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A first glimpse at the MeerKAT DEEP2 field at S-band

T0 review · 2 major / 5 minor · reviewed 2026-08-11 · deepseek-v4-flash

Pith's one-line read With 70 minutes on source, MeerKAT S-band delivers a 1,199-source catalogue of the DEEP2 field, with source counts consistent with established surveys.

desk verdict A useful pilot data paper with a new public catalogue; the source-count consistency claim needs a quantified completeness caveat. read the letter →

arxiv 2412.09314 v1 pith:JB7NL2BU submitted 2024-12-12 astro-ph.GA

classification astro-ph.GA
keywords MeerKATS-bandradiocontinuumsourcecountsDEEP2fieldextragalacticcataloguespectralindexinterferometry
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

The paper presents the first widefield extragalactic continuum catalogue made with the MeerKAT S-band receivers, targeting the radio-selected DEEP2 field. By combining the S1 and S4 sub-bands and about 70 minutes on source, the authors produce an image with 4.7 microjansky per beam sensitivity and detect 1,199 sources down to 16.9 microjansky. They show that the completeness-corrected differential source counts agree with established L-band and 3-GHz surveys, and that stacking faint L-band sources pushes a count estimate down to roughly 10 microjansky. The wider point is that even a short single-pointing S-band observation yields scientifically usable extragalactic results, which supports the case for larger MeerKAT S-band surveys.

What carries the argument

The load-bearing element is the MeerKAT S-band receiver system, whose band is split into five sub-bands (S0–S4); the paper combines S1 and S4 into a contiguous 1.97–3.50 GHz coverage, excludes spectral windows with high noise, and images with WSClean at two Briggs robust weightings. Source detection uses PyBDSF with a 3-sigma island threshold and 5-sigma pixel threshold. Completeness is measured by injecting SKADS-simulated point and extended sources into residual images and re-running detection; the resulting completeness curves enter the source-count correction under the assumption that one third of sources are point-like and two thirds extended. Primary-beam correction uses per-spectral-window holographic beam models combined with the same weights as the multi-frequency synthesis image, and cosmic variance on the counts is estimated by resampling SKADS skies over the same area.

What would settle it

Observe DEEP2 again at S-band to roughly 1 microjansky per beam rms with resolution comparable to the R=-0.5 image, and measure the point-source fraction and counts below 0.1 mJy. If the point-source fraction deviates strongly from one third, or the Euclidean-normalized counts fall outside the uncertainties reported here, the completeness-corrected counts and the claimed consistency with the literature are falsified.

Watch

Extended reading notes

Core claim

The central claim is that MeerKAT's new S-band system is a working widefield extragalactic imaging instrument. Combining sub-bands S1 (1.97–2.84 GHz) and S4 (2.62–3.50 GHz) in a multi-frequency-synthesis image, with 70 minutes on source per sub-band and 52–55 antennas, the authors reach a robust-weighted rms of 4.7 microjansky per beam and extract 1,199 sources at R=0.3 (670 at R=-0.5). They report completeness-corrected Euclidean-normalized differential source counts at 2.5 GHz down to about 20 microjansky that are consistent, within the SKADS-estimated cosmic variance, with the L-band DEEP2 counts and VLA-COSMOS 3-GHz counts. They also derive median spectral indices of about -0.5 to -0.6 across an effective 1.8 GHz frequency baseline, identify 18–22 percent of sources as resolved, and use image-plane stacking to estimate lower-limit counts down to 10 microjansky, finding them consistent with simulations though lower than some published counts.

Load-bearing premise

The completeness correction that converts raw detections to true source counts assumes, following the SKADS simulation, that exactly one third of sources are point-like and the rest extended; if the real sky has a different size distribution, the corrected counts in the faint regime where corrections are large will be wrong.

