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arxiv: 2606.22432 · v1 · pith:3T6CX6ZHnew · submitted 2026-06-21 · 🌌 astro-ph.CO · astro-ph.GA

Tracing Large-scale Structure with the MeerKLASS On-the-Fly Survey: Angular Clustering of Radio Sources at 816 MHz

Sourabh Paul , Suman Chatterjee , Keith Grainge , Laura Wolz , Aishrila Mazumder , Steven Cunnington , Sarvesh Mangla , Joseph J. Mohr
show 3 more authors
Mario G. Santos Oleg Smirnov Cyril Tasse
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Pith reviewed 2026-06-26 10:04 UTC · model grok-4.3

classification 🌌 astro-ph.CO astro-ph.GA
keywords angular clusteringradio sourcesMeerKATcorrelation functionlarge-scale structurebias measurementcontinuum survey
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The pith

MeerKAT radio sources at 816 MHz exhibit positive angular clustering from 0.02 to 10 degrees, with effective bias 1.5-2.0 set by redshift priors.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper measures the angular two-point correlation function of radio sources over an 800 square degree field at 816 MHz. It reports a stable positive signal on scales from 0.02 to 10 degrees and fits an amplitude on intermediate scales. Using two bracketing redshift distributions, it extracts an effective large-scale bias for the sources. The work positions the survey as a new wide-area radio-continuum dataset for large-scale structure studies. Future releases with better redshift calibration are expected to support population splits and bias evolution tracking.

Core claim

We present the first measurement of the angular two-point correlation function w(θ) of radio sources from the MeerKAT Large Area Synoptic Survey UHF on-the-fly continuum Data Release 1, detecting positive clustering over 0.02° ≲ θ ≲ 10°. Modelling the intermediate-scale signal with a fixed-slope power law yields A(1°)=(1.434±0.475)×10^{-3}. Fitting ΛCDM projected-matter templates with two T-RECS redshift priors gives b_eff=1.998±0.350 (AGN prior) and b_eff=1.530±0.265 (TOTAL prior), with dominant uncertainty from N(z).

What carries the argument

Angular two-point correlation function w(θ), fitted with a fixed-slope power law on intermediate scales and Limber-projected ΛCDM templates plus integral-constraint correction to extract effective bias b_eff.

If this is right

  • The measured clustering amplitude remains stable under reasonable changes to depth mask and flux threshold on intermediate and large scales.
  • Limber inversion of the power-law amplitude produces comoving correlation lengths r0 of 6.18±1.13 and 5.59±1.02 h^{-1} Mpc for the two priors.
  • The survey provides a new wide-area, intermediate-frequency dataset for radio-continuum clustering studies.
  • Expanded coverage plus overlapping optical/IR spectroscopy will enable population-split clustering and bias-evolution measurements.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Improved redshift information could separate contributions from AGN and star-forming galaxies in the clustering signal.
  • The dataset could be cross-correlated with optical large-scale structure tracers to test consistency of bias measurements across wavelengths.
  • Scale-dependent bias or different power-law slopes could be tested once redshift uncertainty is reduced.

Load-bearing premise

The two T-RECS redshift-distribution priors adequately bracket the true redshift distribution of the sources.

What would settle it

An independent measurement of the redshift distribution of the detected radio sources that lies outside the range spanned by the AGN and TOTAL T-RECS priors.

Figures

Figures reproduced from arXiv: 2606.22432 by Aishrila Mazumder, Cyril Tasse, Joseph J. Mohr, Keith Grainge, Laura Wolz, Mario G. Santos, Oleg Smirnov, Sarvesh Mangla, Sourabh Paul, Steven Cunnington, Suman Chatterjee.

