model uncertainties is a crucial step toward fully exploiting the cosmological potential of HI intensity-mapping surveys in the SKA Observatory era.

Figures

Figures reproduced from arXiv: 2606.27244 by the authors.

Figure 1
Figure 1. Left. Comparison between the 𝐶 Res ℓ recovered with GNILC (blue line), GMCA (orange line), Need-GMCA (green line), PCA (red line) and Need-PCA (purple line). The input 𝐶 cosmo ℓ is plotted in black. The bottom panel shows the percent difference Δ. The telescope beam is Gaussian, with 𝜃FWHM = 𝑐 𝜈𝐷 , where D is the dish diameter, and it varies across the frequency channels. 𝑁fg =3 for PCA, Need-PCA, GMCA and Need-GMCA… view at source ↗
Figure 2
Figure 2. Comparison of the estimator (𝑃clean − 𝑃true)/𝑃true, where 𝑃clean is the power spectrum of the residual maps for the various cleaning methods, while 𝑃true is the input signal and noise. The left panel show the Gaussian beam case while the right panel show the result for a realistic beam model (Airy, see Harper and Dickinson 2018) Aiming at a detailed comparison among methods, the performances in reconstructing the tr… view at source ↗
Figure 3
Figure 3. Radar charts showing the performance of the various cleaning methods participating in the data challenge presented in Spinelli et al. (2022) (larger covered areas correspond to better performing methods). Mock data are assuming a SKA-Mid Hi IM survey. See text for details. picked up by that; ii) the beam can have a non-trivial chromaticity (see for example the structure in the right panel of [PITH_FULL_IMAGE:figure… view at source ↗
Figures from the paper (6 more)
Figure 4
Figure 4. Figure 4: Left: Primary beam model at 950 MHz: Gauss model (black), Jinc model (Wilson and Rohlfs K., 2013) (solid green), the cosine model (Condon and Ransom, 2016) (magenta), the gaussian tapered Airy disk used in Harper and Dickinson (2018) (dashed red), and the one obtained …
Figure 5
Figure 5. Figure 5: Left. Relative difference between the foreground cleaned (with 𝑁fg = 4) radial power spectrum and the true input signal for the different FWHM models: 𝜆 𝐷 in black, the smooth model in orange and the ripple model in blue. Results are shown for the worst and best-case s…
Figure 6
Figure 6. Figure 6: Angular (left) and frequency (right) power spectrum of the reconstructed Hi IM signal using differ￾ent methods, each represented by a distinct colour. The bottom panels display the ratio of the reconstructed to the true Hi power spectrum for each method. 7 Other approa…
Figure 7
Figure 7. Figure 7: The left and the right panels respectively show (blue solid line) the measured 𝐶ℓ (Δ𝜈) and [𝐶ℓ (Δ𝜈)]𝑇 for a representative ℓ = 2740. The black dashed vertical lines show the chosen characteristic length scale [Δ𝜈]0.1, where the amplitude of [𝐶ℓ (Δ𝜈)]𝑇 falls to 10% of t…
Figure 8
Figure 8. Figure 8: Spherically averaged power spectra for simulated 1/ 𝑓 noise above the instrumental noise level. Two different scan strategies are considered: HRD and random. Forming sky maps from the time-ordered data was done with (MM) and without (Binned) the inclusion of the noise …
Figure 9
Figure 9. Figure 9: Comparison between the full Bayesian approach and a conventional ‘high-pass filter + Wiener filter’ method. Residual map: Map showing the residual difference between the estimated sky signal and the true sky input used in simulations. Uncertainty map: Posterior standar…

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

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

  1. Modeling the HI-Halo Connection: Evolution, Scatter, and a Halo-based Prescription for 21-cm Mock Catalogs

    astro-ph.CO 2026-07 accept novelty 5.0 of 10

    A prescription fitted to GAEA2023 reproduces the median HI-halo mass relation and its scatter using halo spin and concentration, enabling realistic 21-cm mock catalogs.

  2. meer21cm: an Analysis Pipeline and Comprehensive Toolkit for HI Intensity Mapping

    astro-ph.CO 2026-07 accept novelty 5.0 of 10

    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.

