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A measurement of Galactic synchrotron emission using MWA drift scan observations

T0 review · 3 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read Galactic synchrotron spectrum at 154 MHz has beta 0.9–1.7

desk verdict Useful incremental MWA measurement of the DGSE angular power spectrum at 154 MHz, but the quoted beta values rest on an untested assumption that residual systematics are negligible. read the letter →

arxiv 2506.14310 v1 pith:YEXB3QRP submitted 2025-06-17 astro-ph.GA astro-ph.CO

Suman Chatterjee , Shouvik Sarkar , Samir Choudhuri , Khandakar Md Asif Elahi , Somnath Bharadwaj , Shiv Sethi , Akash Kumar Patwa This is my paper · ORCID
classification astro-ph.GAastro-ph.CO
keywords GalacticsynchrotronemissionangularpowerspectrumMurchisonWidefieldArraydriftscanTaperedGriddedEstimator21-cmforegroundspointsourcesubtractionepochofreionization
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 reports a measurement of the angular power spectrum of diffuse Galactic synchrotron emission (DGSE) at 154.2 MHz using Murchison Widefield Array drift-scan observations along a fixed declination strip. After removing point sources brighter than about 430 mJy from 24 pointing centers, the authors fit the residual power spectrum with a combination of a power law from the diffuse emission and a constant from unresolved point-source Poisson fluctuations. For six of the pointings the fit works, giving power-law slopes $\beta$ between 0.9 and 1.7 and amplitudes $A$ between about 154 and 568 $\mathrm{mK}^2$. The slopes are consistent at the $2\sigma$ level with earlier 150 MHz measurements, supporting the use of such measurements as foreground models for 21-cm epoch-of-reionization experiments and as probes of interstellar turbulence.

What carries the argument

The central tool is the Tapered Gridded Estimator (TGE), a visibility-based estimator that grids the measured visibilities, applies a Gaussian tapering window with $15^\circ$ FWHM to suppress primary-beam sidelobes, subtracts the noise bias from the self-correlation of visibilities, and normalizes the estimate using simulated unit angular power spectra. The model being fitted is $C_\ell^M = A (1000/\ell)^\beta + C$, where the power-law term represents the diffuse Galactic synchrotron emission and the constant $C$ represents Poisson fluctuations from point sources below the 430 mJy subtraction threshold. Source subtraction is performed by imaging with long baselines ($|u|>50\lambda$), CLEAN modeling, and subtracting the model visibilities; the analysis is restricted to $65 < \ell < 650$, where primary-beam convolution effects and noise-dominated high-$\ell$ bins are avoided.

What would settle it

A decisive test would be to re-observe the same six fields with deeper integration and a lower source-subtraction threshold (e.g., sources above 100 mJy instead of 430 mJy) and check whether the fitted power-law parameters $A$ and $\beta$ remain within the reported ranges while the constant term $C$ drops proportionally; if the slope or amplitude changes substantially, the claimed diffuse-emission interpretation is contaminated by systematics or unresolved sources.

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Extended reading notes

Core claim

The central claim is that the residual angular power spectrum of diffuse Galactic synchrotron emission, measured with the Tapered Gridded Estimator on MWA drift-scan visibilities after subtracting compact sources above $\sim 430$ mJy, is described in six fields by the model $C_\ell^M = A (1000/\ell)^\beta + C$ over the multipole range $65 < \ell < 650$. The power-law component is attributed to diffuse Galactic synchrotron emission, the constant to Poisson fluctuations of residual point sources, and the fitted parameters vary with sky position: $A$ from about 154 to 568 $\mathrm{mK}^2$, $\beta$ from 0.9 to 1.7, and $C$ from 777 to 4457 $\mathrm{mK}^2$. The paper argues that the shallow slope at $\ell \le 200$, in contrast to the $\ell^2$ scaling of point-source Poisson noise at $\ell > 200$, indicates genuine diffuse emission rather than residual sources. The measured $\beta$ values are consistent at $2\sigma$ with earlier interferometric measurements at similar frequencies and angular scales.

Load-bearing premise

The load-bearing assumption is that the residual visibilities after subtracting point sources are genuine diffuse Galactic synchrotron emission, not leftover calibration errors, ionospheric distortions, or unmodeled compact sources.

