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Double Chooz collaboration(de Kerret, H. et al), & Novella, P. (2018). Yields and production rates of cosmogenic Li-9 and He-8 measured with the Double Chooz near and far detectors. J. High Energy Phys., 11(11), 053–20pp.
Abstract: The yields and production rates of the radioisotopes Li-9 and He-8 created by cosmic muon spallation on C-12, have been measured by the two detectors of the Double Chooz experiment. The identical detectors are located at separate sites and depths, which means that they are subject to different muon spectra. The near (far) detector has an overburden of approximate to 120 m.w.e. (approximate to 300 m.w.e.) corresponding to a mean muon energy of 32.1 +/- 2.0 GeV (63.7 +/- 5.5 GeV). Comparing the data to a detailed simulation of the Li-9 and He-8 decays, the contribution of the He-8 radioisotope at both detectors is found to be compatible with zero. The observed Li-9 yields in the near and far detectors are 5.51 +/- 0.51 and 7.90 +/- 0.51, respectively, in units of 10(-8-1)g(-1)cm(2). The shallow overburdens of the near and far detectors give a unique insight when combined with measurements by KamLAND and Borexino to give the first multi-experiment, data driven relationship between the Li-9 yield and the mean muon energy according to the power law and Y-0 = (0.43 +/- 0.11) x 10(-8-1)g(-1)cm(2). This relationship gives future liquid scintillator based experiments the ability to predict their cosmogenic Li-9 background rates.
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ANTARES Collaboration(Albert, A. et al), Barrios-Marti, J., Coleiro, A., Colomer, M., Gozzini, R., Hernandez-Rey, J. J., et al. (2019). Measuring the atmospheric neutrino oscillation parameters and constraining the 3+1 neutrino model with ten years of ANTARES data. J. High Energy Phys., 06(6), 113–23pp.
Abstract: The ANTARES neutrino telescope has an energy threshold of a few tens of GeV. This allows to study the phenomenon of atmospheric muon neutrino disappearance due to neutrino oscillations. In a similar way, constraints on the 3+1 neutrino model, which foresees the existence of one sterile neutrino, can be inferred. Using data collected by the ANTARES neutrino telescope from 2007 to 2016, a new measurement of m 2 and (23) has been performed which is consistent with world best-fit values and constraints on the 3+1 neutrino model have been derived.
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PTOLEMY Collaboration(Betti, M. G. et al), Gariazzo, S., & Pastor, S. (2019). Neutrino physics with the PTOLEMY project: active neutrino properties and the light sterile case. J. Cosmol. Astropart. Phys., 07(7), 047–31pp.
Abstract: The PTOLEMY project aims to develop a scalable design for a Cosmic Neutrino Background (CNB) detector, the first of its kind and the only one conceived that can look directly at the image of the Universe encoded in neutrino background produced in the first second after the Big Bang. The scope of the work for the next three years is to complete the conceptual design of this detector and to validate with direct measurements that the non-neutrino backgrounds are below the expected cosmological signal. In this paper we discuss in details the theoretical aspects of the experiment and its physics goals. In particular, we mainly address three issues. First we discuss the sensitivity of PTOLEMY to the standard neutrino mass scale. We then study the perspectives of the experiment to detect the CNB via neutrino capture on tritium as a function of the neutrino mass scale and the energy resolution of the apparatus. Finally, we consider an extra sterile neutrino with mass in the eV range, coupled to the active states via oscillations, which has been advocated in view of neutrino oscillation anomalies. This extra state would contribute to the tritium decay spectrum, and its properties, mass and mixing angle, could be studied by analyzing the features in the beta decay electron spectrum.
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Baxter, D., Collar, J. I., Coloma, P., Dahl, C. E., Esteban, I., Ferrario, P., et al. (2020). Coherent elastic neutrino-nucleus scattering at the European Spallation Source. J. High Energy Phys., 02(2), 123–38pp.
Abstract: The European Spallation Source (ESS), presently well on its way to completion, will soon provide the most intense neutron beams for multi-disciplinary science. Fortuitously, it will also generate the largest pulsed neutrino flux suitable for the detection of Coherent Elastic Neutrino-Nucleus Scattering (CE nu NS), a process recently measured for the first time at ORNL's Spallation Neutron Source. We describe innovative detector technologies maximally able to profit from the order-of-magnitude increase in neutrino flux provided by the ESS, along with their sensitivity to a rich particle physics phenomenology accessible through high-statistics, precision CE nu NS measurements.
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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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