Reference graph

Works this paper leans on

122 extracted references · 97 canonical work pages · cited by 2 Pith papers

  1. [1]

    2026 ,publisher =

    Laura Wolz and author2 and author3 and author4 and author5 , title =. 2026 ,publisher =

    2026

  2. [2]

    2026 ,publisher =

    Steven Cunnington&Wang and author2 and author3 and author4 and author5 ,title =. 2026 ,publisher =

    2026

  3. [3]

    2026 ,publisher =

    José Fonseca and author2 and author3 and author4 and author5 ,title =. 2026 ,publisher =

    2026

  4. [4]

    2026 ,publisher =

    Stefano Camera and author2 and author3 and author4 and author5 ,title =. 2026 ,publisher =

    2026

  5. [5]

    2026 ,publisher =

    Khandakar Md Asif Elahi and author2 and author3 and author4 and author5 ,title =. 2026 ,publisher =

    2026

  6. [6]

    2026 ,publisher =

    Tommaso Ronconi and author2 and author3 and author4 and author5 ,title =. 2026 ,publisher =

    2026

  7. [7]

    2026 ,publisher =

    Suman Majumdar and author2 and author3 and author4 and author5 ,title =. 2026 ,publisher =

    2026

  8. [8]

    2026 ,publisher =

    Suman Chatterjee and author2 and author3 and author4 and author5 ,title =. 2026 ,publisher =

    2026

Show all 122 references
  1. [9]

    2018 , eprint=

    Square Kilometre Array Science Data Challenge 1 , author=. 2018 , eprint=

    2018

  2. [10]

    Square Kilometre Array Science Data Challenge 1: analysis and results , volume=

    Bonaldi, A and An, T and Brüggen, M and Burkutean, S and Coelho, B and Goodarzi, H and Hartley, P and Sandhu, P K and Wu, C and Yu, L and Zhoolideh Haghighi, M H and Antón, S and Bagheri, Z and Barbosa, D and Barraca, J P and Bartashevich, D and Bergano, M and Bonato, M and Br...

    doi

  3. [11]

    2019 , eprint=

    Anticipated Performance of the Square Kilometre Array -- Phase 1 (SKA1) , author=. 2019 , eprint=

    2019

  4. [12]

    2015 , publisher=

    Advancing Astrophysics with the Square Kilometre Array (AASKA14) , author=. 2015 , publisher=

    2015

  5. [13]

    MNRAS , keywords =

    H I intensity mapping with MeerKAT: calibration pipeline for multidish autocorrelation observations. MNRAS , keywords =. doi:10.1093/mnras/stab1365 , archivePrefix =. 2011.13789 , primaryClass =

    2011 doi

  6. [14]

    MNRAS , keywords =

    MeerKLASS L-band deep-field intensity maps: entering the H I dominated regime. MNRAS , keywords =. doi:10.1093/mnras/staf195 , archivePrefix =. 2407.21626 , primaryClass =

    doi

  7. [15]

    MNRAS , keywords =

    Impact of 1/f noise on cosmological parameter constraints for SKA intensity mapping. MNRAS , keywords =. doi:10.1093/mnras/stz3307 , archivePrefix =. 1907.12132 , primaryClass =

    1907 doi

  8. [16]

    MNRAS , keywords =

    Simulations for single-dish intensity mapping experiments. MNRAS , keywords =. doi:10.1093/mnras/stv2153 , archivePrefix =. 1507.04561 , primaryClass =

    doi arXiv

  9. [17]

    MNRAS , keywords =

    Potential impact of global navigation satellite services on total power H I intensity mapping surveys. MNRAS , keywords =. doi:10.1093/mnras/sty1495 , archivePrefix =. 1803.06314 , primaryClass =

    doi arXiv

  10. [18]

    The BINGO project. II. Instrument description. AAP , keywords =. doi:10.1051/0004-6361/202039962 , archivePrefix =. 2107.01634 , primaryClass =

    doi

  11. [19]

    MNRAS , keywords =

    1/f noise analysis for FAST H I intensity mapping drift-scan experiment. MNRAS , keywords =. doi:10.1093/mnras/stab2728 , archivePrefix =. 2109.06447 , primaryClass =

    doi

  12. [20]

    MNRAS , keywords =

    H I intensity mapping with MeerKAT: 1/f noise analysis. MNRAS , keywords =. doi:10.1093/mnras/staa3856 , archivePrefix =. 2007.01767 , primaryClass =

    2007 doi

  13. [21]

    MNRAS , keywords =

    Mitigating the effect of 1/f noise on the detection of the H I intensity mapping power spectrum from single-dish measurements. MNRAS , keywords =. doi:10.1093/mnras/stad3457 , archivePrefix =. 2302.02683 , primaryClass =

    doi

  14. [22]

    MNRAS , keywords =

    Impact of simulated 1/f noise for HI intensity mapping experiments. MNRAS , keywords =. doi:10.1093/mnras/sty1238 , archivePrefix =. 1711.07843 , primaryClass =

    doi arXiv

  15. [23]

    Lucas Makinen and Lachlan Lancaster and Francisco Villaescusa-Navarro and others , title =

