Abstract: The Hamamatsu R12199-023-inch photomultiplier tube is the photodetector chosen for the first phase of the KM3NeT neutrino telescope. About 7000 photomultipliers have been characterised for dark count rate, timing spread and spurious pulses. The quantum efficiency, the gain and the peak-to-valley ratio have also been measured for a sub-sample in order to determine parameter values needed as input to numerical simulations of the detector.

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.

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.

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.

Abstract: A theta (13) oscillation analysis based on the observed antineutrino rates at the Double Chooz far and near detectors for different reactor power conditions is presented. This approach provides a so far unique simultaneous determination of theta (13) and the total background rates without relying on any assumptions on the specific background contributions. The analysis comprises 865 days of data collected in both detectors with at least one reactor in operation. The oscillation results are enhanced by the use of 24.06 days (12.74 days) of reactor-off data in the far (near) detector. The analysis considers the nu <mml:mo stretchy=“true”><overbar></mml:mover>e interactions up to a visible energy of 8.5 MeV, using the events at higher energies to build a cosmogenic background model considering fast-neutrons interactions and Li-9 decays. The background-model-independent determination of the mixing angle yields sin(2)(2 theta (13)) = 0.094 0.017, being the best-fit total background rates fully consistent with the cosmogenic background model. A second oscillation analysis is also performed constraining the total background rates to the cosmogenic background estimates. While the central value is not significantly modified due to the consistency between the reactor-off data and the background estimates, the addition of the background model reduces the uncertainty on theta (13) to 0.015. Along with the oscillation results, the normalization of the anti-neutrino rate is measured with a precision of 0.86%, reducing the 1.43% uncertainty associated to the expectation.