The Online Data Filter for the KM3NeT Neutrino Telescopes
O. Adriani, S. Aiello, A. Albert, A.R. Alhebsi, M. Alshamsi, S. Alves Garre, A. Ambrosone, F. Ameli, M. Andre, L. Aphecetche, M. Ardid, S. Ardid, J. Aublin, F. Badaracco, L. Bailly-Salins, Z. Bardacova, B. Baret, A. Bariego-Quintana, Y. Becherini, M. Bendahman

TL;DR
This paper presents the design and performance evaluation of the real-time data filtering software used in the KM3NeT neutrino telescopes, focusing on efficiency, purity, and capacity to optimize neutrino detection in deep-sea environments.
Contribution
It introduces a novel data filtering software for KM3NeT that effectively manages high data rates while maintaining detection accuracy.
Findings
Filter efficiency correlates with neutrino energy levels.
Purity assessment shows effective discrimination between neutrino signals and background noise.
System capacity meets all operational specifications.
Abstract
The KM3NeT research infrastructure comprises two neutrino telescopes located in the deep waters of the Mediterranean Sea, namely ORCA and ARCA. KM3NeT/ORCA is designed for the measurement of neutrino properties and KM3NeT/ARCA for the detection of high-energy neutrinos from the cosmos. Neutrinos are indirectly detected using three-dimensional arrays of photo-sensors which detect the Cherenkov light that is produced when relativistic charged particles emerge from a neutrino interaction. The analogue pulses from the photo-sensors are digitised offshore and all digital data are sent to a station on shore where they are processed in real time using a farm of commodity servers and custom software. In this paper, the design and performance of the software that is used to filter the data are presented. The performance of the data filter is evaluated in terms of its efficiency, purity and…
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