Editorial extensions

If this is right

  • A single 70-minute MeerKAT S-band pointing reaches source densities that previously required much longer VLA campaigns, making large-area S-band surveys cheap.
  • The S-band catalogue, combined with the L-band DEEP2 data, yields spectral indices over an effective 1.8 GHz baseline that can separate flat-spectrum core-dominated sources from steeper star-forming and synchrotron populations.
  • Stacking L-band source positions produces a 62-sigma detection of the faint S-band population, demonstrating that source counts can be extended below the detection threshold.
  • Because a single MeerKAT S-band pointing covers roughly 16 times the sky of the deepest published S-band survey at comparable sensitivity, future surveys will cut cosmic-variance and Poisson scatter.
  • The authors recommend a robust weighting of R=0.3 as the optimal choice for broadband extragalactic S-band imaging.

Reading between the lines

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

  • If the assumed one-third point-source fraction is off, the completeness-corrected counts below about 0.1 mJy are biased; a deeper, higher-resolution S-band image of DEEP2 would settle this directly.
  • The 26 percent shortfall in stacked S-band flux relative to L-band expectations, if not a systematic of stacking, implies a median spectral index near -1.2 for the faint population, which would steepen all S-band count conversions at the faint end.
  • The demonstrated short-integration sensitivity suggests the upcoming MeerKAT+ array could push into confusion-limited sub-microjansky S-band imaging over wide fields, not just statistical stacking.
  • The S1 high-frequency excess noise and beam-elongation peaks mean that survey designers should prefer the S2 sub-band, as the authors note, for maximum usable bandwidth.
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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

2 major / 5 minor

Summary. This paper presents MeerKAT S-band (2.5 GHz) continuum imaging of the DEEP2 field from about 70 minutes on source per sub-band, with detailed calibration, primary-beam correction, source detection, astrometric verification against the Matthews et al. (2021a) L-band catalogue, spectral index measurements, resolved-source classification, completeness and purity simulations, differential source counts, and image-plane stacking. The main scientific claims are that the resulting R=0.3 catalogue (1199 sources) and R=-0.5 catalogue (670 sources) constitute the first S-band extragalactic catalogue of this field, that the differential source counts are consistent with literature measurements and SKADS within the expected variance, and that the spectral index distributions have medians of alpha_L^S1 = -0.52 and alpha_S1^S4 = -0.61.

Significance. The paper is a carefully executed pilot study with substantial technical value: the calibration and imaging steps are described in enough detail to be reproduced, the astrometric offsets are small and well characterised, the noise is tested for Gaussianity, and the completeness and purity simulations follow standard practice. The catalogue and images are made publicly available. The main caveat is the completeness correction, which assumes a fixed point-source fraction derived from SKADS; because the faint-end consistency claim rests on corrected counts in a regime where the correction is large, this assumption needs to be tested explicitly. If the counts survive such a robustness test, the paper will be a useful reference for planning future MeerKAT S-band surveys.

major comments (2)
  1. [Section 4.4 and footnote 8] The completeness-corrected source counts assume that point sources constitute one third of the population. Fig. 7 shows that the point-source and extended-source completeness curves differ substantially below roughly 0.1 mJy, where the correction factors are large. Footnote 8 acknowledges that star-forming galaxies are classified as extended in the SKADS catalogue even though most are likely unresolved at the current resolution. Since the faint population is dominated by star-forming galaxies, the true point-source fraction is plausibly larger than 1/3; in that case the blended completeness used here is underestimated and the corrected counts in the faintest bins of Table C1 are overestimated. The claimed consistency with Matthews et al. (2021a) and Smolčić et al. (2017) at S < 100 uJy is therefore contingent on an unverified size-distribution assumption. I request a robustness test, e.g. recomputing the corrected counts for point-source fractions of 0.5, 0.7, and 1.0, or, if such a test is not feasible, an explicit statement that the faint-end consistency is not robust to this assumption.
  2. [Section 4.3] The stacked S-band flux density is 26% lower than expected from the L-band catalogue assuming alpha = -0.7. The paper attributes this to a systematic effect but does not quantify its possible impact on the catalogue flux scale or on the corrected source counts. A global offset in the faint-end S-band flux scale would shift sources between flux density bins and could bias the counts, so this is not only a stacking issue. I ask for a short assessment of the maximum plausible effect of this 26% deficit on the source counts in the affected flux range, or an explicit statement that the deficit is confined to the stacking analysis and cannot affect the catalogue-based counts.
minor comments (5)
  1. [Section 4.1] The sentence 'Resolved and unresolved sources are respectively modelled as delta functions and Gaussians' is inverted relative to the SKADS description given in the preceding sentence; unresolved sources are the delta functions and resolved sources are the Gaussians. Please correct this and confirm that the simulation code uses the intended mapping.
  2. [Section 4.2] There is a duplicated word in 'we do not expect expect extreme outliers'; it should read 'we do not expect extreme outliers'.
  3. [Section 3.2] There is a duplicated article in 'the the majority of these sources'; it should read 'the majority of these sources'.
  4. [Section 3.3.2] There is a duplicated article in 'subtract the the fitted uncertainty on S_peak'; it should read 'subtract the fitted uncertainty on S_peak'.
  5. [Section 4.4] There is a duplicated 'where' in 'where where simulations and different observations begin to disagree'; it should read 'where simulations and different observations begin to disagree'.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the catalogue and source counts are derived from new S-band data and benchmarked against external literature, with the one modelling prior explicitly stated.