Editorial extensions

If this is right

  • The six fitted power spectra provide a foreground model for epoch-of-reionization 21-cm observations in the MWA EoR0/EoR1 region, enabling better foreground avoidance or removal at arc-minute scales.
  • The pointing-to-pointing variation in $A$ and $\beta$ constrains fluctuations of the Galactic magnetic field and cosmic-ray electron density in this sky region.
  • Consistency of $\beta$ with earlier GMRT and WSRT measurements at 150 MHz strengthens confidence in visibility-based power-spectrum estimation after aggressive source subtraction.
  • For the 18 pointings that do not fit, the flat residual spectrum indicates that unresolved Poisson sources or imaging artifacts limit shallow drift-scan measurements, pointing to the need for deeper observations.

Reading between the lines

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

  • If the measured $\beta$ range (0.9 to 1.7) is representative of diffuse Galactic synchrotron emission at arc-minute scales, then the foreground is much flatter at $\ell \sim 1000$ than the steeper slopes found at degree scales, and locating the break between these regimes would help separate turbulent from Poissonian contributions in 21-cm foreground subtraction.
  • The constant term $C$ of the fit is effectively a measurement of residual point-source confusion power; comparing $C$ with predictions from source count models at 154 MHz could validate the completeness of the 430 mJy catalog and the accuracy of the source subtraction.
  • The 18 non-fitted pointings, including the Fornax A region, suggest that bright extended sources and calibration artifacts dominate the residuals, so a re-analysis after improved ionospheric calibration or with the full MWA Phase II configuration could test whether more pointings become fit.
  • Extending this single-frequency measurement to a wide bandwidth could test the double power-law frequency dependence of the amplitude reported in spectral studies, linking angular and spectral foreground models.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 5 minor

Summary. The paper analyzes MWA Phase II drift-scan observations at 154.2 MHz to measure the angular power spectrum C_l of diffuse Galactic synchrotron emission (DGSE). After removing point sources above a 3-sigma threshold (~430 mJy), the authors apply the Tapered Gridded Estimator (TGE) to residual visibilities and fit the model C_l = A(1000/l)^beta + C over the multipole range 65 < l < 650. They report successful fits for 6 of 24 pointing centers, with beta in the range 0.9-1.7 and A in the range 155-568 mK^2. The power-law component is interpreted as DGSE and the constant as Poisson fluctuations from residual point sources. The paper validates the source subtraction for one pointing against GLEAM and uses MCMC to estimate parameter uncertainties.

Significance. If the measurement is robust, it provides a new estimate of the DGSE angular power spectrum at 154 MHz in a region relevant for EoR experiments, complementing earlier GMRT and WSRT measurements. The use of drift-scan data and the well-established TGE estimator is appropriate, and the validation of source astrometry and flux against GLEAM for one pointing is a positive feature. However, the scientific impact is currently limited by the fact that only 6 of 24 pointing centers yield a fit, and the interpretation of the residual spectrum as genuine DGSE has not been separated from systematic effects. The paper is candid about the Gaussian-random-field assumption for error bars and the strong parameter degeneracies, but it does not provide the null tests needed to support the central claim.

