KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Bariego-Quintana, A., Calvo, D., Carretero, V., Cecchini, V., et al. (2024). Differential Sensitivity of the KM3NeT/ARCA detector to a diffuse neutrino flux and to point-like source emission: Exploring the case of the Starburst Galaxies. Astropart Phys., 162, 102990–9pp.
Abstract: KM3NeT/ARCA is a Cherenkov neutrino telescope under construction in the Mediterranean sea, optimised for the detection of astrophysical neutrinos with energies above similar to 1 TeV. In this work, using Monte Carlo simulations including all-flavour neutrinos, the integrated and differential sensitivities for KM3NeT/ARCA are presented considering the case of a diffuse neutrino flux as well as extended and point-like neutrino sources. This analysis is applied to Starburst Galaxies demonstrating that the detector has the capability of tracing TeV neutrinos from these sources. Remarkably, after eight years, a hard power-law spectrum from the nearby Small Magellanic Cloud can be constrained. The sensitivity and discovery potential for NGC 1068 is also evaluated showing that KM3NeT/ARCA will discriminate between different astrophysical components of the measured neutrino flux after 3 years of data taking.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Bariego-Quintana, A., Calvo, D., Carretero, V., Cecchini, V., et al. (2024). The Power Board of the KM3NeT Digital Optical Module: Design, Upgrade, and Production. Electronics, 13(11), 2044–17pp.
Abstract: The KM3NeT Collaboration is building an underwater neutrino observatory at the bottom of the Mediterranean Sea, consisting of two neutrino telescopes, both composed of a three-dimensional array of light detectors, known as digital optical modules. Each digital optical module contains a set of 31 three-inch photomultiplier tubes distributed over the surface of a 0.44 m diameter pressure-resistant glass sphere. The module also includes calibration instruments and electronics for power, readout, and data acquisition. The power board was developed to supply power to all the elements of the digital optical module. The design of the power board began in 2013, and ten prototypes were produced and tested. After an exhaustive validation process in various laboratories within the KM3NeT Collaboration, a mass production batch began, resulting in the construction of over 1200 power boards so far. These boards were integrated in the digital optical modules that have already been produced and deployed, which total 828 as of October 2023. In 2017, an upgrade of the power board, to increase reliability and efficiency, was initiated. The validation of a pre-production series has been completed, and a production batch of 800 upgraded boards is currently underway. This paper describes the design, architecture, upgrade, validation, and production of the power board, including the reliability studies and tests conducted to ensure safe operation at the bottom of the Mediterranean Sea throughout the observatory's lifespan.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Bariego-Quintana, A., Calvo, D., Carretero, V., Cecchini, V., et al. (2024). Astronomy potential of KM3NeT/ARCA. Eur. Phys. J. C, 84(9), 885–17pp.
Abstract: The KM3NeT/ARCA neutrino detector is currently under construction at 3500 m depth offshore Capo Passero, Sicily, in the Mediterranean Sea. The main science objectives are the detection of high-energy cosmic neutrinos and the discovery of their sources. Simulations were conducted for the full KM3NeT/ARCA detector, instrumenting a volume of 1 km(3), to estimate the sensitivity and discovery potential to point-like neutrino sources. This paper covers the reconstruction of track- and shower-like signatures, as well as the criteria employed for neutrino event selection. With an angular resolution below 0.1 degrees for tracks and under 2 degrees for showers, the sensitivity to point-like neutrino sources surpasses existing observed limits across the entire sky.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Bariego-Quintana, A., Calvo, D., Carretero, V., Cecchini, V., et al. (2024). Measurement of neutrino oscillation parameters with the first six detection units of KM3NeT/ORCA. J. High Energy Phys., 10(10), 206–31pp.