full rationale

The paper's central claims—the first widefield MeerKAT S-band extragalactic catalogue, the 1199 detected sources, the per-source spectral indices, and the differential source counts—are derived directly from the new S-band images and compared against external data sets (Matthews et al. 2021a, Smolčić et al. 2017, and the SKADS simulations). No equation in the derivation reduces to its own inputs. Spectral indices are measured from the observed L-band and S-band SPW flux densities rather than assumed in the derivation; the alpha = -0.7 used to convert literature counts to 2.5 GHz is an external comparison convention and is not fitted from this data set. The completeness correction assumes that point sources make up one third of the population, following the SKADS size distribution. This is a stated external simulation prior, not a parameter fitted from the DEEP2 data, and it does not force the final counts to agree with any particular comparison because the corrected counts retain the observed raw-count shape and the quoted uncertainties include completeness, Poisson, and cosmic-variance contributions. The paper also explicitly acknowledges where the completeness corrections become inadequate below about 50 microJy. There is no load-bearing self-citation: references to Mauch et al. (2020), Matthews et al. (2021a), and Wilman et al. (2008) are external data and simulation products, and the only co-author self-citations concern instrumental or methodological background (e.g., Wagenveld et al. 2023 for the size-ratio distribution), not the central results. The sentence in Section 4.1 stating that resolved and unresolved sources are 'respectively modelled as delta functions and Gaussians' is internally inconsistent with the preceding description of the simulation setup and appears to be a drafting typo, but it is a modelling-description issue, not circular reasoning. Overall, the derivation chain is self-contained against external benchmarks and no circular step is present.

Assumptions & free parameters 2 free parameters · 3 assumptions · 0 invented entities

The central results rest on the absolute flux scale set by PKS 0408-65, the holographic primary beam model, and the SKADS-based completeness and cosmic variance corrections. The catalogue is benchmarked externally, so circularity is low.

free parameters (2)
  • point source fraction in completeness correction = 1/3 (assumed from SKADS)
    Section 4.4: source counts are corrected for completeness assuming one third of sources are point-like; the corrected counts depend on this ratio.
  • spectral index for scaling literature source counts = alpha = -0.7 (assumed)
    Used in Section 4.4 and Figure 8 to convert 1.4 GHz and 3 GHz counts to 2.5 GHz for comparison; not fitted to DEEP2 data.
assumptions (3)
  • domain assumption The absolute flux density scale is set by the PKS 0408-65 model with spix = [-1.2897, -0.2353, 0.0861].
    Section 2.2: all source flux densities inherit this scale; an error would shift the entire source count normalization.
  • domain assumption The holographic primary beam model accurately represents the S-band beam response.
    Section 2.3: primary beam correction uses holographic measurements; errors would bias flux densities away from the pointing centre.
  • domain assumption SKADS simulated skies represent the true source size and clustering statistics.
    Sections 4.1 and 4.4: completeness curves and cosmic variance estimates are derived from SKADS.