    T. Lucas Makinen and Lachlan Lancaster and Francisco Villaescusa-Navarro and others , title =. jcap. doi:10.1088/1475-7516/2021/04/081 , year = 2021, month =

    2021 doi

  16. [24]

    Shulei Ni and Yichao Li and Li-Yang Gao and Xin Zhang , title =. apj. doi:10.3847/1538-4357/ac7a34 , year = 2022, month =

    2022 doi

  17. [25]

    Li-Yang Gao and Yichao Li and Shulei Ni and Xin Zhang , title =. mnras. doi:10.1093/mnras/stad2646 , year = 2023, month =

    2023 doi

  18. [26]

    Monthly Notices of the Royal Astronomical Society , volume =

    Chen, T and Bianco, M and Tolley, E and Spinelli, M and Forero-Sanchez, D and Kneib, J P , title =. Monthly Notices of the Royal Astronomical Society , volume =. 2024 , month =. doi:10.1093/mnras/stae1676 , url =

    2024 doi

  19. [27]

    APJ , keywords =

    Joint Bayesian Component Separation and CMB Power Spectrum Estimation. APJ , keywords =. doi:10.1086/525277 , archivePrefix =. 0709.1058 , primaryClass =

    doi arXiv

  20. [28]

    MNRAS , keywords =

    zeus: a PYTHON implementation of ensemble slice sampling for efficient Bayesian parameter inference. MNRAS , keywords =. doi:10.1093/mnras/stab2867 , archivePrefix =. 2105.03468 , primaryClass =

    doi

  21. [29]

    Physics Letters B , year = 1987, month = sep, volume =

    Hybrid Monte Carlo. Physics Letters B , year = 1987, month = sep, volume =. doi:10.1016/0370-2693(87)91197-X , adsurl =

    1987 doi

  22. [30]

    arXiv e-prints , keywords =

    A Conceptual Introduction to Hamiltonian Monte Carlo. arXiv e-prints , keywords =. doi:10.48550/arXiv.1701.02434 , archivePrefix =. 1701.02434 , primaryClass =

    doi arXiv

  23. [31]

    APJ , keywords =

    Application of Monte Carlo Algorithms to the Bayesian Analysis of the Cosmic Microwave Background. APJ , keywords =. doi:10.1086/383515 , archivePrefix =. astro-ph/0209560 , primaryClass =

    doi arXiv

  24. [32]

    PRD , keywords =

    Global, exact cosmic microwave background data analysis using Gibbs sampling. PRD , keywords =. doi:10.1103/PhysRevD.70.083511 , archivePrefix =. astro-ph/0310080 , primaryClass =

    doi arXiv

  25. [33]

    APJL , keywords =

    The Joint Large-Scale Foreground-CMB Posteriors of the 3 Year WMAP Data. APJL , keywords =. doi:10.1086/526545 , archivePrefix =. 0709.1037 , primaryClass =

    doi arXiv

  26. [34]

    RAS Techniques and Instruments , keywords =

    Statistical estimation of full-sky radio maps from 21 cm array visibility data using Gaussian constrained realizations. RAS Techniques and Instruments , keywords =. doi:10.1093/rasti/rzae041 , archivePrefix =. 2403.13766 , primaryClass =

    doi

  27. [35]

    APJS , keywords =

    Statistical Recovery of 21 cm Visibilities and Their Power Spectra with Gaussian-constrained Realizations and Gibbs Sampling. APJS , keywords =. doi:10.3847/1538-4365/acc324 , archivePrefix =. 2211.05088 , primaryClass =

    doi

  28. [36]

    RAS Techniques and Instruments , keywords =

    Joint Bayesian calibration and map-making for intensity mapping experiments. RAS Techniques and Instruments , keywords =. doi:10.1093/rasti/rzag024 , archivePrefix =. 2509.10992 , primaryClass =

    doi

  29. [37]

    MNRAS , keywords =

    A general polynomial emulator for cosmology via moment projection. MNRAS , keywords =. doi:10.1093/mnras/staf2039 , archivePrefix =. 2507.02179 , primaryClass =

    doi

  30. [38]

    Introduction to Applied Bayesian Statistics and Estimation for Social Scientists

    Lynch, Scott M. Introduction to Applied Bayesian Statistics and Estimation for Social Scientists

  31. [39]

    Removing systematics-induced 21-cm foreground residuals by cross-correlating filtered data , volume=

    Wang, Haochen and Mena-Parra, Juan and Chen, Tianyue and Masui, Kiyoshi , year=. Removing systematics-induced 21-cm foreground residuals by cross-correlating filtered data , volume=. Physical Review D , publisher=. doi:10.1103/physrevd.106.043534 , number=

    doi

  32. [40]

    de Villiers, Dirk I. L. , journal=. Prediction of Aperture Efficiency Ripple in Clear Aperture Offset Gregorian Antennas , year=