Figure 1
Figure 1. Figure 1: Survey footprint, depth variations, and clustering mask for MeerKLASS UHF DR1. Top: pixelised coverage map showing the number of OTF interferometric scan blocks contributing to each sky position (𝑁blocks = 1–8). The deepest region occurs where rising and setting passes overlap, while coverage (and hence sensitivity) decreases towards the survey edges that are sampled by fewer blocks. Bottom: local rms nois… view at source ↗
Figure 2
Figure 2. Figure 2: Uniformity diagnostics for the fiducial clustering selection. Left: ratio of the normalised data and random surface densities, 𝑅 ≡ 𝑛data/𝑛rand, in declination using 30 equal-width bins (normalised such that the mean ratio is unity). Right: the same ratio in right ascension using 30 equal-area bins, where the bin boundaries are defined by RA-quantiles of the random catalogue so that each bin contains (appro… view at source ↗
Figure 3
Figure 3. Figure 3: Fiducial angular clustering measurement and covariance. Left: measured angular correlation function 𝑤( 𝜃 ) in 20 logarithmically spaced bins spanning 0.02◦ ≤ 𝜃 ≤ 10◦ ; error bars show 1𝜎 uncertainties from the spatial jackknife covariance with 𝑁JK = 30 patches. Right: the corresponding jackknife correlation matrix 𝜌𝑖 𝑗 = 𝐶𝑖 𝑗/ √︁ 𝐶𝑖𝑖𝐶𝑗 𝑗, illustrating the bin-to-bin correlations induced by large-scale stru… view at source ↗
Figure 4
Figure 4. Figure 4: Stability of the measured 𝑤( 𝜃 ) to alternative sample selections and masks. Curves show 𝑤( 𝜃 ) for the fiducial case and for a selection of depth/flux/morphology variants. Left: 𝑤( 𝜃 ) over the full angular range. Right: a zoom of the small-angle regime highlighting morphology-driven effects. The compact-only samples show consistent clustering amplitudes on intermediate and large scales, indicating that t… view at source ↗
Figure 5
Figure 5. Figure 5: Power-law characterisation of the clustering signal. Left: fiducial 𝑤( 𝜃 ) measurement with jackknife errors together with best-fitting fixed-slope power￾law models, 𝑤( 𝜃 ) = 𝐴( 𝜃/1 ◦ ) 1−𝛾 , with 𝛾 = 1.8, fitted over three angular windows that progressively exclude the smallest-separation bins: [0.112, 1.36] ◦ (fiducial), [0.153, 1.36] ◦ , and [0.209, 1.36] ◦ . The corresponding amplitudes are 𝐴(1 ◦ ) = (… view at source ↗
Figure 6
Figure 6. Figure 6: Bias inference from ΛCDM template modelling. Left: redshift-distribution priors 𝑁 (𝑧) for the 𝑆816 ≥ 2 mJy sample, taken from the T-RECS semi-empirical simulations for an AGN-dominated selection and for the full population (TOTAL). Each 𝑁 (𝑧) is normalised to unit area; the mean redshift ⟨𝑧⟩ of each prior is indicated in the legend. Right: fiducial 𝑤( 𝜃 ) measurement with jackknife errors compared to the b… view at source ↗
read the original abstract

We present the first measurement of the angular two-point correlation function \(w(\theta)\) of radio sources from the MeerKAT Large Area Synoptic Survey (MeerKLASS) UHF on-the-fly (OTF) continuum Data Release~1. DR1 provides interferometric Stokes-\(I\) imaging at a reference frequency of 816\,MHz over \(\sim 800~\mathrm{deg}^2\) within the DESI footprint. We detect a positive clustering signal over \(0.02^\circ \lesssim \theta \lesssim 10^\circ\). The measurement is stable to reasonable variations of the depth mask and flux threshold on intermediate and large scales. Modelling the intermediate-scale signal (\(0.112^\circ\le\theta\le 1.36^\circ\)) with a fixed-slope power law (\(\gamma=1.8\)) yields \(A(1^\circ)=(1.434\pm0.475)\times10^{-3}\), corresponding to \(\log_{10}A=-2.843^{+0.124}_{-0.175}\). We infer an effective large-scale bias by fitting \(\Lambda\)CDM projected-matter templates \(w_{\rm DM}(\theta)\) computed with \textsc{CAMB} and Limber projection, including an integral-constraint correction evaluated from random--random weights. Using two bracketing T-RECS redshift-distribution priors, we obtain \(b_{\rm eff}=1.998\pm0.350\) (AGN prior) and \(b_{\rm eff}=1.530\pm0.265\) (TOTAL prior), demonstrating that the dominant modelling uncertainty arises from \(N(z)\). As a derived summary we Limber-invert the power-law amplitude to obtain \(r_0=6.18\pm1.13\) and \(5.59\pm1.02~h^{-1}\mathrm{Mpc}\) for the AGN and TOTAL priors, respectively. These results establish MeerKLASS UHF DR1 as a new wide-area, intermediate-frequency dataset for radio-continuum clustering. As MeerKLASS expands and overlapping optical/IR spectroscopy provides improved redshift calibration, future releases will enable population-split clustering and bias evolution measurements with substantially reduced modelling uncertainty.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 0 minor

Summary. The manuscript presents the first measurement of the angular two-point correlation function w(θ) of radio sources from the MeerKLASS UHF on-the-fly continuum Data Release 1 at 816 MHz over ~800 deg² within the DESI footprint. It reports a positive clustering signal stable to mask and flux variations over 0.02° ≲ θ ≲ 10°, fits a fixed-slope (γ=1.8) power-law model to the intermediate scales (0.112°≤θ≤1.36°) yielding A(1°)=(1.434±0.475)×10^{-3}, and infers effective bias b_eff using ΛCDM templates via CAMB and Limber projection with two bracketing T-RECS N(z) priors, obtaining b_eff=1.998±0.350 (AGN) and 1.530±0.265 (TOTAL), with N(z) identified as the dominant modelling uncertainty; derived r_0 values are also reported.