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Cite this review

Pith. "Pith review of A first glimpse at the MeerKAT DEEP2 field at S-band." pith.science (2026). https://pith.science/paper/JB7NL2BU

@misc{pith2026241209314,
  author       = {Pith},
  title        = {Pith review of: A first glimpse at the MeerKAT DEEP2 field at S-band},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/JB7NL2BU}},
  note         = {Machine review of arXiv:2412.09314}
}
abstract

We present the first widefield extragalactic continuum catalogue with the MeerKAT S-band (2.5 GHz), of the radio-selected DEEP2 field. The combined image over the S1 (1.96 - 2.84 GHz) and S4 (2.62 - 3.50 GHz) sub-bands has an angular resolution of 6.8''$\times$3.6'' (4.0''$\times$2.4'') at a robust weighting of $R = 0.3$ ($R=-0.5$) and a sensitivity of 4.7 (7.5) $\mu$Jy beam$^{-1}$ with an on-source integration time of 70 minutes and a minimum of 52 of the 64 antennas, for respective observations. We present the differential source counts for this field, as well as a morphological comparison of resolved sources between S-band and archival MeerKAT L-band images. We find consistent source counts with the literature and provide spectral indices fitted over a combined frequency range of 1.8 GHz. These observations provide an important first demonstration of the capabilities of MeerKAT S-band imaging with relatively short integration times, as well as a comparison with existing S-band surveys, highlighting the rich scientific potential with future MeerKAT S-band surveys.

Figures

Figures reproduced from arXiv: 2412.09314 by the authors.

Figure 1
Figure 1. Top: Flux density of J0252−7104 (PKS 0252−71), the phase calibrator used for the observations, as a function of frequency. Bottom: The residual flux density, after applying the flux density model (green), as a function of frequency. Each marker shows the averaged measurement per SPW of both subbands (S1 in red and S4 in blue). The crosses indicates the resulting flux densities of the SPW images of the full concatena… view at source ↗
Figure 2
Figure 2. The central 54’×54’ of the combined primary beam-corrected S1- and S4-subband image of the DEEP2 field, with a Briggs robust weighting of 𝑅 = 0.3. The FWHM of the primary beam is indicated by the yellow dashed circle, as specified in Section 2.3 [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Astrometric offsets of detected sources in the 𝑅 = 0.3 image with respect to the cross-matched components in the L-band observations. The points are colourised according to the number of matches 𝑛 in the L-band component catalogue for a given S-band source. The synthesised beams of the S- and L-band observations are shown by the black and blue dashed ellipses, respectively. The standard deviations of the offsets are… view at source ↗
Figures from the paper (5 more)
Figure 4
Figure 4. Figure 4: Distribution of spectral indices for 𝛼 S1 L (blue) and 𝛼 S4 S1 (red) for sources above 10𝜎. The medians of the respective distributions are indicated by the dashed lines. The PyBDSF fit uncertainty for 𝑆tot includes the uncertainty on 𝑆peak as well as the uncertainty o…
Figure 5
Figure 5. Figure 5: Cutouts of selected extended sources in L-band (Mauch et al. 2020, left), S-band 𝑅 = 0.3 (centre) and 𝑅 = −0.5 (right). The restoring beam for each image is shown in the bottom left corner. From top to bottom, the sources shown are J041339–794637, J041654–795445 and J0…
Figure 6
Figure 6. Figure 6: Distribution of source flux densities from the 𝑅 = 0.3 (6.8” × 3.6”, red) and 𝑅 = −0.5 (4.0” × 2.4”, yellow) catalogues described in Section 3.4. 10−5 10−4 10−3 10−2 Flux density [Jy] 0.0 0.2 0.4 0.6 0.8 1.0 Completeness Point Extended R = -0.5 R = 0.3 [PITH_FULL_IMAG…
Figure 7
Figure 7. Figure 7: The catalogue completeness for point (solid line) and extended sources (dashed) as a function of flux density. The completeness curves are shown in red and yellow for 𝑅 = 0.3 and 𝑅 = −0.5, respectively. The shaded regions show the standard deviation and the black dotte…
Figure 8
Figure 8. Figure 8: Completeness-corrected differential source counts for the DEEP2 S-band catalogues with 𝑅 = 0.3 (red) and 𝑅 = −0.5 (yellow). The expected differential source counts from the SKADS catalogue is shown by the black solid line, with the grey shaded regions indicating the si…