  33. [41]

    Instrument sensitivity and foreground subtraction

    21 cm observation of large-scale structures at z -0.5ex 1. Instrument sensitivity and foreground subtraction. AAP , keywords =. doi:10.1051/0004-6361/201117837 , archivePrefix =. 1108.1474 , primaryClass =

    doi arXiv

  34. [42]

    Modelling MeerKAT L-band beams

    Primary beam effects of radio astronomy antennas - II. Modelling MeerKAT L-band beams. MNRAS , keywords =. doi:10.1093/mnras/stab104 , archivePrefix =. 1904.07155 , primaryClass =

    1904 doi

  35. [43]

    MNRAS , keywords =

    H I intensity mapping with MeerKAT: primary beam effects on foreground cleaning. MNRAS , keywords =. doi:10.1093/mnras/stab1688 , archivePrefix =. 2011.10815 , primaryClass =

    2011 doi

  36. [44]

    APJS , keywords =

    Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data. APJS , keywords =. doi:10.3847/1538-4365/add897 , archivePrefix =. 2504.03908 , primaryClass =

    doi

  37. [45]

    MNRAS , keywords =

    A quadratic estimator view of the transfer function correction in intensity mapping surveys. MNRAS , keywords =. doi:10.1093/mnrasl/slaf058 , archivePrefix =. 2504.13070 , primaryClass =

    doi

  38. [46]

    MNRAS , keywords =

    Gaussian process foreground subtraction and power spectrum estimation for 21 cm cosmology. MNRAS , keywords =. doi:10.1093/mnras/staa3736 , archivePrefix =. 2010.15892 , primaryClass =

    2010 doi

  39. [47]

    arXiv e-prints , keywords =

    Joint Multichannel Deconvolution and Blind Source Separation. arXiv e-prints , keywords =. doi:10.48550/arXiv.1703.02650 , archivePrefix =. 1703.02650 , primaryClass =

    doi arXiv

  40. [48]

    D. I. L. IEEE Transactions on Antennas and Propagation , title=. 2013 , volume=

    2013

  41. [49]

    Tools of Radio Astronomy

  42. [50]

    Essential Radio Astronomy

  43. [51]

    Digital Signal Processing , keywords =

    Joint deconvolution and unsupervised source separation for data on the sphere. Digital Signal Processing , keywords =. doi:10.1016/j.dsp.2020.102946 , archivePrefix =. 2012.12740 , primaryClass =

    2020 doi

  44. [52]

    MNRAS , keywords =

    Radio frequency interference from radio navigation satellite systems: simulations and comparison to MeerKAT single-dish data. MNRAS , keywords =. doi:10.1093/mnras/stae2649 , archivePrefix =. 2404.17908 , primaryClass =

    doi

  45. [53]

    MNRAS , keywords =

    SKAO H I intensity mapping: blind foreground subtraction challenge. MNRAS , keywords =. doi:10.1093/mnras/stab3064 , archivePrefix =. 2107.10814 , primaryClass =

    doi

  46. [54]

    APJS , keywords =

    First-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Foreground Emission. APJS , keywords =. doi:10.1086/377252 , archivePrefix =. astro-ph/0302208 , primaryClass =

    doi arXiv

  47. [55]

    MNRAS , keywords =

    CMB and SZ effect separation with constrained Internal Linear Combinations. MNRAS , keywords =. doi:10.1111/j.1365-2966.2010.17624.x , archivePrefix =. 1006.5599 , primaryClass =

    2010 doi

  48. [56]

    Planck intermediate results. XLVIII. Disentangling Galactic dust emission and cosmic infrared background anisotropies. AAP , keywords =. doi:10.1051/0004-6361/201629022 , archivePrefix =. 1605.09387 , primaryClass =

    doi arXiv

  49. [57]

    MNRAS , keywords =

    Extracting H I cosmological signal with generalized needlet internal linear combination. MNRAS , keywords =. doi:10.1093/mnras/stv2884 , archivePrefix =. 1509.00742 , primaryClass =

    doi arXiv

  50. [58]

    AAP , archivePrefix = "arXiv", eprint =

    The pre-launch Planck Sky Model: a model of sky emission at submillimetre to centimetre wavelengths. AAP , archivePrefix = "arXiv", eprint =. doi:10.1051/0004-6361/201220019 , url =

    doi

  51. [59]

    The BINGO project. V. Further steps in component separation and bispectrum analysis. AAP , keywords =. doi:10.1051/0004-6361/202141707 , archivePrefix =. 2107.01637 , primaryClass =

    doi

  52. [60]