major comments (3)
  1. [Section 3 (after Fig. 1) and Appendix 1] The conclusion that the shallow component at l<200 is genuine DGSE is not supported by a null test. The source-subtraction validation in Appendix 1 reports a systematic ~30 arcsec DEC offset and flux deviations up to 25% for some sources, and Section 4 attributes the flat C_l of unsuccessful PCs to imaging artifacts and residual gain calibration errors. Since no simulation of a point-source-only sky (with sources below the 430 mJy threshold plus noise) is presented, an imperfectly subtracted bright source could produce a non-white residual that mimics the A(1000/l)^beta term in eq. (4). The authors should demonstrate that the observed residual C_l exceeds the expectation from a point-source-only model with realistic subtraction errors.
  2. [Section 3 (Fig. 3 and Table 1)] The strong degeneracies among A, beta, and C (Pearson |r| ~ 0.9) together with the limited l-range (65<l<650, roughly one decade) mean that the individual parameters may not be independently constrained. The posterior distributions shown in Appendix 2 are highly asymmetric and often truncated at the prior boundary, indicating weak constraints. The paper should assess the robustness of the reported beta range, for example by fixing C to the expected Poisson level from the source count model, by using profile likelihoods, or by checking whether the fit is stable when the fitted l-range is varied.
  3. [Section 3 (selection of the six PCs)] The criterion for being 'able to fit the model' is not defined a priori, and no results are shown for the remaining 18 PCs beyond one representative example (Fig. 4). If the six PCs are selected after inspecting the fit quality, the reported beta range may not be representative of the region and any inference from the scatter of parameters could be biased. The authors should either report the measured C_l for all 24 PCs (including upper limits for the unsuccessful ones) or provide a principled, pre-defined selection rule and justify that the selected subset is unbiased.
minor comments (5)
  1. [Figure 1 caption] The caption states that black lines show the total data before point-source subtraction and red lines show C_l after removal, but Section 3 states that red and black lines show the 'No-Sub' and 'UV-Sub' cases respectively; these are opposite and should be corrected.
  2. [Abstract and Section 3] The abstract and Figure 2 use the fitting range '65 <= l <= 650', while Section 3 uses '65 < l < 650'; please make these consistent.
  3. [Abstract] The abstract states that A varies from 155 to 400 mK^2, but Table 1 and Section 4 report values up to 568.4 mK^2; please correct the abstract.
  4. [Appendix 1] The phrase 'we consider an angular scale of 0.4 × theta_FWHM' is ambiguous; it likely means a radial cut at 0.4 times the primary beam FWHM, but this should be stated explicitly.
  5. [General] The measured C_l values are not provided in a table or as electronic supplementary material, which would facilitate comparison with future measurements and independent re-analysis.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the reported beta values are MCMC fits to measured C_l, not predictions derived from the model inputs.

full rationale

The paper's central result is a measurement: residual visibilities after subtracting sources above 430 mJy are processed with TGE, and the resulting C_l are fit to C_l^M = A(1000/l)^beta + C (eq. 4). A, beta, and C are free parameters estimated by MCMC, so the reported beta range 0.9-1.7 is a fitted description of the data, not a quantity already contained in the inputs. The TGE normalization is calibrated with simulations of a unit angular power spectrum (C_l = 1), an independent Monte Carlo calibration rather than a self-referential input. The choice of fitting range 65 <= l <= 650 is justified by simulations in Chatterjee et al. (2022), a same-group citation, but this is a methodological calibration about convolution and systematics, not an assumption that encodes the measured beta; it is not load-bearing for the value of beta. No uniqueness theorem or ansatz is imported to force the model. The paper's inference that DGSE dominates at l <= 200 is an interpretation of the shallower slope after subtraction, not a circular definition; the subsequent fit could in principle have failed, and indeed did fail for 18 of 24 pointing centers. Concerns about residual calibration artifacts or source-subtraction systematics are validity risks, not circularity: the absence of a point-source-only null test would bear on systematic error, not on whether the derivation is equivalent to its inputs by construction.

Assumptions & free parameters 6 free parameters · 5 assumptions · 0 invented entities

The central claim rests on fitted model parameters and several analysis choices (source threshold, taper width, l-range). No new physical entities are introduced. The axioms are standard domain assumptions for interferometric power spectrum estimation, with the Gaussian random field assumption being the most fragile.