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Works this paper leans on

46 extracted references · 12 canonical work pages

  1. [1]

    Algera H. S. B., et al., 2020, @doi [ ] 10.3847/1538-4357/abb77a , https://ui.adsabs.harvard.edu/abs/2020ApJ...903..139A 903, 139

  2. [2]

    S., 1995, PhD thesis, New Mexico Institute of Mining and Technology

    Briggs D. S., 1995, PhD thesis, New Mexico Institute of Mining and Technology

  3. [3]

    J., 1984, @doi [ ] 10.1086/162705 , https://ui.adsabs.harvard.edu/abs/1984ApJ...287..461C 287, 461

    Condon J. J., 1984, @doi [ ] 10.1086/162705 , https://ui.adsabs.harvard.edu/abs/1984ApJ...287..461C 287, 461

  4. [4]

    J., 1992, @doi [ ] 10.1146/annurev.aa.30.090192.003043 , https://ui.adsabs.harvard.edu/abs/1992ARA&A..30..575C 30, 575

    Condon J. J., 1992, @doi [ ] 10.1146/annurev.aa.30.090192.003043 , https://ui.adsabs.harvard.edu/abs/1992ARA&A..30..575C 30, 575

  5. [5]

    Condon J., 2015, in The Many Facets of Extragalactic Radio Surveys: Towards New Scientific Challenges. p. 4, @doi 10.22323/1.267.0004

  6. [6]

    J., Cotton W

    Condon J. J., Cotton W. D., Greisen E. W., Yin Q. F., Perley R. A., Taylor G. B., Broderick J. J., 1998, @doi [ ] 10.1086/300337 , https://ui.adsabs.harvard.edu/abs/1998AJ....115.1693C 115, 1693

  7. [7]

    D., et al., 2018, @doi [ ] 10.3847/1538-4357/aaaec4 , https://ui.adsabs.harvard.edu/abs/2018ApJ...856...67C 856, 67

    Cotton W. D., et al., 2018, @doi [ ] 10.3847/1538-4357/aaaec4 , https://ui.adsabs.harvard.edu/abs/2018ApJ...856...67C 856, 67

  8. [8]

    Delhaize J., et al., 2017, @doi [ ] 10.1051/0004-6361/201629430 , https://ui.adsabs.harvard.edu/abs/2017A&A...602A...4D 602, A4

Show all 46 references
  1. [10]

    P., Woudt P

    Fairall A. P., Woudt P. A., 2006, @doi [ ] 10.1111/j.1365-2966.2005.09859.x , https://ui.adsabs.harvard.edu/abs/2006MNRAS.366..267F 366, 267

  2. [11]

    Franzen T. M. O., et al., 2015, @doi [ ] 10.1093/mnras/stv1866 , https://ui.adsabs.harvard.edu/abs/2015MNRAS.453.4020F 453, 4020

  3. [12]

    Originally published in: 2021A&A...649A...1G; doi:10.5270/esa-1ug, @doi 10.26093/cds/vizier.1350

    Gaia Collaboration 2020, VizieR Online Data Catalog: Gaia EDR3 (Gaia Collaboration, 2020) , VizieR On-line Data Catalog: I/350. Originally published in: 2021A&A...649A...1G; doi:10.5270/esa-1ug, @doi 10.26093/cds/vizier.1350

  4. [13]

    Gaia Collaboration et al., 2023, @doi [ ] 10.1051/0004-6361/202243940 , https://ui.adsabs.harvard.edu/abs/2023A&A...674A...1G 674, A1

  5. [14]

    L., et al., 2023, @doi [ ] 10.1093/mnras/stac3320 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.520.2668H 520, 2668

    Hale C. L., et al., 2023, @doi [ ] 10.1093/mnras/stac3320 , https://ui.adsabs.harvard.edu/abs/2023MNRAS.520.2668H 520, 2668

  6. [15]

    Heesen V., et al., 2019, @doi [ ] 10.1051/0004-6361/201833905 , https://ui.adsabs.harvard.edu/abs/2019A&A...622A...8H 622, A8

  7. [16]

    J., Condon J

    Heywood I., Jarvis M. J., Condon J. J., 2013, @doi [ ] 10.1093/mnras/stt843 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.432.2625H 432, 2625