    IEEE Transactions on Automatic Control , keywords =

    A New Look at the Statistical Model Identification. IEEE Transactions on Automatic Control , keywords =

  53. [61]

    MNRAS , keywords =

    Foreground component separation with generalized Internal Linear Combination. MNRAS , keywords =. doi:10.1111/j.1365-2966.2011.19497.x , archivePrefix =. 1103.1166 , primaryClass =

    2011 doi

  54. [62]

    Narcowich, F. J. and Petrushev, P. and Ward, J. D. , title =. SIAM Journal on Mathematical Analysis , volume =. 2006 , doi =

    2006

  55. [63]

    and Kerkyacharian, G

    Baldi, P. and Kerkyacharian, G. and Marinucci, D. and Picard, D. , TITLE =. Ann. Statist. , FJOURNAL =. 2009 , NUMBER =. doi:10.1214/08-AOS601 , URL =

    2009 doi

  56. [64]

    2011 , PAGES =

    Marinucci, Domenico and Peccati, Giovanni , TITLE =. 2011 , PAGES =. doi:10.1017/CBO9780511751677 , URL =

    2011 doi

  57. [65]

    PRD , keywords =

    Integrated Sachs-Wolfe effect from the cross correlation of WMAP 3year and the NRAO VLA sky survey data: New results and constraints on dark energy. PRD , keywords =. doi:10.1103/PhysRevD.74.043524 , archivePrefix =. astro-ph/0606475 , primaryClass =

    doi arXiv

  58. [66]

    MNRAS , keywords =

    Spherical needlets for cosmic microwave background data analysis. MNRAS , keywords =. 2008 , volume =. doi:10.1111/j.1365-2966.2007.12550.x , archivePrefix =. 0707.0844 , primaryClass =

    2008 doi

  59. [67]

    arXiv e-prints , keywords =

    Needlets and foreground removal for SKAO hydrogen intensity maps. arXiv e-prints , keywords =. doi:10.48550/arXiv.2509.02644 , archivePrefix =. 2509.02644 , primaryClass =

    doi

  60. [68]

    APJ , keywords =

    HEALPix: A Framework for High-Resolution Discretization and Fast Analysis of Data Distributed on the Sphere. APJ , keywords =. doi:10.1086/427976 , archivePrefix =. astro-ph/0409513 , primaryClass =

    doi arXiv

  61. [69]

    AAP , keywords =

    Foreground removal in HI 21 cm intensity mapping under frequency-dependent beam distortions. AAP , keywords =. doi:10.1051/0004-6361/202557229 , archivePrefix =. 2511.13328 , primaryClass =

    doi

  62. [70]

    MNRAS , keywords =

    HI as a probe of the large-scale structure in the post-reionization universe. MNRAS , keywords =. doi:10.1111/j.1365-2966.2010.16933.x , archivePrefix =. 0908.3796 , primaryClass =

    2010 doi

  63. [71]

    Advancing Astrophysics with the Square Kilometre Array (AASKA14) , year = 2015, month = apr, eid =

    Cosmology from a SKA HI intensity mapping survey. Advancing Astrophysics with the Square Kilometre Array (AASKA14) , year = 2015, month = apr, eid =

    2015

  64. [72]

    MNRAS , keywords =

    Fluctuations in 21-cm emission after reionization. MNRAS , keywords =. doi:10.1111/j.1365-2966.2007.12568.x , archivePrefix =. 0708.3392 , primaryClass =

    2007 doi

  65. [73]

    ArXiv e-prints , archivePrefix = "arXiv", eprint =

    MeerKLASS: MeerKAT Large Area Synoptic Survey. ArXiv e-prints , archivePrefix = "arXiv", eprint =

  66. [74]

    MNRAS , keywords =

    H I intensity mapping: a single dish approach. MNRAS , keywords =. doi:10.1093/mnras/stt1082 , archivePrefix =. 1209.0343 , primaryClass =

    doi arXiv

  67. [75]

    MNRAS , keywords =

    Fast simulations for intensity mapping experiments. MNRAS , keywords =. doi:10.1093/mnras/stu1666 , archivePrefix =. 1405.1751 , primaryClass =

    doi arXiv

  68. [76]

    PRD , keywords =

    Coaxing cosmic 21 cm fluctuations from the polarized sky using m -mode analysis. PRD , keywords =. doi:10.1103/PhysRevD.91.083514 , archivePrefix =. 1401.2095 , primaryClass =

    doi arXiv

  69. [77]

    PASA , keywords =

    Cosmology with Phase 1 of the Square Kilometre Array Red Book 2018: Technical specifications and performance forecasts. PASA , keywords =. doi:10.1017/pasa.2019.51 , archivePrefix =. 1811.02743 , primaryClass =

    2018 doi

  70. [78]

