J/A+A/653/A106 List of candidate clusters (Hurier+, 2021)
MILCANN: a tSZ map for galaxy cluster detection assessed using a neural network.
Hurier G., Aghanim N., Douspis M.
<Astron. Astrophys. 653, A106 (2021)>
=2021A&A...653A.106H 2021A&A...653A.106H (SIMBAD/NED BibCode)
ADC_Keywords: Clusters, galaxy
Keywords: large-scale structure of Universe - galaxies: clusters: general -
methods: data analysis
Abstract:
We present the first combination of a thermal Sunyaev-Zel'dovich
(tSZ) map with a multi-frequency quality assessment of the sky pixels
based on artificial neural networks (ANNs) with the aim being to
detect tSZ sources from submillimeter observations of the sky by
Planck.We present the construction of the resulting filtered and
cleaned tSZ map, MILCANN.We show that this combination leads to a
significant reduction of noise fluctuations and foreground residuals
compared to standard reconstructions of tSZ maps. From the MILCANN
map, we constructed a tSZ source catalog of about 4000 sources with a
purity of 90%. Finally, we compare this catalog with ancillary
catalogs and show that the galaxy-cluster candidates in our catalog
are essentially low-mass (down to M500=1014M+☉_) high-redshift
(up to z≤1) galaxy cluster candidates.
Description:
The matched-filtering and the ANN weighting process
involved in the construction of the MILCANN tSZ map means that its use
is specifically tailored to tSZ-cluster detection. In particular, the
MILCANN tSZ map presents a significantly lower level of noise and
foreground residuals than standard tSZ maps. However, the ANN
weighting procedure produces a distortion of the tSZ signal both in
shape and flux. Consequently, the MILCANN map can only be used for
cluster-detection purposes and is not suited for other analyses such
as tSZ scaling relations, profiles, or angular power spectra.
From the MILCANN tSZ map, we constructed the HAD source catalog
containing 3969 cluster candidates with an estimated purity of 90%.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
hadv1.dat 35 3969 HAD catalog (list of candidate clusters)
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Byte-by-byte Description of file: hadv1.dat
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Bytes Format Units Label Explanations
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1- 8 A8 --- HAD Designation, HAD-NNNN
10- 17 F8.4 deg GLON Galactic longitude
19- 26 F8.4 deg GLAT Galactic latitude
28- 35 F8.6 --- QN [0/1] Quality flag, QN (1)
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Note (1): ANN-based weight quality flag, QN, as
QN = QGOOD(1-QBAD)
where QGOOD and QBAD are the ANN classification output values for the
Good and Bad classes. By construction, this ANN-weight ranges from 0 to 1,
with values close to 1 for pixels that present a high-quality tSZ signal.
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Acknowledgements:
Guillaume Hurier, hurier.guillaume(at)gmail.com
(End) Guillaume Hurier [CEPCA], Patricia Vannier [CDS] 10-Sep-2021