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Context. The typically large distances, extinction, and crowding of Galactic supermassive star clusters (stellar clusters more massive than 10⁴M_⊙) have so far hampered the identification of their very low mass members, required to extend our understanding of star and planet formation, and early stellar evolution, to the extremely energetic star-forming environment typical of starbursts. This situation has now evolved thanks to theJames WebbSpace Telescope (JWST), and its unmatched resolution and sensitivity in the infrared. Aims. In this paper, the third of the series of the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS), we present JWST/NIRCam and JWST/MIRI observations of the supermassive star cluster Westerlund 1. These observations are specifically designed to unveil the cluster members down to the brown dwarf mass regime, and to allow us to select and study the protoplane-tary disks in the cluster and to study the mutual feedback between the cluster members and the surrounding environment. Methods. Westerlund 1 was observed as part of JWST GO-1905 for 23.6 hours. The data have been reduced using the JWST calibration pipeline, together with specific tools necessary to remove artifacts, such as the 1 /frandom noise in NIRCam images. Source identification and photometry were performed withDOLPHOT. Results. The MIRI images show a plethora of different features. Diffuse nebular emission is observed around the cluster, which is typically composed of myriads of droplet-like features pointing toward the cluster center or the group of massive stars surrounding the Wolf–Rayet star W72/A. A long pillar is also observed in the northwest. The MIRI images also show resolved shells and outflows surrounding the M-type supergiants W20, W26, W75, and W237, the sgB[e] star W9 and the yellow hypergiant W4. Some of these shells have been observed before at other wavelengths, but never with the level of detail provided by JWST. The color-magnitude diagrams built using the NIRCam photometry show a clear cluster sequence, which is marked in its upper part by the 1828 NIRCam stars with X-ray counterparts. NIRCam observations using the F115W filter have reached the 23.8 mag limit with 50% completeness (roughly corresponding to a 0.06 M0 brown dwarf). 

Abstract Next-generation surveys like the Legacy Survey of Space and Time (LSST) on the Vera C. Rubin Observatory (Rubin) will generate orders of magnitude more discoveries of transients and variable stars than previous surveys. To prepare for this data deluge, we developed the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC), a competition that aimed to catalyze the development of robust classifiers under LSST-like conditions of a nonrepresentative training set for a large photometric test set of imbalanced classes. Over 1000 teams participated in PLAsTiCC, which was hosted in the Kaggle data science competition platform between 2018 September 28 and 2018 December 17, ultimately identifying three winners in 2019 February. Participants produced classifiers employing a diverse set of machine-learning techniques including hybrid combinations and ensemble averages of a range of approaches, among them boosted decision trees, neural networks, and multilayer perceptrons. The strong performance of the top three classifiers on Type Ia supernovae and kilonovae represent a major improvement over the current state of the art within astronomy. This paper summarizes the most promising methods and evaluates their results in detail, highlighting future directions both for classifier development and simulation needs for a next-generation PLAsTiCC data set.