    Using HI to Probe Large Scale Structures at z \ 3. J. Astrophys. Astron. , eprint =. doi:10.1007/BF02933588 , adsurl =

    doi

  71. [79]

    HI Fluctuations at Large Redshifts: I--Visibility correlation. J. Astrophys. Astron. , eprint =. doi:10.1007/BF02702273 , adsurl =

    doi

  72. [80]

    Formalism and the expected signal

    On using visibility correlations to probe the HI distribution from the dark ages to the present epoch - I. Formalism and the expected signal. MNRAS , eprint =. doi:10.1111/j.1365-2966.2004.08604.x , adsurl =

    2004 doi

  73. [81]

    2006 , doi =

    Gaussian Processes for Machine Learning , author =. 2006 , doi =

    2006

  74. [82]

    MNRAS , keywords =

    A Tapered Gridded Estimator (TGE) for the multifrequency angular power spectrum (MAPS) and the cosmological H I 21-cm power spectrum. MNRAS , keywords =. doi:10.1093/mnras/sty3501 , archivePrefix =. 1812.08801 , primaryClass =

    doi arXiv

  75. [83]

    Saiyad and Chengalur, Jayaram N

    Ghosh, Abhik and Bharadwaj, Somnath and Ali, Sk. Saiyad and Chengalur, Jayaram N. , title = ". MNRAS , volume =. 2011 , month =. doi:10.1111/j.1365-2966.2010.17853.x , url =

    2011 doi

  76. [84]

    Saiyad and Chengalur, Jayaram N

    Ghosh, Abhik and Bharadwaj, Somnath and Ali, Sk. Saiyad and Chengalur, Jayaram N. , title = ". MNRAS , volume =. 2011 , month =. doi:10.1111/j.1365-2966.2011.19649.x , url =

    2011 doi

  77. [85]

    Saiyad , title = "

    Choudhuri, Samir and Bharadwaj, Somnath and Ghosh, Abhik and Ali, Sk. Saiyad , title = ". MNRAS , volume =. 2014 , month =. doi:10.1093/mnras/stu2027 , url =

    2014 doi

  78. [86]

    Saiyad , title = "

    Choudhuri, Samir and Bharadwaj, Somnath and Roy, Nirupam and Ghosh, Abhik and Ali, Sk. Saiyad , title = ". MNRAS , volume =. 2016 , month =. doi:10.1093/mnras/stw607 , url =

    2016 doi

  79. [87]

    Datta and Srijita Pal and Madhurima Choudhury and Samir Choudhuri and Prasun Dutta and Debanjan Sarkar , title =

    Arnab Chakraborty and Abhirup Datta and Nirupam Roy and Somnath Bharadwaj and Tirthankar Roy Choudhury and Kanan K. Datta and Srijita Pal and Madhurima Choudhury and Samir Choudhuri and Prasun Dutta and Debanjan Sarkar , title =. 2021 , month =. doi:10.3847/2041-8213/abd17a , url =

    2021 doi

  80. [88]

    HI intensity mapping: Impact of primary beam effects , school =

    Siyambonga Donald Matshawule , year =. HI intensity mapping: Impact of primary beam effects , school =

  81. [89]

    MNRAS , keywords =

    Demonstrating the Tapered Gridded Estimator (TGE) for the cosmological H I 21-cm power spectrum using 150-MHz GMRT observations. MNRAS , keywords =. doi:10.1093/mnras/staa3831 , archivePrefix =. 2012.04998 , primaryClass =

    2012 doi

  82. [90]

    MNRAS , keywords =

    Towards 21-cm intensity mapping at z = 2.28 with uGMRT using the tapered gridded estimator I: Foreground avoidance. MNRAS , keywords =. doi:10.1093/mnras/stac2419 , archivePrefix =. 2208.11063 , primaryClass =

    doi

  83. [91]

    Cross-polarization power spectrum

    Towards 21-cm intensity mapping at z = 2.28 with uGMRT using the tapered gridded estimator - II. Cross-polarization power spectrum. MNRAS , keywords =. doi:10.1093/mnras/stad191 , archivePrefix =. 2301.06677 , primaryClass =

    doi

  84. [92]

    MNRAS , keywords =

    Towards 21-cm intensity mapping at z = 2.28 with uGMRT using the tapered gridded estimator III: Foreground removal. MNRAS , keywords =. doi:10.1093/mnras/stad2495 , archivePrefix =. 2308.08284 , primaryClass =

    doi

  85. [93]

    Wide-band analysis

    Towards 21-cm intensity mapping at z = 2.28 with uGMRT using the tapered gridded estimator - IV. Wide-band analysis. MNRAS , keywords =. doi:10.1093/mnras/stae740 , archivePrefix =. 2403.06736 , primaryClass =

    doi

  86. [94]

