We have searched for a deeply bound kaonic state by using the FINUDA spectrometer installed at the e(+)e(-) collider DAPhiNE. Almost monochromatic K(-)'s produced through the decay of phi(1020) mesons are used to observe K(-) absorption reactions stopped on very thin nuclear targets. Taking this unique advantage, we have succeeded to detect a kaon-bound state K(-)pp through its two-body decay into a Lambda hyperon and a proton. The binding energy and the decay width are determined from the invariant-mass distribution as 115(+6)(-5)(stat)(+3)(-4)(syst) MeV and 67(+14)(-11)(stat)(+2)(-3)(syst) MeV, respectively.

Estimating the pose of multiple animals is a challenging computer vision problem: frequent interactions cause occlusions and complicate the association of detected keypoints to the correct individuals, as well as having extremely similar looking animals that interact more closely than in typical multi-human scenarios. To take up this challenge, we build on DeepLabCut, a popular open source pose estimation toolbox, and provide high-performance animal assembly and tracking—features required for robust multi-animal scenarios. Furthermore, we integrate the ability to predict an animal’s identity directly to assist tracking (in case of occlusions). We illustrate the power of this framework with four datasets varying in complexity, which we release to serve as a benchmark for future algorithm development.

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AbstractΛ-hypernuclei are produced and studied, with the FINUDA spectrometer, for the first time at an e + e − collider: DAΦNE, the Frascati φ-factory. The slow negative kaons from φ(1020) decay are stopped in thin (0.2 g/cm 2 ) nuclear targets, and Λ-hypernuclei formation is detected by measuring the momentum of the outgoing π − . A preliminary analysis on 12 Λ C shows an energy resolution of 1.29 MeV FWHM on the hypernuclear levels, the best obtained so far with magnetic spectrometers at hadron facilities. Capture rates for the ground state and the excited ones are reported, and compared with previous experiments.PACS: 21.80.+a