Abstract: According to the “Black Box” theorem the experimental confirmation of neutrinoless double beta decay (0 nu 2 beta) would imply that at least one of the neutrinos is a Majorana particle. However, a null 0 nu 2 beta signal cannot decide the nature of neutrinos, as it can be suppressed even for Majorana neutrinos. In this letter we argue that if the null 0 nu 2 beta decay signal is accompanied by a 0 nu 2 beta quadruple beta decay signal, then at least one neutrino should be a Dirac particle. This argument holds irrespective of the underlying processes leading to such decays.

Abstract: Active galaxies, especially blazars, are among the most promising extragalactic candidates for high-energy neutrino sources. To date, ANTARES searches included these objects and used GeV-TeV gamma-ray flux to select blazars. Here, a statistically complete blazar sample selected by their bright radio emission is used as the target for searches of origins of neutrinos collected by the ANTARES neutrino telescope over 13 yr of operation. The hypothesis of a neutrino-blazar directional correlation is tested by pair counting and a complementary likelihood-based approach. The resulting posttrial p-value is 3.0% (2.2 sigma in the two-sided convention). Additionally, a time-dependent analysis is performed to search for temporal clustering of neutrino candidates as a means of detecting neutrino flares in blazars. None of the investigated sources alone reaches a significant flare detection level. However, the presence of 18 sources with a pretrial significance above 3 sigma indicates a p = 1.4% (2.5 sigma in the two-sided convention) detection of a time-variable neutrino flux. An a posteriori investigation reveals an intriguing temporal coincidence of neutrino, radio, and gamma-ray flares of the J0242+1101 blazar at a p = 0.5% (2.9 sigma in the two-sided convention) level. Altogether, the results presented here suggest a possible connection of neutrino candidates detected by the ANTARES telescope with radio-bright blazars.

Abstract: Addressing the origin of the astrophysical neutrino flux observed by IceCube is of paramount importance. Gamma-Ray Bursts (GRBs) are among the few astrophysical sources capable of achieving the required energy to contribute to such neutrino flux through p gamma interactions. In this work, ANTARFS data have been used to search for upward going muon neutrinos in spatial and temporal coincidence with 784 GRBs occurred from 2007 to 2017. For each GRB, the expected neutrino flux has been calculated in the framework of the internal shock model and the impact of the lack of knowledge on the majority of source redshifts and on other intrinsic parameters of the emission mechanism has been quantified. It is found that the model parameters that set the radial distance where shock collisions occur have the largest impact on neutrino flux expectations. In particular, the bulk Lorentz factor of the source ejecta and the minimum variability time-scale are found to contribute significantly to the GRB-neutrino flux uncertainty. For the selected sources, ANTARES data have been analysed by maximizing the discovery probability of the stacking sample through an extended maximum-likelihood strategy. Since no neutrino event passed the quality cuts set by the optimization procedure, 90 per cent confidence level upper limits (with their uncertainty) on the total expected diffuse neutrino flux have been derived, according to the model. The GRB contribution to the observed diffuse astrophysical neutrino flux around 100 TeV is constrained to be less than 10 percent.

Abstract: After introducing a master formula for the Majorana neutrino mass matrix, we present a master parametrization for the Yukawa matrices automatically in agreement with neutrino oscillation data. This parametrization can be used for any model that induces Majorana neutrino masses. The application of the master parametrization is also illustrated in an example model, with special focus on its lepton flavor violating phenomenology.

Abstract: Aims. In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regression remains an area with room for improvement. We aim to design a network that can accurately estimate sources' features and their uncertainties from single-band image cutouts, given the approximated locations of the sources provided by the previously developed code AutoSourceID-Light (ASID-L) or other external catalogues. This work serves as a proof of concept, showing the potential of machine learning in estimating astronomical features when trained on meticulously crafted synthetic images and subsequently applied to real astronomical data.Methods. The algorithm presented here, AutoSourceID-FeatureExtractor (ASID-FE), uses single-band cutouts of 32x32 pixels around the localised sources to estimate flux, sub-pixel centre coordinates, and their uncertainties. ASID-FE employs a two-step mean variance estimation (TS-MVE) approach to first estimate the features and then their uncertainties without the need for additional information, for example the point spread function (PSF). For this proof of concept, we generated a synthetic dataset comprising only point sources directly derived from real images, ensuring a controlled yet authentic testing environment.Results. We show that ASID-FE, trained on synthetic images derived from the MeerLICHT telescope, can predict more accurate features with respect to similar codes such as SourceExtractor and that the two-step method can estimate well-calibrated uncertainties that are better behaved compared to similar methods that use deep ensembles of simple MVE networks. Finally, we evaluate the model on real images from the MeerLICHT telescope and the Zwicky Transient Facility (ZTF) to test its transfer learning abilities.