KM3NeT Collaboration(Aiello, S. et al), Calvo, D., Coleiro, A., Colomer, M., Gozzini, S. R., Hernandez-Rey, J. J., et al. (2019). KM3NeT front-end and readout electronics system: hardware, firmware, and software. J. Astron. Telesc. Instrum. Syst., 5(4), 046001–15pp.
Abstract: The KM3NeT research infrastructure being built at the bottom of the Mediterranean Sea will host water-Cherenkov telescopes for the detection of cosmic neutrinos. The neutrino telescopes will consist of large volume three-dimensional grids of optical modules to detect the Cherenkov light from charged particles produced by neutrino-induced interactions. Each optical module houses 31 3-in. photomultiplier tubes, instrumentation for calibration of the photomultiplier signal and positioning of the optical module, and all associated electronics boards. By design, the total electrical power consumption of an optical module has been capped at seven Watts. We present an overview of the front-end and readout electronics system inside the optical module, which has been designed for a 1-ns synchronization between the clocks of all optical modules in the grid during a life time of at least 20 years. (C) 2019 Society of Photo-Optical Instrumentation Engineers (SPIE)
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KM3NeT Collaboration(Aiello, S. et al), Calvo, D., Coleiro, A., Colomer, M., Gozzini, S. R., Hernandez-Rey, J. J., et al. (2020). The Control Unit of the KM3NeT Data Acquisition System. Comput. Phys. Commun., 256, 107433–16pp.
Abstract: The KM3NeT Collaboration runs a multi-site neutrino observatory in the Mediterranean Sea. Water Cherenkov particle detectors, deep in the sea and far off the coasts of France and Italy, are already taking data while incremental construction progresses. Data Acquisition Control software is operating off-shore detectors as well as testing and qualification stations for their components. The software, named Control Unit, is highly modular. It can undergo upgrades and reconfiguration with the acquisition running. Interplay with the central database of the Collaboration is obtained in a way that allows for data taking even if Internet links fail. In order to simplify the management of computing resources in the long term, and to cope with possible hardware failures of one or more computers, the KM3NeT Control Unit software features a custom dynamic resource provisioning and failover technology, which is especially important for ensuring continuity in case of rare transient events in multi-messenger astronomy. The software architecture relies on ubiquitous tools and broadly adopted technologies and has been successfully tested on several operating systems.
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Coleiro, A., Colomer, M., Dornic, D., Lincetto, M., & Kulikovskiy, V. (2020). Combining neutrino experimental light-curves for pointing to the next galactic core-collapse supernova. Eur. Phys. J. C, 80(9), 856–12pp.
Abstract: The multi-messenger observation of the next galactic core-collapse supernova will shed light on the different physical processes involved in these energetic explosions. Good timing and pointing capabilities of neutrino detectors would help in the search for an electromagnetic or gravitational-wave counterparts. An approach for the determination of the arrival time delay of the neutrino signal at different experiments using a direct detected neutrino light-curve matching is discussed. A simplified supernova model and detector simulation are used for its application. The arrival time delay and its uncertainty between two neutrino detectors are estimated with chi-square and cross-correlation methods. The direct comparison of the detected light-curves offers the advantage to be model-independent. Millisecond time resolution on the arrival time delay at two different detectors is needed. Using the computed time delay between different combinations of currently operational and future detectors, a triangulation method is used to infer the supernova localisation in the sky. The combination of IceCube, Hyper-Kamiokande, JUNO and KM3NeT/ARCA provides a 90% confidence area of 140 +/- 20 deg(2). These low-latency analysis methods can be implemented in the SNEWS alert system.
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