free parameters (6)
  • A (per-PC amplitude) = 154.3 to 568.4 mK^2 (Table 1)
    Amplitude of the power-law term fitted to each measured C_l.
  • beta (per-PC spectral index) = 0.9 to 1.7 (Table 1)
    Slope of the power-law term; the central reported quantity.
  • C (Poisson constant) = 777 to 4057 mK^2 (Table 1)
    Constant term attributed to unresolved point sources.
  • Source subtraction threshold S_c = 430 mJy (3 sigma)
    Chosen per-field as 3-sigma image rms; determines the residual data used for power spectrum estimation.
  • Tapering FWHM = 15 degrees
    Choice of Gaussian taper width affects which angular scales are measured; justified by prior same-group simulations (Chatterjee et al. 2022).
  • Fitting l-range = 65 < l < 650
    Excludes l values affected by beam convolution (l < 65) and poor sampling at long baselines (l > 650).
assumptions (5)
  • domain assumption The residual sky signal after point source subtraction is a Gaussian random field.
    Used to simulate 40 realizations for 1-sigma error bars; the authors state this is likely not strictly valid (Section 3, after eq. 4).
  • domain assumption The residual C_l is described by a single power law plus a constant Poisson term within 65 < l < 650.
    The model C_l = A(1000/l)^beta + C is assumed; fits the data for only 6 of 24 PCs.
  • domain assumption The sky signal is statistically isotropic in the plane of the sky for annular binning.
    Used to bin C_l estimates in u-v annuli (Section 2).
  • domain assumption The primary beam and calibration model from Patwa et al. (2021) are accurate in the central 7.5 degree region.
    Source identification and subtraction depend on the beam model; only one pointing is validated against GLEAM (Appendix 1).
  • standard math The TGE normalization M_g from unit-angular-power-spectrum simulations is unbiased.
    Standard estimator calibration from prior same-group papers; not machine-checked.

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Pith. "Pith review of A measurement of Galactic synchrotron emission using MWA drift scan observations." pith.science (2026). https://pith.science/paper/YEXB3QRP

@misc{pith2026250614310,
  author       = {Pith},
  title        = {Pith review of: A measurement of Galactic synchrotron emission using MWA drift scan observations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/YEXB3QRP}},
  note         = {Machine review of arXiv:2506.14310}
}
abstract

Studying the diffuse Galactic synchrotron emission (hereafter, DGSE) at arc-minute angular scale is important to remove the foregrounds for the cosmological 21-cm observations. Statistical measurements of the large-scale DGSE can also be used to constrain the magnetic field and the cosmic ray electron density of our Galaxy's interstellar medium (ISM). Here, we have used the Murchison Widefield Array (MWA) drift scan observations at $154.2 \, {\rm MHz}$ to measure the angular power spectrum $({\cal C}_{\ell})$ of the DGSE of a region of the sky from right ascension (RA) $349^{\circ}$ to $70.3^{\circ}$ at the fixed declination $-26.7^{\circ}$. In this RA range, we have chosen 24 pointing centers (PCs), for which we have removed all the bright point sources above $\sim430 \, {\rm mJy}\,(3\sigma)$, and applied the Tapered Gridded Estimator (TGE) on residual data to estimate the ${\cal C}_{\ell}$. We use the angular multipole range $65 \le \ell \le 650$ to fit the data with a model, ${\cal C}^M_{\ell}=A\times \left(\frac{1000}{\ell}\right)^{\beta}+C$, where we interpret the model as the combination of a power law $(\propto \ell^{-\beta})$ nature of the DGSE and a constant part due to the Poisson fluctuations of the residual point sources. We are able to fit the model ${\cal C}^M_{\ell}$ for six PCs centered at $\alpha=352.5^{\circ}, 353^{\circ}, 357^{\circ}, 4.5^{\circ}, 4^{\circ}$ and $1^{\circ}$. We run the Markov Chain Monte Carlo (MCMC) ensemble sampler to get the best-fit values of the parameters $A, \beta$ and $C$ for these PCs. We see that the values of $A$ vary in the range $155$ to $400$ mK$^{2}$, whereas the $\beta$ varies in the range $0.9$ to $1.7$. We find that the value of $\beta$ is consistent at $2-\sigma$ level with the earlier measurement of the DGSE at similar frequency and angular scales.

Figures

Figures reproduced from arXiv: 2506.14310 by the authors.

Figure 1
Figure 1. This shows the estimated Dℓ = ℓ(ℓ + 1)Cℓ/2π as a function of ℓ for six pointing centered at α = 352.5◦, 353◦, 357◦, 4.5◦, 4◦ and 1 ◦, and δ remain the same for all pointing at δ = −26.7◦. The black lines show the total data before point source subtraction, and the red lines show the Cℓ after removing the sources above 3σ. the C M ℓ beyond the range 65 ≤ ℓ ≤ 650, used for the fitting. This is to show the expected sky… view at source ↗
Figure 2
Figure 2. The blue points show the estimated angular power spectrum Cℓ as a function of ℓ with 1σ error bars from the residual data. The black dot-dashed line shows the model C M ℓ (eq. 4) with best-fitted parameters from the MCMC run. The shaded region (65 ≤ ℓ ≤ 650) shows the data range used for the fitting [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 4
Figure 4. The blue points show the estimated Cℓ as a function of ℓ with 1 − σ error bars from the residual data for a PC centered at α = 37◦. The black dot-dashed line shows the fitted model, which is a straight line with amplitude A = 272.8 +719.2 −238.6. Here, we are not able to fit the data points with a power-law model (eq. 4). mK2 for ℓ values in the range 40 and 1000. Also, it follows a power law Dℓ ∝ ℓ 2 for ℓ > 200. T… view at source ↗