  8. [17]

    Time-Frequency Methods and Phase Space

    Holschneider M., Kronland-Martinet R., Morlet J., Tchamitchian P., 1989, in Combes J.-M., Grossmann A., Tchamitchian P., eds, Wavelets. Time-Frequency Methods and Phase Space. p. 286

  9. [18]

    Jarvis M., et al., 2016, in MeerKAT Science: On the Pathway to the SKA. p. 6 ( @eprint arXiv 1709.01901 ), @doi 10.22323/1.277.0006

  10. [19]

    Jonas J., MeerKAT Team 2016, in MeerKAT Science: On the Pathway to the SKA. p. 1, @doi 10.22323/1.277.0001

  11. [20]

    Karim A., et al., 2011, @doi [ ] 10.1088/0004-637X/730/2/61 , https://ui.adsabs.harvard.edu/abs/2011ApJ...730...61K 730, 61

  12. [21]

    Kramer M., et al., 2016, in MeerKAT Science: On the Pathway to the SKA. p. 3, @doi 10.22323/1.277.0003

  13. [22]

    K., et al., 2020, @doi [ ] 10.3847/1538-4357/aba044 , https://ui.adsabs.harvard.edu/abs/2020ApJ...899...58L 899, 58

    Leslie S. K., et al., 2020, @doi [ ] 10.3847/1538-4357/aba044 , https://ui.adsabs.harvard.edu/abs/2020ApJ...899...58L 899, 58

  14. [23]

    M., Condon J

    Matthews A. M., Condon J. J., Cotton W. D., Mauch T., 2021a, @doi [ ] 10.3847/1538-4357/abdd37 , https://ui.adsabs.harvard.edu/abs/2021ApJ...909..193M 909, 193

  15. [24]

    M., Condon J

    Matthews A. M., Condon J. J., Cotton W. D., Mauch T., 2021b, @doi [ ] 10.3847/1538-4357/abfaf6 , https://ui.adsabs.harvard.edu/abs/2021ApJ...914..126M 914, 126

  16. [25]

    Mauch T., et al., 2020, @doi [ ] 10.3847/1538-4357/ab5d2d , https://ui.adsabs.harvard.edu/abs/2020ApJ...888...61M 888, 61

  17. [26]

    P., Waters B., Schiebel D., Young W., Golap K., 2007, in Shaw R

    McMullin J. P., Waters B., Schiebel D., Young W., Golap K., 2007, in Shaw R. A., Hill F., Bell D. J., eds, Astronomical Society of the Pacific Conference Series Vol. 376, Astronomical Data Analysis Software and Systems XVI. p. 127

  18. [27]

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

  19. [28]

    J., 2009, @doi [ ] 10.1088/0004-637X/706/1/482 , https://ui.adsabs.harvard.edu/abs/2009ApJ...706..482M 706, 482

    Murphy E. J., 2009, @doi [ ] 10.1088/0004-637X/706/1/482 , https://ui.adsabs.harvard.edu/abs/2009ApJ...706..482M 706, 482

  20. [29]

    R., et al., 2014, @doi [ ] 10.1093/mnras/stu1368 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.444..606O 444, 606

    Offringa A. R., et al., 2014, @doi [ ] 10.1093/mnras/stu1368 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.444..606O 444, 606

  21. [30]

    \'E ., 2024, @doi [ ] 10.1093/mnras/stad3411 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.3436P 527, 3436

    Perger K., Frey S., Gab \'a nyi K. \'E ., 2024, @doi [ ] 10.1093/mnras/stad3411 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527.3436P 527, 3436

  22. [31]

    R., Ricci R., Parma P., Gregorini L., Ekers R

    Prandoni I., de Ruiter H. R., Ricci R., Parma P., Gregorini L., Ekers R. D., 2010, @doi [ ] 10.1051/0004-6361/200913052 , https://ui.adsabs.harvard.edu/abs/2010A&A...510A..42P 510, A42

  23. [32]

    F., Beswick R

    Radcliffe J. F., Beswick R. J., Thomson A. P., Njeri A., Muxlow T. W. B., 2024, @doi [ ] 10.1093/mnras/stad2694 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.527..942R 527, 942