Abstract: KM3NeT/ORCA is a water Cherenkov neutrino detector under construction and anchored at the bottom of the Mediterranean Sea. The detector is designed to study oscillations of atmospheric neutrinos and determine the neutrino mass ordering. This paper focuses on an initial configuration of ORCA, referred to as ORCA6, which comprises six out of the foreseen 115 detection units of photo-sensors. A high-purity neutrino sample was extracted, corresponding to an exposure of 433 kton-years. The sample of 5828 neutrino candidates is analysed following a binned log-likelihood method in the reconstructed energy and cosine of the zenith angle. The atmospheric oscillation parameters are measured to be sin(2)theta(23) = 0.51(-0.05)(+0.04), and Delta m(31)(2) = 2.18(-0.35)(+0.25) x 10(-3) eV(2) boolean OR {-2.25,-1.76} x 10(-3) eV(2) at 68% CL. The inverted neutrino mass ordering hypothesis is disfavoured with a p-value of 0.25.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Bariego-Quintana, A., Calvo, D., Carretero, V., Garcia Soto, A., et al. (2024). Searches for neutrino counterparts of gravitational waves from the LIGO/Virgo third observing run with KM3NeT. J. Cosmol. Astropart. Phys., 04(4), 026–28pp.
Abstract: The KM3NeT neutrino telescope is currently being deployed at two different sites in the Mediterranean Sea. First searches for astrophysical neutrinos have been performed using data taken with the partial detector configuration already in operation. The paper presents the results of two independent searches for neutrinos from compact binary mergers detected during the third observing run of the LIGO and Virgo gravitational wave interferometers. The first search looks for a global increase in the detector counting rates that could be associated with inverse beta decay events generated by MeV-scale electron anti -neutrinos. The second one focuses on upgoing track -like events mainly induced by muon (anti -)neutrinos in the GeV-TeV energy range. Both searches yield no significant excess for the sources in the gravitational wave catalogs. For each source, upper limits on the neutrino flux and on the total energy emitted in neutrinos in the respective energy ranges have been set. Stacking analyses of binary black hole mergers and neutron star -black hole mergers have also been performed to constrain the characteristic neutrino emission from these categories.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Bariego-Quintana, A., Calvo, D., Cecchini, V., Garcia Soto, A., et al. (2024). Atmospheric muons measured with the KM3NeT detectors in comparison with updated numeric predictions. Eur. Phys. J. C, 84(7), 696–19pp.
Abstract: The measurement of the flux of muons produced in cosmic ray air showers is essential for the study of primary cosmic rays. Such measurements are important in extensive air shower detectors to assess the energy spectrum and the chemical composition of the cosmic ray flux, complementary to the information provided by fluorescence detectors. Detailed simulations of the cosmic ray air showers are carried out, using codes such as CORSIKA, to estimate the muon flux at sea level. These simulations are based on the choice of hadronic interaction models, for which improvements have been implemented in the post-LHC era. In this work, a deficit in simulations that use state-of-the-art QCD models with respect to the measurement deep underwater with the KM3NeT neutrino detectors is reported. The KM3NeT/ARCA and KM3NeT/ORCA neutrino telescopes are sensitive to TeV muons originating mostly from primary cosmic rays with energies around 10 TeV. The predictions of state-of-the-art QCD models show that the deficit with respect to the data is constant in zenith angle; no dependency on the water overburden is observed. The observed deficit at a depth of several kilometres is compatible with the deficit seen in the comparison of the simulations and measurements at sea level.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Bariego-Quintana, A., Calvo, D., Cecchini, V., Garcia Soto, A., et al. (2024). Search for neutrino emission from GRB 221009A using the KM3NeT ARCA and ORCA detectors. J. Cosmol. Astropart. Phys., 08(8), 006–16pp.