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Works this paper leans on

70 extracted references · 61 canonical work pages

  1. [1]

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

    ENTRY address archivePrefix author booktitle chapter doi edition editor eprint howpublished institution 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 :=...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION format.doi doi empty "" "doi:" doi * if FUNCTION format.eprint eprint empty "" archivePrefix empty "" archivePrefix ":" * if eprint field.or.null * if FUNCTION format.pid eprint empty format.doi format.eprint if FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = ...

  3. [3]

    S., Bharadwaj , S., & Chengalur , J

    Ali , S. S., Bharadwaj , S., & Chengalur , J. N. 2008, , 385, 2166

    work page 2008

  4. [4]

    E., Amiri , M., et al

    Bandura , K., Addison , G. E., Amiri , M., et al. 2014, in , Vol. 9145, Ground-based and Airborne Telescopes V, 914522

    work page 2014

  5. [5]

    F., & Pober, J

    Barry, N., Hazelton, B., Sullivan, I., Morales, M. F., & Pober, J. C. 2016, Monthly Notices of the Royal Astronomical Society, 461, 3135

    work page 2016

  6. [6]

    M., et al

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

    work page 2019

  7. [7]

    P., Hazelton , B

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

    work page 2016

  8. [8]

    L., Hill , R

    Bennett , C. L., Hill , R. S., Hinshaw , G., et al. 2003, , 148, 97

    work page 2003

Show all 70 references
  1. [9]

    G., Brentjens , M

    Bernardi , G., de Bruyn , A. G., Brentjens , M. A., et al. 2009, , 500, 965

    2009

  2. [10]

    2007, IEEE Transactions on Image Processing, 16, 2662

    Bobin, J., Starck, J.-L., Fadili, J., & Moudden, Y. 2007, IEEE Transactions on Image Processing, 16, 2662

    2007

  3. [11]

    F., Hazelton, B., et al

    Byrne, R., Morales, M. F., Hazelton, B., et al. 2021, Monthly Notices of the Royal Astronomical Society, 510, 2011

    2021

  4. [12]

    F., Hazelton , B., et al

    Byrne , R., Morales , M. F., Hazelton , B., et al. 2019, , 875, 70

    2019

  5. [13]

    2019, , 487, 4102

    Chakraborty, A., Datta, A., Choudhuri, S., et al. 2019, , 487, 4102

    2019

  6. [14]

    Chatterjee, S., Bharadwaj, S., Choudhuri, S., Sethi, S., & Patwa, A. K. 2022, , 519, 2410

    2022

  7. [15]

    Chatterjee, S., Elahi, K. M. A., Bharadwaj, S., et al. 2024, Publications of the Astronomical Society of Australia, 41, doi:10.1017/pasa.2024.45

    2024 doi

  8. [16]

    K., Jordan , C

    Chege , J. K., Jordan , C. H., Lynch , C., et al. 2022, , 39, e047

    2022

  9. [17]

    2010, The Astrophysical Journal, 720, 1181

    Cho, J., & Lazarian, A. 2010, The Astrophysical Journal, 720, 1181

    2010

  10. [18]

    S., et al

    Choudhuri, S., Bharadwaj, S., Ali, S. S., et al. 2017, : Letters, 470, L11

    2017

  11. [19]

    2016, , 463, 4093

    Choudhuri, S., Bharadwaj, S., Chatterjee, S., et al. 2016, , 463, 4093

    2016

  12. [20]

    Choudhuri , S., Bharadwaj , S., Roy , N., Ghosh , A., & Ali , S. S. 2016, , 459, 151

