J/A+A/710/A219 Galaxy clusters in the LoTSS-DR3 (Stuardi+, 2026)
Galaxy clusters in the LoTSS-DR3:
Catalogues and detection pipeline for diffuse radio emission.
Stuardi C., Di Gennaro G., Botteon A., Braga F., Gheller C., Vazza F.,
Balboni M., Biava N., Bonafede A., Brueggen M., Brunetti G., Cassano R.,
Cianfaglione M., Cuciti V., De Gasperin F., Gastaldello F., Hardcastle M.J.,
Hoeft M., Rottgering H.J.A., Sanvitale N., Shimwell T.W., van Weeren R.J.
<Astron. Astrophys. 710, A219 (2026)>
=2026A&A...710A.219S 2026A&A...710A.219S (SIMBAD/NED BibCode)
ADC_Keywords: Clusters, galaxy ; Surveys ; Cross identifications
Keywords: techniques: image processing - catalogs -
galaxies: clusters : intracluster medium
Abstract:
The third data release (DR3) of the LOFAR Two-metre Sky Survey (LoTSS)
provides an unprecedented view of the northern sky at 144MHz,
comprising more than 13 million radio sources. While compact sources
can be efficiently identified with automated software packages, the
detection of diffuse radio emission associated with galaxy clusters
still requires dedicated processing and visual inspection. Given the
scale of current and forthcoming radio surveys, automated approaches
based on artificial intelligence are becoming essential to identify
the most interesting targets.
We aim to develop an automated pipeline to construct a catalogue of
galaxy clusters hosting diffuse radio emission from LoTSS-DR3 20arcsec
images. The pipeline is designed to provide both the probability that
a cluster hosts diffuse emission and an interpretable image of its
shape and morphology.
We employ Radio U-Net, a convolutional neural network optimised for
image segmentation (i.e. pixel-level identification) of diffuse radio
emission. To associate detected emission with individual clusters, we
combine the network output with positional, mass, and redshift
information from four X-ray- and Sunyaev-Zeldovich-selected cluster
catalogues, resulting in a merged sample of 3822 clusters covered by
the LoTSS-DR3.
We produce a pixel-level segmentation map of the full LoTSS-DR3 and a
quantitative indicator (R value) for the presence of diffuse radio
emission in each cluster. This enables the selection of sub-samples
with specific properties for targeted follow-up or statistical
studies. As a demonstration, we identify a sub-sample of 357 clusters
selected at the highest network accuracy (76%), and
we show some examples of newly detected systems. The detection
fraction of diffuse radio sources in the four catalogues increases
with the clusters' mass and redshift.
This work establishes a flexible and scalable framework for
deep-learning-based searches for diffuse radio emission in
new-generation wide-area radio surveys.
Description:
This table lists the 3822 galaxy clusters in the LoTSS-DR3 footprint
derived by cross-matching and merging four X-ray- and
Sunyaev-Zel'dovich-selected cluster catalogues: the second Planck
Sunyaev-Zel'dovich cluster catalogue, the fifth data release of the
Atacama Cosmology Telescope cluster catalogue, the second
Meta-Catalogue of X-ray detected Clusters of galaxies, and the first
SRG/eROSITA All-Sky Survey cluster catalogue. We selected only the
systems with mass M500≥1014M☉. The table is complemented with
information about the LoTSS-DR3 pointing(s) where each cluster is
observed and about the possible presence of diffuse radio emission
obtained with Radio U-Net.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
allrunet.dat 534 3822 Catalog
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See also:
J/A+A/707/A198 : LOFAR Two-metre Sky Survey (LoTSS) DR3 (Shimwell+, 2026)
J/A+A/594/A27 : Planck Sunyaev-Zeldovich sources (PSZ2) (Planck+, 2016)
J/A+A/690/A322 : The ACT-DR5 MCMF cluster catalog (Klein+, 2024)
J/A+A/688/A187 : MCXC Second release (MCXC-II) (Sadibekova+, 2024)
J/A+A/682/A34 : SRG/eROSITA all-sky survey catalogs (eRASS1) (Merloni+, 2024)
Byte-by-byte Description of file: allrunet.dat
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Bytes Format Units Label Explanations
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1- 23 A23 --- Name Name
25- 39 F15.11 deg RAdeg Right ascension (J2000)
41- 55 F15.11 deg DEdeg Declination (J2000)
57- 65 F9.7 --- z Redshift
67- 75 F9.7 --- e_z Error on z from the original catalogue.
When no error was provided,
we used 0.01(1+z)
77- 95 F19.16 10+14Msun M500 Mass M500
97-117 F21.18 10+14Msun e_M500 ?=- Lower error on M500
119-139 F21.18 10+14Msun E_M500 ?=- Upper error on M500
141-144 I4 kpc R500kpc R500 in kpc computed from M500 with
cosmology: H0=70km/(s.Mpc), Omega0=0.3
146-151 F6.3 arcmin R500amin R500 in arcmin converted with
cosmology: H0=70km/(s.Mpc), Omega0=0.3
153-219 A67 --- AName Alternative name derived from the
cross-match between the four original
catalogues
221-227 A7 --- HP-mosaic Name of the mosaic at the position of
the cluster in the DR3 mosaicking scheme
229-263 A35 --- PointID Names of all pointing used to create
the mosaic (names of mosaics following
the DR2 mosaicking scheme)
265-283 A19 deg DistPoint Distance of the cluster from the
pointing centre of each pointing
285-307 A23 uJy/beam noisePoint Noise at the cluster location in each
pointing before mosaicking
309-315 A7 --- Quality Quality class of each mosaic [0,1,2]
317-370 A54 --- Comment Comment on the mosaic(s) used
to compute R
372-382 A11 --- PointIDR Name of the mosaic used to compute R.
For quality class 2, this is not listed
384 I1 --- qualityR [0/2] Quality class of the mosaic used
to compute R
386-397 E12.6 --- R ?=- R value computed within 2.2R500
399-410 E12.6 --- e_R ?=- Error on the R value based on the
redshift of the cluster
412-534 A123 --- Overlap List of clusters that overlap within the
2.2R500 of the cluster
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Acknowledgements:
Chiara Stuardi, ccstuardi(at)gmail.com
License: CC-BY-4.0
(End) Patricia Vannier [CDS] 05-May-2026