Abstract: Gamma-ray bursts are promising candidate sources of high-energy astrophysical neutrinos. The recent GRB 221009A event, identified as the brightest gamma-ray burst ever detected, provides a unique opportunity to investigate hadronic emissions involving neutrinos. The KM3NeT undersea neutrino detectors participated in the worldwide follow-up effort triggered by the event, searching for neutrino events. In this paper, we summarize subsequent searches, in a wide energy range from MeV up to a few PeVs. No neutrino events are found in any of the searches performed. Upper limits on the neutrino emission associated with GRB 221009A are computed.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Calvo, D., Carretero, V., Colomer, M., Corredoira, I., et al. (2020). Deep-sea deployment of the KM3NeT neutrino telescope detection units by self-unrolling. J. Instrum., 15(11), P11027–18pp.
Abstract: KM3NeT is a research infrastructure being installed in the deep Mediterranean Sea. It will house a neutrino telescope comprising hundreds of networked moorings – detection units or strings – equipped with optical instrumentation to detect the Cherenkov radiation generated by charged particles from neutrino-induced collisions in its vicinity. In comparison to moorings typically used for oceanography, several key features of the KM3NeT string are different: the instrumentation is contained in transparent and thus unprotected glass spheres; two thin Dyneema (R) ropes are used as strength members; and a thin delicate backbone tube with fibre-optics and copper wires for data and power transmission, respectively, runs along the full length of the mooring. Also, compared to other neutrino telescopes such as ANTARES in the Mediterranean Sea and GVD in Lake Baikal, the KM3NeT strings are more slender to minimise the amount of material used for support of the optical sensors. Moreover, the rate of deploying a large number of strings in a period of a few years is unprecedented. For all these reasons, for the installation of the KM3NeT strings, a custom-made, fast deployment method was designed. Despite the length of several hundreds of metres, the slim design of the string allows it to be compacted into a small, re-usable spherical launching vehicle instead of deploying the mooring weight down from a surface vessel. After being lowered to the seafloor, the string unfurls to its full length with the buoyant launching vehicle rolling along the two ropes. The design of the vehicle, the loading with a string, and its underwater self-unrolling are detailed in this paper.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Calvo, D., Carretero, V., Colomer, M., Corredoira, I., et al. (2020). gSeaGen: The KM3NeT GENIE-based code for neutrino telescopes. Comput. Phys. Commun., 256, 107477–15pp.
Abstract: The gSeaGen code is a GENIE-based application developed to efficiently generate high statistics samples of events, induced by neutrino interactions, detectable in a neutrino telescope. The gSeaGen code is able to generate events induced by all neutrino flavours, considering topological differences between tracktype and shower-like events. Neutrino interactions are simulated taking into account the density and the composition of the media surrounding the detector. The main features of gSeaGen are presented together with some examples of its application within the KM3NeT project. Program summary Program Title: gSeaGen CPC Library link to program files: http://dx.doi.org/10.17632/ymgxvy2br4.1 Licensing provisions: GPLv3 Programming language: C++ External routines/libraries: GENIE [1] and its external dependencies. Linkable to MUSIC [2] and PROPOSAL [3]. Nature of problem: Development of a code to generate detectable events in neutrino telescopes, using modern and maintained neutrino interaction simulation libraries which include the state-of-the-art physics models. The default application is the simulation of neutrino interactions within KM3NeT [4]. Solution method: Neutrino interactions are simulated using GENIE, a modern framework for Monte Carlo event generators. The GENIE framework, used by nearly all modern neutrino experiments, is considered as a reference code within the neutrino community. Additional comments including restrictions and unusual features: The code was tested with GENIE version 2.12.10 and it is linkable with release series 3. Presently valid up to 5 TeV. This limitation is not intrinsic to the code but due to the present GENIE valid energy range. References: [1] C. Andreopoulos at al., Nucl. Instrum. Meth. A614 (2010) 87. [2] P. Antonioli et al., Astropart. Phys. 7 (1997) 357. [3] J. H. Koehne et al., Comput. Phys. Commun. 184 (2013) 2070. [4] S. Adrian-Martinez et al., J. Phys. G: Nucl. Part. Phys. 43 (2016) 084001.
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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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