    2016

  13. [21]

    2020, , 494, 1936

    Choudhuri, S., Ghosh, A., Roy, N., et al. 2020, , 494, 1936

    2020

  14. [22]

    C., Amiri, M., Bandura, K., et al

    Collaboration, T. C., Amiri, M., Bandura, K., et al. 2022, The Astrophysical Journal Supplement Series, 261, 29

    2022

  15. [23]

    D., & Carilli , C

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

    2010

  16. [24]

    M., et al

    de Oliveira-Costa , A., Tegmark , M., Gaensler , B. M., et al. 2008, , 388, 247

    2008

  17. [25]

    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

  18. [26]

    B., Schinzel, F

    Dowell, J., Taylor, G. B., Schinzel, F. K., Kassim, N. E., & Stovall, K. 2017, Monthly Notices of the Royal Astronomical Society, 469, 4537

    2017

  19. [27]

    W., Anderson , M

    Eastwood , M. W., Anderson , M. M., Monroe , R. M., et al. 2018, , 156, 32

    2018

  20. [28]

    Elahi, K. M. A., Bharadwaj, S., Chatterjee, S., et al. 2025, Monthly Notices of the Royal Astronomical Society, 540, 2745

    2025

  21. [29]

    Elahi, K. M. A., Bharadwaj, S., Pal, S., et al. 2023, Monthly Notices of the Royal Astronomical Society, 525, 3439

    2023

  22. [30]

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

    Foreman-Mackey , D., Hogg , D. W., Lang , D., & Goodman , J. 2013, PASP, 125, 306

    2013

  23. [31]

    Franzen , T. M. O., Jackson , C. A., Offringa , A. R., et al. 2016, , 459, 3314

    2016

  24. [32]

    S., & Chengalur , J

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

    2012

  25. [33]

    J., Fosalba , P., et al

    Giardino , G., Banday , A. J., Fosalba , P., et al. 2001, , 371, 708

    2001

  26. [34]

    2010, Communications in Applied Mathematics and Computational Science, 5, 65

    Goodman , J., & Weare , J. 2010, Communications in Applied Mathematics and Computational Science, 5, 65

    2010

  27. [35]

    2017, CURRENT SCIENCE, 113, 707

    Gupta, Y., Ajithkumar, B., Kale, H., et al. 2017, CURRENT SCIENCE, 113, 707

    2017

  28. [36]

    E., May , J., Alvarez , H., & Maeda , K

    Guzm \'a n , A. E., May , J., Alvarez , H., & Maeda , K. 2011, , 525, A138

    2011

  29. [37]

    Haslam , C. G. T., Klein , U., Salter , C. J., et al. 1981, , 100, 209

    1981

  30. [38]

    R., et al

    Hothi, I., Chapman, E., Pritchard, J. R., et al. 2020, Monthly Notices of the Royal Astronomical Society, 500, 2264

    2020

  31. [39]

    2013 a , , 549, A56

    Iacobelli , M., Haverkorn , M., & Katgert , P. 2013 a , , 549, A56

    2013

  32. [40]

    2013 b , , 558, A72

    Iacobelli , M., Haverkorn , M., Orr \'u , E., et al. 2013 b , , 558, A72

    2013

  33. [41]

    T., Jagannathan, P., Mooley, K

    Intema, H. T., Jagannathan, P., Mooley, K. P., & Frail, D. A. 2017, A&A, 598, A78

    2017

  34. [42]

    2015, Advancing Astrophysics with the Square Kilometre Array (AASKA14), 1

    Koopmans , L., Pritchard , J., Mellema , G., et al. 2015, Advancing Astrophysics with the Square Kilometre Array (AASKA14), 1

    2015

  35. [43]

    2008, , 479, 641

    La Porta , L., Burigana , C., Reich , W., & Reich , P. 2008, , 479, 641

    2008

  36. [44]

    2012, The Astrophysical Journal, 747, 5

    Lazarian, A., & Pogosyan, D. 2012, The Astrophysical Journal, 747, 5

    2012

  37. [45]

    J., Cappallo , R

    Lonsdale , C. J., Cappallo , R. J., Morales , M. F., et al. 2009, IEEE Proceedings, 97, 1497

    2009

  38. [46]

