We update the all-sky Planck catalogue of 1227 clusters and cluster candidates (PSZ1) published in March 2013, derived from Sunyaev-Zeldovich (SZ) effect detections using the first 15.5 months of Planck satellite observations. Addendum. We deliver an
updated version of the PSZ1 catalogue, reporting the further confirmation of 86 Planck-discovered clusters. In total, the PSZ1 now contains 947 confirmed clusters, of which 214 were confirmed as newly discovered clusters through follow-up observations undertaken by the Planck Collaboration. The updated PSZ1 contains redshifts for 913 systems, of which 736 (~80.6%) are spectroscopic, and associated mass estimates derived from the Y_z mass proxy. We also provide a new SZ quality flag, derived from a novel artificial neural network classification of the SZ signal, for the remaining 280 candidates. Based on this assessment, the purity of the updated PSZ1 catalogue is estimated to be 94%. In this release, we provide the full updated catalogue and an additional readme file with further information on the Planck SZ detections.
We examine three approaches to the problem of source classification in catalogues. Our goal is to determine the confidence with which the elements in these catalogues can be distinguished in populations on the basis of their spectral energy distribut
ion (SED). Our analysis is based on the projection of the measurements onto a comprehensive SED model of the main signals in the considered range of frequencies. We first first consider likelihood analysis, which half way between supervised and unsupervised methods. Next, we investigate an unsupervised clustering technique. Finally, we consider a supervised classifier based on Artificial Neural Networks. We illustrate the approach and results using catalogues from various surveys. i.e., X-Rays (MCXC), optical (SDSS) and millimetric (Planck Sunyaev-Zeldovich (SZ)). We show that the results from the statistical classifications of the three methods are in very good agreement with each others, although the supervised neural network-based classification shows better performances allowing the best separation into populations of reliable and unreliable sources in catalogues. The latest method was applied to the SZ sources detected by the Planck satellite. It led to a classification assessing and thereby agreeing with the reliability assessment published in the Planck SZ catalogue. Our method could easily be applied to catalogues from future large survey such as SRG/eROSITA and Euclid.
We describe the all-sky Planck catalogue of clusters and cluster candidates derived from Sunyaev--Zeldovich (SZ) effect detections using the first 15.5 months of Planck satellite observations. The catalogue contains 1227 entries, making it over six t
imes the size of the Planck Early SZ (ESZ) sample and the largest SZ-selected catalogue to date. It contains 861 confirmed clusters, of which 178 have been confirmed as clusters, mostly through follow-up observations, and a further 683 are previously-known clusters. The remaining 366 have the status of cluster candidates, and we divide them into three classes according to the quality of evidence that they are likely to be true clusters. The Planck SZ catalogue is the deepest all-sky cluster catalogue, with redshifts up to about one, and spans the broadest cluster mass range from (0.1 to 1.6) 10^{15}Msun. Confirmation of cluster candidates through comparison with existing surveys or cluster catalogues is extensively described, as is the statistical characterization of the catalogue in terms of completeness and statistical reliability. The outputs of the validation process are provided as additional information. This gives, in particular, an ensemble of 813 cluster redshifts, and for all these Planck clusters we also include a mass estimated from a newly-proposed SZ-mass proxy. A refined measure of the SZ Compton parameter for the clusters with X-ray counter-parts is provided, as is an X-ray flux for all the Planck clusters not previously detected in X-ray surveys.
Clusters are potentially powerful tools for cosmology provided their observed properties such as the Sunyaev-Zeldovich (SZ) or X-ray signals can be translated into physical quantities like mass and temperature. Scaling relations are the appropriate m
ean to perform this translation. It is therefore, important to understand their evolution and their modifications with respect to the physics and to the underlying cosmology. In this spirit, we investigate the effect of dark energy on the X-ray and SZ scaling relations. The study is based on the first hydro-simulations of cluster formation for diferent models of dark energy. We present results for four dark energy models which differ from each other by their equations of state parameter, $w$. Namely, we use a cosmological constant model $w=-1$ (as a reference), a perfect fluid with constant equation of state parameter $w=-0.8$ and one with $w = -1.2$ and a scalar field model (or quintessence) with varying $w$. We generate N-body/hydrodynamic simulations that include radiative cooling with the public version of the Hydra code, modified to consider an arbitrary dark energy component. We produce cluster catalogues for the four models and derive the associated X-ray and SZ scaling relations. We find that dark energy has little effect on scaling laws making it safe to use the $Lambda$CDM scalings for conversion of observed quantities into temperature and masses.