  24. [33]

    J., 1967, @doi [ ] 10.1093/mnras/136.3.279 , https://ui.adsabs.harvard.edu/abs/1967MNRAS.136..279R 136, 279

    Rees M. J., 1967, @doi [ ] 10.1093/mnras/136.3.279 , https://ui.adsabs.harvard.edu/abs/1967MNRAS.136..279R 136, 279

  25. [34]

    K., et al., 2021, @doi [ ] 10.3847/1538-4357/ac2239 , https://ui.adsabs.harvard.edu/abs/2021ApJ...923...31S 923, 31

    Sarbadhicary S. K., et al., 2021, @doi [ ] 10.3847/1538-4357/ac2239 , https://ui.adsabs.harvard.edu/abs/2021ApJ...923...31S 923, 31

  26. [35]

    arXiv:2308.05192

    Sinha A., Mangla S., Datta A., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2308.05192 , https://ui.adsabs.harvard.edu/abs/2023arXiv230805192S p. arXiv:2308.05192

  27. [36]

    Smol c i \'c V., et al., 2016, @doi [ ] 10.1051/0004-6361/201526818 , https://ui.adsabs.harvard.edu/abs/2016A&A...592A..10S 592, A10

  28. [37]

    Smol c i \'c V., et al., 2017, @doi [ ] 10.1051/0004-6361/201628704 , https://ui.adsabs.harvard.edu/abs/2017A&A...602A...1S 602, A1

  29. [38]

    D., et al., 2023, @doi [ ] 10.1051/0004-6361/202245477 , https://ui.adsabs.harvard.edu/abs/2023A&A...673A.113W 673, A113

    Wagenveld J. D., et al., 2023, @doi [ ] 10.1051/0004-6361/202245477 , https://ui.adsabs.harvard.edu/abs/2023A&A...673A.113W 673, A113

  30. [39]

    L., Helfand D

    White R. L., Helfand D. J., Becker R. H., Glikman E., de Vries W., 2007, @doi [ ] 10.1086/507700 , https://ui.adsabs.harvard.edu/abs/2007ApJ...654...99W 654, 99

  31. [40]

    H., et al., 2013, @doi [ ] 10.1093/mnras/sts478 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.429.2080W 429, 2080

    Whittam I. H., et al., 2013, @doi [ ] 10.1093/mnras/sts478 , https://ui.adsabs.harvard.edu/abs/2013MNRAS.429.2080W 429, 2080

  32. [41]

    J., et al., 2008, @doi [ ] 10.1111/j.1365-2966.2008.13486.x , https://ui.adsabs.harvard.edu/abs/2008MNRAS.388.1335W 388, 1335

    Wilman R. J., et al., 2008, @doi [ ] 10.1111/j.1365-2966.2008.13486.x , https://ui.adsabs.harvard.edu/abs/2008MNRAS.388.1335W 388, 1335

  33. [42]

    Zwart J. T. L., Jarvis M. J., Deane R. P., Bonfield D. G., Knowles K., Madhanpall N., Rahmani H., Smith D. J. B., 2014, @doi [ ] 10.1093/mnras/stu053 , https://ui.adsabs.harvard.edu/abs/2014MNRAS.439.1459Z 439, 1459

  34. [43]

    S., 2023, @doi [ ] 10.3847/1538-3881/acabc3 , https://ui.adsabs.harvard.edu/abs/2023AJ....165...78D 165, 78

    de Villiers M. S., 2023, @doi [ ] 10.3847/1538-3881/acabc3 , https://ui.adsabs.harvard.edu/abs/2023AJ....165...78D 165, 78

  35. [44]

    S., Cotton W

    de Villiers M. S., Cotton W. D., 2022, @doi [ ] 10.3847/1538-3881/ac460a , 163, 135

  36. [45]

    van der Vlugt D., et al., 2021, @doi [ ] 10.3847/1538-4357/abcaa3 , https://ui.adsabs.harvard.edu/abs/2021ApJ...907....5V 907, 5

  37. [46]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.stat...

  38. [47]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.stat...

Pith tools

Reviewed August 11, 2026 · model on record in the stance chip above.