Context. Cosmological probes based on galaxy clusters rely on cluster number counts and large-scale structure information. X-ray cluster surveys are well suited for this purpose because they are far less affected by projection effects than optical surveys, and cluster properties can be predicted with good accuracy. Aims. The XMM Cluster Archive Super Survey, X-CLASS, is a serendipitous search of X-ray-detected galaxy clusters in 4176 XMM-Newton archival observations until August 2015. All observations are clipped to exposure times of 10 and 20 ks to obtain uniformity, and they span ∼269 deg 2 across the high-Galactic latitude sky (|b| > 20 o ). The main goal of the survey is the compilation of a wellselected cluster sample suitable for cosmological analyses. Methods. We describe the detection algorithm, the visual inspection, the verification process, and the redshift validation of the cluster sample, as well as the cluster selection function computed by simulations. We also present the various metadata that are released with the catalogue, along with two different count-rate measurements, an automatic one provided by the pipeline, and a more detailed and accurate interactive measurement. Furthermore, we provide the redshifts of 124 clusters obtained with a dedicated multi-object spectroscopic follow-up programme. Results. With this publication, we release the new X-CLASS catalogue of 1646 well-selected X-ray-detected clusters over a wide sky area, along with their selection function. The sample spans a wide redshift range, from the local Universe up to z ∼ 1.5, with 982 spectroscopically confirmed clusters, and over 70 clusters above z = 0.8. The redshift distribution peaks at z∼ 0.1, while if we remove the pointed observations it peaks at z ∼ 0.3. Because of its homogeneous selection and thorough verification, the cluster sample can be used for cosmological analyses, but also as a test-bed for the upcoming eROSITA observations and other current and future large-area cluster surveys. It is the first time that such a catalogue is made available to the community via an interactive database which gives access to a wealth of supplementary information, images, and data.

Galaxy clusters appear as extended sources in XMM–Newton images, but not all extended sources are clusters. So, their proper classification requires visual inspection with optical images, which is a slow process with biases that are almost impossible to model. We tackle this problem with a novel approach, using convolutional neural networks (CNNs), a state-of-the-art image classification tool, for automatic classification of galaxy cluster candidates. We train the networks on combined XMM–Newton X-ray observations with their optical counterparts from the all-sky Digitized Sky Survey. Our data set originates from the XMM CLuster Archive Super Survey (X-CLASS) survey sample of galaxy cluster candidates, selected by a specially developed pipeline, the XAmin, tailored for extended source detection and characterization. Our data set contains 1707 galaxy cluster candidates classified by experts. Additionally, we create an official Zooniverse citizen science project, The Hunt for Galaxy Clusters, to probe whether citizen volunteers could help in a challenging task of galaxy cluster visual confirmation. The project contained 1600 galaxy cluster candidates in total of which 404 overlap with the expert’s sample. The networks were trained on expert and Zooniverse data separately. The CNN test sample contains 85 spectroscopically confirmed clusters and 85 non-clusters that appear in both data sets. Our custom network achieved the best performance in the binary classification of clusters and non-clusters, acquiring accuracy of 90 per cent, averaged after 10 runs. The results of using CNNs on combined X-ray and optical data for galaxy cluster candidate classification are encouraging, and there is a lot of potential for future usage and improvements.

Context. Nowadays, we know that the origin of the cosmic X-ray background (CXB) is the integrated emission of nearby active galactic nuclei. Therefore, in order to obtain a precise estimate of the contribution of different source classes to the CXB, it is crucial to achieve full characterization of the hard-X ray sky. Aims. We present a multifrequency analysis of all sources listed in the third release of the Palermo Swift-BAT hard X-ray catalog (3PBC) with the goal of (i) identifying and classifying the largest number of sources adopting multifrequency criteria, with particular emphasis on extragalactic populations and (ii) extracting sources belonging to the class of Seyfert galaxies to present here the release of the second version of the Turin-SyCAT. Methods. We outline a classification scheme based on radio, infrared (IR), and optical criteria that allows us to distinguish between unidentified and unclassified hard X-ray sources, as well as to classify those sources belonging to the Galactic and the extragalactic populations. Results. Our revised version of the 3PBC lists 1176 classified, 820 extragalactic, and 356 Galactic sources, as well as 199 unclassified and 218 unidentified sources. According to our analysis, the hard X-ray sky is mainly populated by Seyfert galaxies and blazars. For the blazar population, we report trends between the hard X-ray and the gamma-ray emissions based on the fact that a large fraction of them also have a counterpart detected by the Fermi satellite. These trends are all in agreement with the expectations of inverse Compton models which are widely adopted to explain the blazar broadband emission. For the Seyfert galaxies, we present the second version of the Turin-SyCAT, including a total of 633 Seyfert galaxies, with 282 new sources corresponding to an increase of ∼80 % with respect to the previous release. Comparing the hard X-ray and the infrared emissions of Seyfert galaxies, we confirm that there is no clear difference between the flux distribution of the infrared-to-hard X-ray flux ratio of Seyfert galaxies Type 1 and Type 2. However, there is a significant trend between the mid-IR flux and hard X-ray flux, confirming previous statistical results in the literature. Conclusions. We provide two catalog tables. The first is the revised version of the 3PBC catalog based on our multifrequency analyses. The second catalog table is a release of the second version of the Turin-SyCAT catalog. Finally, we highlight that extensive soft X-ray data are already available in the form of the SWIFT archive which can be used to search for potential counterparts of unidentified hard X-ray sources. All these datasets will be reduced and analyzed in a forthcoming analysis to determine the precise position of lowenergy counterparts in the 0.5 -10 keV energy range for 3PBC sources that can be targets of future optical spectroscopic campaigns; this is necessary to obtain their precise classification.