J/A+A/592/A48   Annotations to the second Planck cluster catalog  (Khatri, 2016)

An alternative validation strategy for the Planck cluster catalog and y-distortion maps. Khatri R. <Astron. Astrophys. 592, A48 (2016)> =2016A&A...592A..48K 2016A&A...592A..48K (SIMBAD/NED BibCode)
ADC_Keywords: Clusters, galaxy ; Molecular clouds Keywords: cosmic background radiation - cosmology: observations - ISM: clouds - radio lines: ISM - methods: data analysis - galaxies: clusters : intracluster medium Abstract: We present an all sky map of the y-type distortion calculated from the full mission Planck HFI (High Frequency Instrument) data using the recently proposed approach to component separation based on parametric model fitting and model selection. This simple model selection approach allows us to distinguish between carbon monoxide (CO) line emission and y-type distortion, something that is not possible using the internal linear combination based methods. We create a mask to cover the regions of significant CO emission relying on the information in the χ2 map obtained when fitting for the y-distortion and CO emission to the lowest four HFI channels. We revisit the second Planck cluster catalog and try to quantify the quality of the cluster candidates in an approach that is similar in spirit to Aghanim et al. (2015A&A...580A.138A 2015A&A...580A.138A). We find that at least 93% of the clusters in the cosmology sample are free of CO contamination. We also find that 59% of unconfirmed candidates may have significant contamination from molecular clouds. We agree with Planck Collaboration et al. (2016, A&A, in press., arXiv:1502.01598) for the worst offenders. We suggest an alternative validation strategy of measuring and subtracting the CO emission from the Planck cluster candidates using radio telescopes thus improving the reliability of the catalog. Our CO mask and annotations to the Planck cluster catalog identifying cluster candidates with possible CO contamination are made publicly available. Description: We have added additional columns to the second Planck cluster catalog which quantify the quality of clusters and try to discriminate the molecular cloud contamination in the catalog. We provide the χ2 for the fits of a parametric model with either Sunyaev-Zeldovich spectrum or CO-line emission spectrum to the Planck data within 5-arcmin at the position of each cluster. The difference in the χ2 value can be used to determine whether a candidate is likely to be a cluster or a molecular cloud and is indicative of the quality of the cluster candidate. File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file catalog.dat 156 1653 Planck cluster catalog with additional columns (planckclustersR2.0_x3.8.dat) -------------------------------------------------------------------------------- See also: VIII/88 : Planck Early Release Compact Source Catalogue (Planck, 2011) VIII/91 : Planck Catalog of Compact Sources Release 1 (Planck, 2013) J/A+A/536/A8 : Planck early results. VIII. ESZ sample. (Planck+, 2011) https://wiki.cosmos.esa.int/planckpla2015/index.php/ Catalogues#Union_catalogue : (Planck collaboration second SZ union catalogue) Byte-by-byte Description of file: catalog.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 2- 5 I4 --- Seq [1/1653] Serial number in the present catalogue 7- 10 I4 --- Planck [1/1653] Serial number in original Planck catalogue (1) 13- 16 A4 --- --- [PSZ2] 18- 30 A13 --- PSZ2 Planck cluster name, GLLL.ll+BB.bb (1) 32- 40 F9.5 deg GLON Galactic longitude (1) 42- 50 F9.5 deg GLAT Galactic latitude (1) 52- 60 F9.5 --- S/N Signal to noise ratio of the detection (1) 62- 70 F9.5 --- z Redshift of cluster (1) 72- 83 E12.5 10-3arcmin+2 Y Total integrated Comptonization parameter, mean marginal Y5R500 as determined by reference pipeline (1) 85- 96 E12.5 10-3arcmin+2 e_Y rms uncertainty on Y (1) 99-101 I3 --- Pvalid [-1/30] Planck validation flag (1) (2) 103-111 F9.3 --- COX2 Chi2 for CO spectrum fit 113-121 F9.3 --- SZX2 Chi2 for SZ spectrum fit 122-131 F10.3 --- COX2-SZX2 Difference between CO and SZ Chi2 133-136 A4 --- LILvalid Validation flag from LIL model selection algorithm (3) 139 A1 --- FCosmo [F/T] Planck cosmology flag (1) (4) 145-149 F5.3 --- QN [0/1] Planck neural network quality flag (1) (5) 153-156 A4 --- Qual Good/Bad classification based on QN -------------------------------------------------------------------------------- Note (1): This field is copied from the original Planck catalogue without modification. See https://wiki.cosmos.esa.int/planckpla2015/index.php/Catalogues#Union_catalogue for details. Note (2): Summary of the external validation, encoding the most robust external identification as follows: 10 = ENO follow-up 11 = RTT follow-up 12 = PanSTARRs 13 = RedMAPPer non-blind 14 = SDSS high-z 15 = AMI 16 = WISE 20 = legacy identification from the PSZ1 21 = MCXC 22 = SPT 23 = ACT 24 = RedMAPPer 25 = legacy identification from PSZ1 with externally updated redshift 30 = NED -1 = no known external counterpart Note (3): Validation flag from LIL model selection algorithm as follows: CLG = cluster IND = indeterminable MOC = molecular cloud pCLG = cluster with lower significance of classification than CLG pMOC = molecular cloud with lower significance of classification than MOC Note (4): Indicates whether detection is in the cosmology sample (T for True). Note (5): Neural network quality flag is 1-Qbad, following the definitions in Aghanim et al. (2015A&A...580A.138A 2015A&A...580A.138A). -------------------------------------------------------------------------------- Acknowledgements: Rishi Khatri, khatri(at)theory.tifr.res.in References: https://wiki.cosmos.esa.int/planckpla2015/index.php/Catalogues#Union_catalogue
(End) Rishi Khatri [TIFR Mumbai, India], Patricia Vannier [CDS] 31-May-2016
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