    APJ , keywords =

    Foreground Contamination in Interferometric Measurements of the Redshifted 21 cm Power Spectrum. APJ , keywords =. doi:10.1088/0004-637X/695/1/183 , archivePrefix =. 0807.3956 , primaryClass =

    doi arXiv

  87. [95]

    MNRAS , keywords =

    Measurements of the diffuse Galactic synchrotron spectral index and curvature from MeerKLASS pilot data. MNRAS , keywords =. doi:10.1093/mnras/stab3346 , archivePrefix =. 2111.08517 , primaryClass =

    doi

  88. [96]

    MNRAS , keywords =

    Measuring ultralarge scale effects in the presence of 21 cm intensity mapping foregrounds. MNRAS , keywords =. doi:10.1093/mnras/stab903 , archivePrefix =. 2011.11510 , primaryClass =

    2011 doi

  89. [97]

    and Abdalla, F.B

    Wolz, L. and Abdalla, F.B. and Blake, C. and Shaw, J.R. and Chapman, E. and Rawlings, S. The effect of foreground subtraction on cosmological measurements from Intensity Mapping. 2014. doi:10.1093/mnras/stu792. arXiv:1310.8144

    2014 doi arXiv

  90. [98]

    MNRAS , keywords =

    Recovering the 21-cm signal from simulated FAST intensity maps. MNRAS , keywords =. doi:10.1093/mnras/stab1197 , archivePrefix =. 2104.10937 , primaryClass =

    doi

  91. [99]

    APJ , keywords =

    Multifrequency Analysis of 21 Centimeter Fluctuations from the Era of Reionization. APJ , keywords =. doi:10.1086/429857 , archivePrefix =. astro-ph/0408515 , primaryClass =

    doi arXiv

  92. [100]

    MNRAS , keywords =

    Bayesian estimation of cross-coupling and reflection systematics in 21cm array visibility data. MNRAS , keywords =. doi:10.1093/mnras/stae2242 , archivePrefix =. 2312.03697 , primaryClass =

    doi

  93. [101]

    arXiv e-prints , keywords =

    Bayesian component separation and power spectrum estimation for 21 cm intensity mapping data cubes. arXiv e-prints , keywords =. doi:10.48550/arXiv.2604.26890 , archivePrefix =. 2604.26890 , primaryClass =

    doi arXiv

  94. [102]

    BEYONDPLANCK. I. Global Bayesian analysis of the Planck Low Frequency Instrument data. AAP , keywords =. doi:10.1051/0004-6361/202244953 , archivePrefix =. 2011.05609 , primaryClass =

    2011 doi

  95. [103]

    COSMOGLOBE DR1 results. I. Improved Wilkinson Microwave Anisotropy Probe maps through Bayesian end-to-end analysis. AAP , keywords =. doi:10.1051/0004-6361/202346414 , archivePrefix =. 2303.08095 , primaryClass =

    doi

  96. [104]

    Cosmoglobe DR2. I. Global Bayesian analysis of COBE-DIRBE. arXiv e-prints , keywords =. doi:10.48550/arXiv.2408.10952 , archivePrefix =. 2408.10952 , primaryClass =

    doi

  97. [105]

    HI constraints from the cross-correlation of eBOSS galaxies and Green Bank Telescope intensity maps , volume=

    Wolz, Laura and Pourtsidou, Alkistis and Masui, Kiyoshi W and Chang, Tzu-Ching and Bautista, Julian E and Müller, Eva-Maria and Avila, Santiago and Bacon, David and Percival, Will J and Cunnington, Steven and Anderson, Chris and Chen, Xuelei and Kneib, Jean-Paul and Li, Yi-Cha...

    doi

  98. [106]

    2007", month =

    Sparsity and Morphological Diversity in Blind Source Separation. IEEE Transactions on Image Processing , year = "2007", month = "Nov", volume =. doi:10.1109/TIP.2007.906256 , adsurl =

    2007 doi

  99. [107]

    IEEE transactions on neural networks , year=

    Fast and robust fixed-point algorithms for independent component analysis , author=. IEEE transactions on neural networks , year=

  100. [108]

    and Harker, Geraint and Jelic, Vibor and Labropoulos, Panagiotis and Zaroubi, Saleem and Brentjens, Michiel A

    Chapman, Emma and Abdalla, Filipe B. and Harker, Geraint and Jelic, Vibor and Labropoulos, Panagiotis and Zaroubi, Saleem and Brentjens, Michiel A. and de Bruyn, A.G. and Koopmans, L.V.E. Foreground Removal using FastICA: A Showcase of LOFAR-EoR. 2012. doi:10.1111/j.1365-2966....