    2002, Monthly Notices of the Royal Astronomical Society, 334, 53

    Maino, D., Farusi, A., Baccigalupi, C., et al. 2002, Monthly Notices of the Royal Astronomical Society, 334, 53

    2002

  39. [47]

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

    2013

  40. [48]

    G., Mevius, M., Koopmans, L

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

    2020

  41. [49]

    2015, PyBDSF: Python Blob Detection and Source Finder , Astrophysics Source Code Library, record ascl:1502.007, ascl:1502.007

    Mohan , N., & Rafferty , D. 2015, PyBDSF: Python Blob Detection and Source Finder , Astrophysics Source Code Library, record ascl:1502.007, ascl:1502.007

    2015

  42. [50]

    R., & Smirnov, O

    Offringa, A. R., & Smirnov, O. 2017, Monthly Notices of the Royal Astronomical Society, 471, 301

    2017

  43. [51]

    R., McKinley, B., Hurley-Walker, N., et al

    Offringa, A. R., McKinley, B., Hurley-Walker, N., et al. 2014, Monthly Notices of the Royal Astronomical Society, 444, 606

    2014

  44. [52]

    G., Bandura , K., et al

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

    2013

  45. [53]

    K., Datta , A., & Mazumder , A

    Pal , S. K., Datta , A., & Mazumder , A. 2024, arXiv e-prints, arXiv:2407.17573

    2024 arXiv

  46. [54]

    H., Yatawatta, S., Koopmans, L

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

    2017

  47. [55]

    K., Sethi, S., & Dwarakanath, K

    Patwa, A. K., Sethi, S., & Dwarakanath, K. S. 2021, , 504, 2062

    2021

  48. [56]

    1986, , 63, 205

    Reich , P., & Reich , W. 1986, , 63, 205

    1986

  49. [57]

    C., & Reich , W

    Reich , P., Testori , J. C., & Reich , W. 2001, , 376, 861

    2001

  50. [58]

    1982, , 48, 219

    Reich , W. 1982, , 48, 219

    1982

  51. [59]

    J., Bigot-Sazy , M

    Remazeilles , M., Dickinson , C., Banday , A. J., Bigot-Sazy , M. A., & Ghosh , T. 2015, , 451, 4311

    2015

  52. [60]

    Rice, J. A. 2006, Mathematical Statistics and Data Analysis, 3rd edn. (Belmont, CA: Duxbury Press), see Chapter 9 (Hypothesis Testing), Section 9.2

    2006

  53. [61]

    2023, Publications of the Astronomical Society of the Pacific, 135, 036001

    Singal, J., Fornengo, N., Regis, M., et al. 2023, Publications of the Astronomical Society of the Pacific, 135, 036001

    2023

  54. [62]

    Sirothia, S. K. , Lecavelier des Etangs, A. , Gopal-Krishna , Kantharia, N. G. , & Ishwar-Chandra, C. H. 2014, A&A, 562, A108

    2014

  55. [63]

    K., et al

    Swarup , G., Ananthakrishnan , S., Kapahi , V. K., et al. 1991, Current Science, Vol. 60, NO.2/JAN25, P. 95, 1991, 60, 95

    1991

  56. [64]

    2013, , 776, 6

    Thyagarajan , N., Udaya Shankar , N., Subrahmanyan , R., et al. 2013, , 776, 6

    2013

  57. [65]

    J., Goeke , R., Bowman , J

    Tingay , S. J., Goeke , R., Bowman , J. D., et al. 2013, , 30, e007

    2013

  58. [66]

    M., Jordan, C

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

    2020

  59. [67]

    P., Wise , M

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

    2013

  60. [68]

    B., Lenc, E., Bell, M

    Wayth, R. B., Lenc, E., Bell, M. E., et al. 2015, Publications of the Astronomical Society of Australia, 32, e025

    2015

  61. [69]

    B., Tingay, S

    Wayth, R. B., Tingay, S. J., Trott, C. M., et al. 2018, Publications of the Astronomical Society of Australia, 35, e033

    2018

  62. [70]

    S., et al

    Zheng, H., Tegmark, M., Dillon, J. S., et al. 2016, Monthly Notices of the Royal Astronomical Society, 464, 3486

    2016

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