Significance. If the measurement and modelling hold, this establishes MeerKLASS UHF DR1 as a new wide-area intermediate-frequency radio-continuum dataset for large-scale structure studies. The direct use of survey data with standard external tools (CAMB, Limber), stability tests, and explicit demonstration that N(z) drives the uncertainty are strengths. The results provide a baseline for future population-split analyses and bias evolution as the survey expands and spectroscopic overlap improves redshift calibration.

major comments (1)
  1. [Abstract (modelling paragraph)] Abstract (modelling paragraph): The central claim that the AGN and TOTAL T-RECS redshift-distribution priors 'adequately bracket' the true N(z) of the 816 MHz sources (and thus that the ~30% spread in b_eff represents the dominant uncertainty) is load-bearing for the interpretation of the bias results. The manuscript provides no explicit tests, literature comparisons, or selection-effect arguments demonstrating that no other population mix at this frequency produces an N(z) outside the envelope; if this assumption does not hold, the quoted b_eff and r_0 values cannot be trusted at the reported precision even if w(θ) itself is robust.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their positive assessment of the work and recommendation for minor revision. We address the single major comment below.

read point-by-point responses

  1. Referee: [Abstract (modelling paragraph)] Abstract (modelling paragraph): The central claim that the AGN and TOTAL T-RECS redshift-distribution priors 'adequately bracket' the true N(z) of the 816 MHz sources (and thus that the ~30% spread in b_eff represents the dominant uncertainty) is load-bearing for the interpretation of the bias results. The manuscript provides no explicit tests, literature comparisons, or selection-effect arguments demonstrating that no other population mix at this frequency produces an N(z) outside the envelope; if this assumption does not hold, the quoted b_eff and r_0 values cannot be trusted at the reported precision even if w(θ) itself is robust.

    Authors: We agree that the manuscript does not include explicit additional tests, literature comparisons, or selection-effect arguments beyond the adoption of the T-RECS model to demonstrate that the AGN and TOTAL priors encompass every conceivable population mix at 816 MHz. T-RECS is a semi-empirical simulation calibrated on multi-frequency data, with the AGN and TOTAL cases representing the primary source populations (AGN-dominated versus total including star-forming galaxies). The difference between these priors is used to quantify sensitivity to N(z). To address the concern, we will revise the abstract to state that these are bracketing priors within the T-RECS framework and that N(z) constitutes the dominant modelling uncertainty under this choice, without asserting that they cover all possible mixes. A corresponding clarification will be added to the main text if appropriate. This is a minor wording revision. revision: yes

Circularity Check

0 steps flagged

Direct data measurement and external-template bias inference show no circularity

full rationale

The paper measures w(θ) directly from MeerKLASS DR1 imaging data, fits a fixed-slope power law to extract amplitude A on intermediate scales, and infers b_eff by scaling CAMB/Limber dark-matter templates against two external T-RECS N(z) priors. The r0 values are obtained by standard Limber inversion of the fitted A. None of these steps reduce by construction to the paper's own fitted quantities, self-citations, or ansatzes; the N(z) spread is treated as acknowledged modelling uncertainty rather than a definitional loop. The derivation therefore remains self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

2 free parameters · 3 axioms · 0 invented entities

The measurement relies on standard cosmological assumptions and external simulation-based priors; no new entities are introduced. The fixed slope and amplitude are fitted parameters, while N(z) priors are treated as bracketing assumptions.

free parameters (2)
  • power-law slope gamma = 1.8
    Fixed to 1.8 for the intermediate-scale fit
  • correlation amplitude A = 1.434e-3
    Fitted to measured w(theta) on intermediate scales
axioms (3)
  • domain assumption Limber approximation for angular projection
    Used to obtain w_DM(theta) from 3D matter power spectrum
  • domain assumption Lambda CDM cosmology for matter templates
    Templates computed with CAMB
  • domain assumption T-RECS simulation redshift distributions bracket the true N(z)
    Used as bracketing priors for bias inference

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discussion (0)

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