Probing the neutrino mass ordering with KM3NeT-ORCA: Analysis and perspectives

The discrimination of the two possible options for the neutrino mass ordering (normal or inverted) is a major goal for current and future neutrino oscillation experiments. Such goal might be reached by observing high-statistics energy-angle spectra of events induced by atmospheric neutrinos and antineutrinos propagating in the Earth matter. Large volume water-Cherenkov detectors envisaged to this purpose include the so-called KM3NeT-ORCA project (in seawater) and the IceCube-PINGU project (in ice). Building upon a previous work focused on PINGU, we study in detail the effects of various systematic uncertainties on the ORCA sensitivity to the mass ordering, for the reference configuration with 9 m vertical spacing. We point out the need to control spectral shape uncertainties at the percent level, the effects of better priors on the theta-23 mixing parameter, and the benefits of an improved flavor identification in reconstructed ORCA events.Comment: 15 pages, including 7 figures. A few paragraphs and references added. Invited contribution to appear in the JPG Focus Issue on "Neutrino Mass and Mass Ordering

Self-induced temporal instability from a neutrino antenna

It has been recently shown that the flavor composition of a self-interacting neutrino gas can spontaneously acquire a time-dependent pulsating component during its flavor evolution. In this work, we perform a more detailed study of this effect in a model where neutrinos are assumed to be emitted in a two-dimensional plane from an infinite line that acts as a neutrino antenna. We consider several examples with varying matter and neutrino densities and find that temporal instabilities with various frequencies are excited in a cascade. We compare the numerical calculations of the flavor evolution with the predictions of linearized stability analysis of the equations of motion. The results obtained with these two approaches are in good agreement in the linear regime, while a dramatic speed-up of the flavor conversions occurs in the non-linear regime due to the interactions among the different pulsating modes. We show that large flavor conversions can take place if some of the temporal modes are unstable for long enough, and that this can happen even if the matter and neutrino densities are changing, as long as they vary slowly.Comment: v2: revised version, 15 pages, 6 figures. Minor changes. Typos removed, figures improved. Matches the version accepted on JCA

Neutrino Mass Hierarchy and Neutrino Oscillation Parameters with One Hundred Thousand Reactor Events

Abstract High-statistics reactor neutrino experiments at medium baselines will probe mass-mixing parameters governing neutrino oscillations at long wavelength, driven by the ( δm 2 , θ 12 ) and at short wavelength, driven by (Δ m 2 , θ 13 ).The interference between these two oscillations will allow to probe the mass hierarchy. The determination of the neutrino mass spectrum hierarchy, however, will require an unprecedented level of detector performance and collected statistics, and the control of several systematics at (sub)percent level. In this work we perform accurate theoretical calculations of reactor event spectra and refined statistical analyses to show that with O (10 5 ) reactor events, a typical sensitivity of ∼ 2 σ could be achieved by an experiment such as JUNO. We also show the impact of the energy scale and spectrum shape systematics on the determination of the hierarchy

Fast flavor conversions of supernova neutrinos: Classifying instabilities via dispersion relations

Supernova neutrinos can exhibit a rich variety of flavor conversion mechanisms. In particular, they can experience "fast" self-induced flavor conversions almost immediately above the core. Very recently, a novel method has been proposed to investigate these phenomena, in terms of the dispersion relation for the complex frequency and wave number ($\omega$,$k$) of disturbances in the mean field of the $\nu_e\nu_x$ flavor coherence. We discuss a systematic approach to such instabilities, originally developed in the context of plasma physics, and based of the time-asymptotic behavior of the Green's function of the system. Instabilities are typically seen to emerge for complex $\omega$, and can be further characterized as convective (moving away faster than they spread) and absolute (growing locally), depending on $k$-dependent features. Stable cases emerge when $k$ (but not $\omega$) is complex, leading to disturbances damped in space, or when both $\omega$ and $k$ are real, corresponding to complete stability. The analytical classification of both unstable and stable modes leads not only to qualitative insights about their features but also to quantitative predictions about the growth rates of instabilities. Representative numerical solutions are discussed in a simple two-beam model of interacting neutrinos. As an application, we argue that supernova and binary neutron star mergers exhibiting a "crossing" in the electron lepton number would lead to an absolute instability in the flavor content of the neutrino gas.Comment: (v2, revised version: 25 pages, 15 pdf figures. Minor changes. Figures improved. Matches the version published on PRD

Axion-like particles from primordial black holes shining through the Universe

We consider a cosmological scenario in which the very early Universe experienced a transient epoch of matter domination due to the formation of a large population of primordial black holes (PBHs) with masses $M \lesssim 10^{9}\,\textrm{g}$, that evaporate before Big Bang nucleosynthesis. In this context, Hawking radiation would be a non-thermal mechanism to produce a cosmic background of axion-like particles (ALPs). We assume the minimal scenario in which these ALPs couple only with photons. In the case of ultralight ALPs ($m_a \lesssim 10^{-9}\,\textrm{eV}$) the cosmic magnetic fields might trigger ALP-photon conversions, while for masses $m_a \gtrsim 10\,\textrm{eV}$ spontaneous ALP decay in photon pairs would be effective. We investigate the impact of these mechanisms on the cosmic X-ray background, on the excess in X-ray luminosity in Galaxy Clusters, and on the process of cosmic reionization.Comment: (33 pages, 12 pdf figures

Global 3ν oscillation analysis: Status of unknown parameters and future systematic challenges for ORCA and PINGU

Within the standard 3ν oscillation framework, we illustrate the status of currently unknown oscillation parameters: the θ23 octant, the mass hierarchy (normal or inverted), and the possible CP-violating phase δ, as derived by a (preliminary) global analysis of oscillation data available in 2015. We then discuss some challenges that will be faced by future, high-statistics analyses of spectral data, starting with one-dimensional energy spectra in reactor experiments, and concluding with two-dimensional energy-angle spectra in large-volume atmospheric experiments. It is shown that systematic uncertainties in the spectral shapes can noticeably affect the prospective sensitivities to unknown oscillation parameters, in particular to the mass hierarchy

The NMR added value to the Green Foodomics perspective: advances by machine learning to the holistic view on food and nutrition

Food is a complex matter, literally. From production to functionalization, from nutritional quality engineering to predicting effects on health, the interest in finding an efficient physicochemical characterization of food has boomed in recent years. The sheer complexity of characterizing food and its interaction with the human organism has however made the use of data driven approaches in modelling a necessity. High-throughput techniques, such as Nuclear Magnetic Resonance (NMR) spectroscopy, are well suited for omics data production and, coupled with machine learning, are paving a promising way of modelling food-human interaction. The foodomics approach sets the framework for omic data integration in food studies, in which NMR experiments play a key role. NMR data can be used to assess nutritional qualities of food, helping the design of functional and sustainable sources of nutrients, detect biomarkers of intake and study how they impact the metabolism of different individuals, study the kinetics of compounds in foods or their by-products to detect pathological conditions and improve the efficiency of in-silico models of the metabolic network