Balibrea-Correa, J., Lerendegui-Marco, J., Calvo, D., Caballero, L., Babiano, V., Ladarescu, I., et al. (2021). A first prototype of C6D6 total-energy detector with SiPM readout for neutron capture time-of-flight experiments. Nucl. Instrum. Methods Phys. Res. A, 985, 164709–8pp.
Abstract: Low efficiency total-energy detectors (TEDs) are one of the main tools for neutron capture cross section measurements utilizing the time-of-flight (TOF) technique. State-of-the-art TEDs are based on a C6D6 liquid-scintillation cell optically coupled to a fast photomultiplier tube. The large photomultiplier tube represents yet a significant contribution to the so-called neutron sensitivity background, which is one of the most conspicuous sources of uncertainty in this type of experiments. Here we report on the development of a first prototype of a TED based on a silicon-photomultiplier (SiPM) readout, thus resulting in a lightweight and much more compact detector. Apart from the envisaged improvement in neutron sensitivity, the new system uses low voltage (+28 V) and low current supply (-50 mA), which is more practical than the-kV supply required by conventional photomultipliers. One important difficulty hindering the earlier implementation of SiPM readout for this type of detector was the large capacitance for the output signal when all pixels of a SiPM array are summed together. The latter leads to long pulse rise and decay times, which are not suitable for time-of-flight experiments. In this work we demonstrate the feasibility of a Schottky-diode multiplexing readout approach, that allows one to preserve the excellent timing properties of SiPMs, hereby paving the way for their implementation in future neutron TOF experiments.
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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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Balibrea-Correa, J., Lerendegui-Marco, J., Babiano-Suarez, V., Caballero, L., Calvo, D., Ladarescu, I., et al. (2021). Machine Learning aided 3D-position reconstruction in large LaCl3 crystals. Nucl. Instrum. Methods Phys. Res. A, 1001, 165249–17pp.
Abstract: We investigate five different models to reconstruct the 3D gamma-ray hit coordinates in five large LaCl3(Ce) monolithic crystals optically coupled to pixelated silicon photomultipliers. These scintillators have a base surface of 50 x 50 mm(2) and five different thicknesses, from 10 mm to 30 mm. Four of these models are analytical prescriptions and one is based on a Convolutional Neural Network. Average resolutions close to 1-2 mm fwhm are obtained in the transverse crystal plane for crystal thicknesses between 10 mm and 20 mm using analytical models. For thicker crystals average resolutions of about 3-5 mm fwhm are obtained. Depth of interaction resolutions between 1 mm and 4 mm are achieved depending on the distance of the interaction point to the photosensor surface. We propose a Machine Learning algorithm to correct for linearity distortions and pin-cushion effects. The latter allows one to keep a large field of view of about 70%-80% of the crystal surface, regardless of crystal thickness. This work is aimed at optimizing the performance of the so-called Total Energy Detector with Compton imaging capability (i-TED) for time-of-flight neutron capture cross-section measurements.
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Babiano-Suarez, V. et al, Lerendegui-Marco, J., Balibrea-Correa, J., Caballero, L., Calvo, D., Ladarescu, I., et al. (2021). Imaging neutron capture cross sections: i-TED proof-of-concept and future prospects based on Machine-Learning techniques. Eur. Phys. J. A, 57(6), 197–17pp.
Abstract: i-TED is an innovative detection system which exploits Compton imaging techniques to achieve a superior signal-to-background ratio in (n, gamma) cross-section measurements using time-of-flight technique. This work presents the first experimental validation of the i-TED apparatus for high-resolution time-of-flight experiments and demonstrates for the first time the concept proposed for background rejection. To this aim, the Au-197(n, gamma) and Fe-56(n, gamma) reactions were studied at CERN n_TOF using an i-TED demonstrator based on three position-sensitive detectors. Two C6D6 detectors were also used to benchmark the performance of i-TED. The i-TED prototype built for this study shows a factor of similar to 3 higher detection sensitivity than state-of-the-art C6D6 detectors in the 10 keV neutron-energy region of astrophysical interest. This paper explores also the perspectives of further enhancement in performance attainable with the final i-TED array consisting of twenty position-sensitive detectors and newanalysis methodologies based on Machine-Learning techniques.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Calvo, D., Carretero, V., Colomer, M., Hernandez-Rey, J. J., et al. (2021). The KM3NeT potential for the next core-collapse supernova observation with neutrinos. Eur. Phys. J. C, 81(5), 445–19pp.
Abstract: The KM3NeT research infrastructure is under construction in the Mediterranean Sea. It consists of two water Cherenkov neutrino detectors, ARCA and ORCA, aimed at neutrino astrophysics and oscillation research, respectively. Instrumenting a large volume of sea water with similar to 6200 optical modules comprising a total of similar to 200,000 photomultiplier tubes, KM3NeT will achieve sensitivity to similar to 10 MeV neutrinos from Galactic and near-Galactic core-collapse supernovae through the observation of coincident hits in photomultipliers above the background. In this paper, the sensitivity of KM3NeT to a supernova explosion is estimated from detailed analyses of background data from the first KM3NeT detection units and simulations of the neutrino signal. The KM3NeT observational horizon (for a 5 sigma discovery) covers essentially the Milky-Way and for the most optimistic model, extends to the Small Magellanic Cloud (similar to 60 kpc). Detailed studies of the time profile of the neutrino signal allow assessment of the KM3NeT capability to determine the arrival time of the neutrino burst with a few milliseconds precision for sources up to 5-8 kpc away, and detecting the peculiar signature of the standing accretion shock instability if the core-collapse supernova explosion happens closer than 3-5 kpc, depending on the progenitor mass. KM3NeT's capability to measure the neutrino flux spectral parameters is also presented.
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