    2012 doi

  101. [109]

    MNRAS , keywords =

    Recovery of 21 cm intensity maps with sparse component separation. MNRAS , keywords =. doi:10.1093/mnras/staa2854 , archivePrefix =. 2006.05996 , primaryClass =

    2006 doi

  102. [110]

    MNRAS , keywords =

    Comparing foreground removal techniques for recovery of the LOFAR-EoR 21 cm power spectrum. MNRAS , keywords =. doi:10.1093/mnras/staa3446 , archivePrefix =. 2011.01284 , primaryClass =

    2011 doi

  103. [111]

    Impact of foregrounds on HI intensity mapping cross-correlations with optical surveys

    Cunnington, Steven and Wolz, Laura and Pourtsidou, Alkistis and Bacon, David. Impact of foregrounds on HI intensity mapping cross-correlations with optical surveys. 2019. doi:10.1093/mnras/stz1916. arXiv:1904.01479

    2019 doi arXiv

  104. [112]

    MNRAS , keywords =

    21-cm foregrounds and polarization leakage: cleaning and mitigation strategies. MNRAS , keywords =. doi:10.1093/mnras/stab856 , archivePrefix =. 2010.02907 , primaryClass =

    2010 doi

  105. [113]

    and Chang, Tzu-Ching and Masui, Kiyoshi W

    Switzer, Eric R. and Chang, Tzu-Ching and Masui, Kiyoshi W. and Pen, Ue-Li and Voytek, Tabitha C. Interpreting the unresolved intensity of cosmologically redshifted line radiation. Astrophys. J. 2015. doi:10.1088/0004-637X/815/1/51. arXiv:1504.07527

    2015 doi arXiv

  106. [114]

    4", pages =

    Wolz, L. and others. MNRAS , number = "4", pages = "4938--4949", primaryClass = "astro-ph.CO", title = ". 2017. doi:10.1093/mnras/stw2556. arXiv:1510.05453

    2017 doi arXiv

  107. [115]

    The degeneracy between primordial non-Gaussianity and foregrounds in 21 cm intensity mapping experiments

    Cunnington, Steven and Camera, Stefano and Pourtsidou, Alkistis. The degeneracy between primordial non-Gaussianity and foregrounds in 21 cm intensity mapping experiments. Mon. Not. Roy. Astron. Soc. 2020. doi:10.1093/mnras/staa2986. arXiv:2007.12126

    2020 doi

  108. [116]

    and Cunnington, Steven and Pourtsidou, Alkistis and Blake, Chris

    Soares, Paula S. and Cunnington, Steven and Pourtsidou, Alkistis and Blake, Chris. Power spectrum multipole expansion for HI intensity mapping experiments: unbiased parameter estimation. Mon. Not. Roy. Astron. Soc. 2021. doi:10.1093/mnras/stab027. arXiv:2008.12102

    2021 doi

  109. [117]

    arXiv e-prints , keywords =

    Gaussian Process Regression for foreground removal in HI intensity mapping experiments. arXiv e-prints , keywords =

  110. [118]

    and others

    Carucci, Isabella P. and others. Hydrogen intensity mapping with MeerKAT: Preserving cosmological signal by optimising contaminant separation. Astron. Astrophys. 2025. doi:10.1051/0004-6361/202453461. arXiv:2412.06750

    2025 doi

  111. [119]

    and Dunkley, J

    Thorne, B. and Dunkley, J. and Alonso, D. and Næss, S. , year=. The Python Sky Model: software for simulating the Galactic microwave sky , volume=. Monthly Notices of the Royal Astronomical Society , publisher=. doi:10.1093/mnras/stx949 , number=

    doi

  112. [120]

    Monthly Notices of the Royal Astronomical Society , volume =

    Spinelli, M and Bernardi, G and Santos, M G , title =. Monthly Notices of the Royal Astronomical Society , volume =. 2018 , doi =

    2018

  113. [121]

    IEEE Transactions on Image Processing , keywords =

    The Undecimated Wavelet Decomposition and its Reconstruction. IEEE Transactions on Image Processing , keywords =. doi:10.1109/TIP.2006.887733 , adsurl =

    2006 doi

  114. [122]

    The foreground transfer function for H \, i intensity mapping signal reconstruction: MeerKLASS and precision cosmology applications

    Cunnington, Steven and others. The foreground transfer function for H \, i intensity mapping signal reconstruction: MeerKLASS and precision cosmology applications. Mon. Not. Roy. Astron. Soc. 2023. doi:10.1093/mnras/stad1567. arXiv:2302.07034

    2023 doi

Pith tools

Reviewed June 26, 2026 · model on record in the stance chip above.