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The Baikal Gigaton Volume Detector (Baikal-GVD) is a km$$^3$$ 3 -scale neutrino detector currently under construction in Lake Baikal, Russia. The detector consists of several thousand optical sensors arranged on vertical strings, with 36 sensors per string. The strings are grouped into clusters of 8 strings each. Each cluster can operate as a stand-alone neutrino detector. The detector layout is optimized for the measurement of astrophysical neutrinos with energies of $$\sim $$ ∼ 100 TeV and above. Events resulting from charged current interactions of muon (anti-)neutrinos will have a track-like topology in Baikal-GVD. A fast $$\chi ^2$$ χ 2 -based reconstruction algorithm has been developed to reconstruct such track-like events. The algorithm has been applied to data collected in 2019 from the first five operational clusters of Baikal-GVD, resulting in observations of both downgoing atmospheric muons and upgoing atmospheric neutrinos. This serves as an important milestone towards experimental validation of the Baikal-GVD design. The analysis is limited to single-cluster data, favoring nearly-vertical tracks.

Performance of the muon track reconstruction with the Baikal-GVD neutrino telescopeGrigory Safronov , * on behalf of the Baikal-GVD Collaboration

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The Cosmic-Ray Extremely Distributed Observatory (CREDO) uses the hunt for particle cascades from deep space as a vehicle for a unique "bottom-up" approach to scientific research. By engaging the non-specialist public of all ages as "citizen scientists" we create opportunities for lifelong learning for individuals as well as for cooperation and the sharing of common educational tools amongst institutions. The discoveries of these citizen scientists will feed directly into a pioneering new area of scientific research oriented on Cosmic Ray Ensembles (CRE). The detection (or nondetection) of such particle groups promises to open up a new method for exploring our universe, and a new channel on the multi-messenger stage, oriented on both astro-and geo-investigations. The opportunities this would create for cross-disciplinary research are significant and beneficial for individuals, networks of institutions and the global communities of both professional scientists and science enthusiasts.

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