KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Calvo, D., Carretero, V., Garcia Soto, A., Gozzini, S. R., et al. (2023). First observation of the cosmic ray shadow of the Moon and the Sun with KM3NeT/ORCA. Eur. Phys. J. C, 83(4), 344–9pp.
Abstract: This article reports the first observation of the Moon and the Sun shadows in the sky distribution of cosmicray induced muons measured by the KM3NeT/ORCA detector. The analysed data-taking period spans from February 2020 to November 2021, when the detector had 6 Detection Units deployed at the bottom of the Mediterranean Sea, each composed of 18 Digital Optical Modules. The shadows induced by theMoon and the Sun were detected at their nominal position with a statistical significance of 4.2 sigma and 6.2 sigma, and an angular resolution of sigma(res) = 0.49 degrees and sigma(res) = 0.66 degrees, respectively, consistent with the prediction of 0.53 degrees from simulations. This early result confirms the effectiveness of the detector calibration, in time, position and orientation and the accuracy of the event direction reconstruction. This also demonstrates the performance and the competitiveness of the detector in terms of pointing accuracy and angular resolution.
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ANTARES Collaboration(Reeb, N. et al), Alves, S., Carretero, V., Colomer, M., Hernandez-Rey, J. J., Khan-Chowdhury, N. R., et al. (2023). Studying bioluminescence flashes with the ANTARES deep-sea neutrino telescope. Limnol. Oceanogr. Meth., 21(11), 734–760.
Abstract: We develop a novel technique to exploit the extensive data sets provided by underwater neutrino telescopes to gain information on bioluminescence in the deep sea. The passive nature of the telescopes gives us the unique opportunity to infer information on bioluminescent organisms without actively interfering with them. We propose a statistical method that allows us to reconstruct the light emission of individual organisms, as well as their location and movement. A mathematical model is built to describe the measurement process of underwater neutrino telescopes and the signal generation of the biological organisms. The Metric Gaussian Variational Inference algorithm is used to reconstruct the model parameters using photon counts recorded by photomultiplier tubes. We apply this method to synthetic data sets and data collected by the ANTARES neutrino telescope. The telescope is located 40 km off the French coast and fixed to the sea floor at a depth of 2475 m. The runs with synthetic data reveal that we can model the emitted bioluminescent flashes of the organisms. Furthermore, we find that the spatial resolution of the localization of light sources highly depends on the configuration of the telescope. Precise measurements of the efficiencies of the detectors and the attenuation length of the water are crucial to reconstruct the light emission. Finally, the application to ANTARES data reveals the first localizations of bioluminescent organisms using neutrino telescope data.
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