Low energy event classification in IceCube using boosted decision trees

The DeepCore sub-array within the IceCube Neutrino Observatory is a densely instrumented region of Antarctic ice designed to observe atmospheric neutrino interactions above 5 GeV via Cherenkov radiation. An essential aspect of any neutrino oscillation analysis is the ability to accurately identify the flavor of neutrino events in the detector. This task is particularly difficult at low energies when very little light is deposited in the detector. Here we discuss the use of machine learning to perform event classification at low energies in IceCube using a boosted decision tree (BDT). A BDT is trained using reconstructed quantities to identify track-like events, which result from muon neutrino charged current interactions. This new method improves the accuracy of particle identification compared to traditional classification methods which rely on univariate straight cuts.

Small 𝜃13 and solar neutrino oscillation parameters from μ − τ symmetry

Exchange [Formula: see text] symmetry in the effective Majorana neutrino mass matrix does predict a maximal mixing for atmospheric neutrino oscillations asides to a null mixing that cannot be straightforwardly identified with reactor neutrino oscillation mixing, [Formula: see text], unless a specific ordering is assumed for the mass eigenstates. Otherwise, a nonzero value for [Formula: see text] is predicted already at the level of an exact symmetry. In this case, solar neutrino mixing and scale, as well as the correct atmospheric mixing arise from the breaking of the symmetry. I present a mass matrix proposal for normal hierarchy that realizes this scenario, where the smallness of [Formula: see text] is naturally given by the parameter [Formula: see text] and the solar mixing is linked to the smallness of [Formula: see text]. The proposed matrix remains stable under renormalization effects and it also allows to account for CP violation within the expected region without further constrains.

Sterile Neutrinos with Neutrino Telescopes

Searches for light sterile neutrinos are motivated by the unexpected observation of an electron neutrino appearance in short-baseline experiments, such as the Liquid Scintillator Neutrino Detector (LSND) and the Mini Booster Neutrino Experiment (MiniBooNE). In light of these unexpected results, a campaign using natural and anthropogenic sources to find the light (mass-squared-difference around 1 eV2) sterile neutrinos is underway. Among the natural sources, atmospheric neutrinos provide a unique gateway to search for sterile neutrinos due to the broad range of baseline-to-energy ratios, L/E, and the presence of significant matter effects. Since the atmospheric neutrino flux rapidly falls with energy, studying its highest energy component requires gigaton-scale neutrino detectors. These detectors—often known as neutrino telescopes since they are designed to observe tiny astrophysical neutrino fluxes—have been used to perform searches for light sterile neutrinos, and researchers have found no significant signal to date. This brief review summarizes the current status of searches for light sterile neutrinos with neutrino telescopes deployed in solid and liquid water.

Atmospheric neutrinos with the first detection units of KM3NeT/ARCA

The KM3NeT collaboration is constructing two deep-sea Cherenkov detectors in the Mediterranean Sea. The ARCA detector aims at TeV-PeV neutrino astronomy, while the ORCA detector is optimised for atmospheric neutrino oscillation studies at energies of a few GeV. In this contribution, an analysis of the data collected with the first deployed detection units of the ARCA detector is presented. A high-purity sample of atmospheric neutrinos is selected demonstrating the capability of the ARCA detector.

JUNO sensitivity to low energy atmospheric neutrino spectra

Atmospheric neutrinos are one of the most relevant natural neutrino sources that can be exploited to infer properties about cosmic rays and neutrino oscillations. The Jiangmen Underground Neutrino Observatory (JUNO) experiment, a 20 kton liquid scintillator detector with excellent energy resolution is currently under construction in China. JUNO will be able to detect several atmospheric neutrinos per day given the large volume. A study on the JUNO detection and reconstruction capabilities of atmospheric $$\nu _e$$ ν e and $$\nu _\mu $$ ν μ fluxes is presented in this paper. In this study, a sample of atmospheric neutrino Monte Carlo events has been generated, starting from theoretical models, and then processed by the detector simulation. The excellent timing resolution of the 3” PMT light detection system of JUNO detector and the much higher light yield for scintillation over Cherenkov allow to measure the time structure of the scintillation light with very high precision. Since $$\nu _e$$ ν e and $$\nu _\mu $$ ν μ interactions produce a slightly different light pattern, the different time evolution of light allows to discriminate the flavor of primary neutrinos. A probabilistic unfolding method has been used, in order to infer the primary neutrino energy spectrum from the detector experimental observables. The simulated spectrum has been reconstructed between 100 MeV and 10 GeV, showing a great potential of the detector in the atmospheric low energy region.

Future prospects in neutrino physics

Neutrino physics has come a long way and made great strides in the past decades. We discuss the prospects of what more can be learned in this field in the forthcoming neutrino oscillation facilities. We will mostly focus on the potential of the long-baseline experiments and the atmospheric neutrino experiments. Sensitivity of these experiments to standard neutrino oscillation parameters will be presented. We will also discuss the prospects of new physics searches at these facilities.