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KM3NeT Collaboration(Adrian-Martinez, S. et al), Barrios-Marti, J., Calvo, D., Hernandez-Rey, J. J., Illuminati, G., Lotze, M., et al. (2017). Intrinsic limits on resolutions in muon- and electron-neutrino charged-current events in the KM3NeT/ORCA detector. J. High Energy Phys., 05(5), 008–39pp.
Abstract: Studying atmospheric neutrino oscillations in the few-GeV range with a multimegaton detector promises to determine the neutrino mass hierarchy. This is the main science goal pursued by the future KM3NeT/ORCA water Cherenkov detector in the Mediterranean Sea. In this paper, the processes that limit the obtainable resolution in both energy and direction in charged-current neutrino events in the ORCA detector are investigated. These processes include the composition of the hadronic fragmentation products, the subsequent particle propagation and the photon-sampling fraction of the detector. GEANT simulations of neutrino interactions in seawater produced by GENIE are used to study the effects in the 1-20 GeV range. It is found that fluctuations in the hadronic cascade in conjunction with the variation of the inelasticity y are most detrimental to the resolutions. The effect of limited photon sampling in the detector is of significantly less importance. These results will therefore also be applicable to similar detectors/media, such as those in ice.
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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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ANTARES Collaboration(Albert, A. et al), Barrios-Marti, J., Coleiro, A., Hernandez-Rey, J. J., Illuminati, G., Lotze, M., et al. (2017). First all-flavor neutrino pointlike source search with the ANTARES neutrino telescope. Phys. Rev. D, 96(8), 082001–15pp.
Abstract: A search for cosmic neutrino sources using the data collected with the ANTARES neutrino telescope between early 2007 and the end of 2015 is performed. For the first time, all neutrino interactions-charged and neutral-current interactions of all flavors-are considered in a search for point-like sources with the ANTARES detector. In previous analyses, only muon neutrino charged-current interactions were used. This is achieved by using a novel reconstruction algorithm for shower-like events in addition to the standard muon track reconstruction. The shower channel contributes about 23% of all signal events for an E-2 energy spectrum. No significant excess over background is found. The most signal-like cluster of events is located at (alpha, delta) = (343.8 degrees, 23.5 degrees) with a significance of 1.9 sigma. The neutrino flux sensitivity of the search is about E(2)d Phi/dE = 6 x 10(-9) GeV cm(-2) s(-1) for declinations from -90 degrees up to -42 degrees, and below 10(-8) GeV cm(-2) s(-1) for declinations up to 5 degrees. The directions of 106 source candidates and 13 muon track events from the IceCube high-energy sample events are investigated for a possible neutrino signal and upper limits on the signal flux are determined.
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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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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Calvo, D., Carretero, V., Colomer, M., Hernandez-Rey, J. J., et al. (2022). Determining the neutrino mass ordering and oscillation parameters with KM3NeT/ORCA. Eur. Phys. J. C, 82(1), 26–16pp.
Abstract: The next generation of water Cherenkov neutrino telescopes in the Mediterranean Sea are under construction offshore France (KM3NeT/ORCA) and Sicily (KM3NeT/ARCA). The KM3NeT/ORCA detector features an energy detection threshold which allows to collect atmospheric neutrinos to study flavour oscillation. This paper reports the KM3NeT/ORCA sensitivity to this phenomenon. The event reconstruction, selection and classification are described. The sensitivity to determine the neutrino mass ordering was evaluated and found to be 4.4 sigma if the true ordering is normal and 2.3 sigma if inverted, after 3 years of data taking. The precision to measure Delta m(32)(2) and theta(23) were also estimated and found to be 85.10(-6) eV(2) and (<b>(+1.9)(-3.1))degrees for normal neutrino mass ordering and, 75.10(-6) eV(2) and ((+2.0)(-7.0))degrees for inverted ordering. Finally, a unitarity test of the leptonic mixing matrix by measuring the rate of tau neutrinos is described. Three years of data taking were found to be sufficient to exclude (nu)over-left-right-arrow tau event rate variations larger than 20% at 3 sigma level.
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