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arxiv: 2605.20027 · v1 · pith:G46FMG3Tnew · submitted 2026-05-19 · 🌌 astro-ph.CO · astro-ph.GA

ComPACT: Mass-Redshift Properties of the galaxy cluster catalogue

S. Voskresenskaia , N. Lyskova , I. Zaznobin , A. Meshcheryakov This is my paper

Pith reviewed 2026-05-20 03:57 UTC · model grok-4.3

classification 🌌 astro-ph.CO astro-ph.GA
keywords galaxy clustersSunyaev-Zeldovich effectmachine learningACT surveyPlanck surveycluster cataloguehigh-redshift clustersSZ scaling relations
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The pith

A convolutional neural network on ACT and Planck maps identifies five new massive galaxy clusters at z greater than 0.7.

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

The paper constructs the ComPACT catalogue of 2962 SZ-selected galaxy cluster candidates by applying a convolutional neural network to combined ACT and Planck microwave maps. Roughly 60 percent of the candidates are confirmed as clusters through redshift estimates from literature and photometric data from DESI Legacy Imaging Surveys, with masses derived for 56 percent of the sample using SZ scaling relations from the Compton-y maps. This process yields 158 new mass estimates and 116 new redshifts spanning 0.007 to 1.7. The central result is the identification of five previously unreported clusters with masses above 6 times 10 to the 14 solar masses at redshifts over 0.7, increasing the known population of such systems by about 10 percent. This expansion matters because it improves the census of high-mass structures at earlier cosmic times.

Core claim

The ComPACT catalogue, built from a convolutional neural network applied to publicly available combined ACT+Planck maps, contains 2962 SZ-selected galaxy cluster candidates of which approximately 60 percent are confirmed as clusters. Redshifts range from 0.007 to 1.7 with 116 new measurements, and masses for 56 percent of the sample span 0.25 to 13.1 times 10 to the 14 solar masses with 158 new determinations. The catalogue identifies five previously unreported massive clusters with M_500c greater than 6 times 10 to the 14 solar masses at z greater than 0.7, increasing the known population of such systems by approximately 10 percent.

What carries the argument

Convolutional neural network that detects Sunyaev-Zeldovich signals in combined ACT and Planck Compton-y maps to generate cluster candidates, followed by redshift confirmation and mass estimation via SZ scaling relations.

Load-bearing premise

The SZ scaling relations used to estimate masses from the Compton-y maps are assumed to hold without bias for these newly detected high-redshift clusters.

What would settle it

Independent X-ray or weak-lensing mass measurements showing that any of the five reported clusters have M_500c below 6 times 10 to the 14 solar masses at their stated redshifts would falsify the claimed increase in the known population.

Figures

Figures reproduced from arXiv: 2605.20027 by A. Meshcheryakov, I. Zaznobin, N. Lyskova, S. Voskresenskaia.

Figure 1
Figure 1. Figure 1: Comparison of cluster redshift estimates obtained with the [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Estimated completeness of the DL based cluster catalogue (without [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Comparison of the ComPACT cluster sample in the mass–redshift plane. The distribution of ComPACT clusters is shown [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Most massive clusters that are detected by [PITH_FULL_IMAGE:figures/full_fig_p010_4.png] view at source ↗
read the original abstract

Machine-learning methods are increasingly applied to astronomical surveys, providing powerful tools for detecting and studying galaxy clusters. We investigate the mass-redshift properties and completeness of the ComPACT galaxy cluster catalogue, constructed using a convolutional neural network applied to publicly available combined ACT+Planck maps. The ComPACT catalogue contains 2,962 SZ-selected galaxy cluster candidates. We confirm clusters by estimating redshifts using literature information and photometric techniques based on DESI Legacy Imaging Surveys data. Cluster masses are derived from ACT+Planck and Planck Compton-y maps via SZ scaling relations. The completeness is assessed using simulated cluster injections into real microwave maps. We confirm approximately $\sim$60 % of the ComPACT candidates as galaxy clusters. The redshifts span the range $0.007 < z < 1.7$, including approximately 116 new measurements. Masses are obtained for 56 % of the sample, covering the range $(0.25 - 13.1) \times 10^{14} ~M_\odot$ and including 158 new mass determinations. We identify five previously unreported massive clusters ($M_{500c} > 6 \times 10^{14}~M_\odot$) at $z > 0.7$, increasing the known population of such systems by approximately 10 %. The ComPACT catalogue expands the SZ-selected Planck-like cluster population, especially at high redshift and high mass, demonstrating the effectiveness of deep-learning approaches for cluster detection in microwave data.

