KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Calvo, D., Carretero, V., Colomer, M., Corredoira, I., et al. (2020). Event reconstruction for KM3NeT/ORCA using convolutional neural networks. J. Instrum., 15(10), P10005–39pp.
Abstract: The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches.
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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. (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), Alves Garre, S., Calvo, D., Carretero, V., Colomer, M., Corredoira, I., et al. (2021). Architecture and performance of the KM3NeT front-end firmware. J. Astron. Telesc. Instrum. Syst., 7(1), 016001–24pp.
Abstract: The KM3NeT infrastructure consists of two deep-sea neutrino telescopes being deployed in the Mediterranean Sea. The telescopes will detect extraterrestrial and atmospheric neutrinos by means of the incident photons induced by the passage of relativistic charged particles through the seawater as a consequence of a neutrino interaction. The telescopes are configured in a three-dimensional grid of digital optical modules, each hosting 31 photomultipliers. The photomultiplier signals produced by the incident Cherenkov photons are converted into digital information consisting of the integrated pulse duration and the time at which it surpasses a chosen threshold. The digitization is done by means of time to digital converters (TDCs) embedded in the field programmable gate array of the central logic board. Subsequently, a state machine formats the acquired data for its transmission to shore. We present the architecture and performance of the front-end firmware consisting of the TDCs and the state machine.
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Aiola, S., Bandiera, L., Cavoto, G., De Benedetti, F., Fu, J., Guidi, V., et al. (2021). Progress towards the first measurement of charm baryon dipole moments. Phys. Rev. D, 103(7), 072003–15pp.
Abstract: Electromagnetic dipole moments of short-lived particles are sensitive to physics within and beyond the Standard Model of particle physics but have not been accessible experimentally to date. To perform such measurements it has been proposed to exploit the spin precession of channeled particles in bent crystals at the LHC. Progress that enables the first measurement of charm baryon dipole moments is reported. In particular, the design and characterization on beam of silicon and germanium bent crystal prototypes, the optimization of the experimental setup, and advanced analysis techniques are discussed. Sensitivity studies show that first measurements of Lambda(+)(c) and Xi(+)(c) baryon dipole moments can he performed in two years of data taking with an experimental setup positioned upstream of the LHCb detector.
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Aja, B. et al, & Gimeno, B. (2022). The Canfranc Axion Detection Experiment (CADEx): search for axions at 90 GHz with Kinetic Inductance Detectors. J. Cosmol. Astropart. Phys., 11(11), 044–29pp.
Abstract: We propose a novel experiment, the Canfranc Axion Detection Experiment (CADEx), to probe dark matter axions with masses in the range 330-460 μeV, within the W-band (80-110 GHz), an unexplored parameter space in the well-motivated dark matter window of Quantum ChromoDynamics (QCD) axions. The experimental design consists of a microwave resonant cavity haloscope in a high static magnetic field coupled to a highly sensitive detecting system based on Kinetic Inductance Detectors via optimized quasi-optics (horns and mirrors). The experiment is in preparation and will be installed in the dilution refrigerator of the Canfranc Underground Laboratory. Sensitivity forecasts for axion detection with CADEx, together with the potential of the experiment to search for dark photons, are presented.
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