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 / 1 minor

Summary. The manuscript presents the ComPACT galaxy cluster catalogue of 2,962 SZ-selected candidates identified via a convolutional neural network applied to combined ACT+Planck maps. Approximately 60% of candidates are confirmed as clusters using literature redshifts and photometric redshifts from DESI Legacy Imaging Surveys data, spanning 0.007 < z < 1.7 and including 116 new redshift measurements. Masses are derived for 56% of the sample via SZ scaling relations applied to ACT+Planck and Planck Compton-y maps, covering (0.25–13.1) × 10^{14} M_⊙ with 158 new mass estimates. Completeness is assessed through simulated cluster injections into real microwave maps. The central result is the identification of five previously unreported clusters with M_{500c} > 6 × 10^{14} M_⊙ at z > 0.7, claimed to increase the known population of such systems by ~10%.

Significance. If the mass estimates for the five new high-redshift systems prove robust, the work would provide a useful expansion of the high-mass, high-redshift SZ-selected cluster sample, which is valuable for cosmological constraints on structure growth and for testing the evolution of the SZ-mass relation. The use of machine learning on public survey data and the simulation-based completeness assessment are constructive contributions. However, the overall significance is limited by the absence of explicit validation for the scaling relations at z > 0.7.

major comments (1)
  1. Abstract: The headline claim of five new clusters satisfying M_{500c} > 6 × 10^{14} M_⊙ at z > 0.7 (increasing the known population by ~10%) rests on masses obtained from SZ scaling relations applied to ACT+Planck and Planck y-maps. The manuscript provides no redshift-dependent bias tests, no comparison to weak-lensing or X-ray masses for these objects, and no quantification of how 20–30% additional scatter (plausible from higher merger rates or beam dilution at z > 0.7) would affect the count of qualifying systems. This directly undermines the reported 10% increase.
minor comments (1)
  1. Abstract: The phrasing 'approximately ~60 %' is redundant and should be simplified to 'approximately 60 %' or '~60 %'.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their careful and constructive review of our manuscript. We address the major comment below and have revised the manuscript to strengthen the presentation of our results while acknowledging limitations in the available validation data.

read point-by-point responses

  1. Referee: Abstract: The headline claim of five new clusters satisfying M_{500c} > 6 × 10^{14} M_⊙ at z > 0.7 (increasing the known population by ~10%) rests on masses obtained from SZ scaling relations applied to ACT+Planck and Planck y-maps. The manuscript provides no redshift-dependent bias tests, no comparison to weak-lensing or X-ray masses for these objects, and no quantification of how 20–30% additional scatter (plausible from higher merger rates or beam dilution at z > 0.7) would affect the count of qualifying systems. This directly undermines the reported 10% increase.

    Authors: We acknowledge that the manuscript does not present new redshift-dependent bias tests or direct comparisons to weak-lensing or X-ray masses for the five newly identified high-redshift clusters, as independent mass measurements for these specific objects are not available in the literature. The SZ scaling relations applied are the standard calibrations used for ACT and Planck data (as detailed in Section 3), which have been validated on samples extending to z ≈ 1. We agree that additional scatter from merger activity or beam effects at z > 0.7 is a plausible concern. In the revised manuscript we have added a dedicated paragraph in the discussion section that quantifies the impact of a 25% increase in mass uncertainty on the sample; under this test, four of the five clusters remain above the M_{500c} > 6 × 10^{14} M_⊙ threshold. We have also revised the abstract to include a brief caveat noting that the reported increase relies on SZ-derived masses and is subject to the systematic uncertainties discussed in the text. These changes address the referee’s concern without altering the core result. revision: partial

Circularity Check

0 steps flagged

No significant circularity in observational catalogue construction

full rationale

The paper constructs a cluster catalogue by applying a convolutional neural network to public ACT+Planck microwave maps, confirms candidates via external literature redshifts and DESI Legacy photometric redshifts, and derives masses using established SZ scaling relations from the literature. Completeness is evaluated through simulated injections into real maps. None of these steps reduce by definition or by self-citation to the paper's own fitted outputs or inputs; the reported 10% increase in high-mass high-redshift systems is a direct count against external catalogues rather than a derived prediction. The derivation chain remains self-contained against external benchmarks with no load-bearing internal loops.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claims rest on the accuracy of standard SZ scaling relations for mass estimation and on the fidelity of simulated cluster injections for completeness assessment; no free parameters or new entities are introduced in the abstract.

axioms (1)
  • domain assumption SZ scaling relations convert observed Compton-y signal to cluster mass without significant bias for the detected systems
    Invoked when deriving masses from ACT+Planck and Planck Compton-y maps as stated in the abstract.

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