Centelles Chulia, S., Cepedello, R., Peinado, E., & Srivastava, R. (2020). Scotogenic dark symmetry as a residual subgroup of Standard Model symmetries. Chin. Phys. C, 44(8), 083110–7pp.
Abstract: We demonstrate that a scotogenic dark symmetry can be obtained as a residual subgroup of the global U(1)(B-L) symmetry already present in the Standard Model. In addition, we propose a general framework in which the U(1)(B-L) symmetry is spontaneously broken into an even Z(2n) subgroup, setting the general conditions for neutrinos to be Majorana and for dark matter stability to exist in terms of the residual Z(2n). As an example, under this general framework, we build a class of simple models where, in a scotogenic manner, the dark matter candidate is the lightest particle running inside the mass loop of a neutrino. The global U(1)(B-L) symmetry in our framework, being anomaly free, can also be gauged in a straightforward manner leading to a richer phenomenology.
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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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Archidiacono, M., Gariazzo, S., Giunti, C., Hannestad, S., & Tram, T. (2020). Sterile neutrino self-interactions: H-0 tension and short-baseline anomalies. J. Cosmol. Astropart. Phys., 12(12), 029–20pp.
Abstract: Sterile neutrinos with a mass in the eV range have been invoked as a possible explanation of a variety of short baseline (SBL) neutrino oscillation anomalies. However, if one considers neutrino oscillations between active and sterile neutrinos, such neutrinos would have been fully thermalised in the early universe, and would be therefore in strong conflict with cosmological bounds. In this study we first update cosmological bounds on the mass and energy density of eV-scale sterile neutrinos. We then perform an updated study of a previously proposed model in which the sterile neutrino couples to a new light pseudoscalar degree of freedom. Consistently with previous analyses, we find that the model provides a good fit to all cosmological data and allows the high value of H-0 measured in the local universe to be consistent with measurements of the cosmic microwave background. However, new high l polarisation data constrain the sterile neutrino mass to be less than approximately 1 eV in this scenario. Finally, we combine the cosmological bounds on the pseudoscalar model with a Bayesian inference analysis of SBL data and conclude that only a sterile mass in narrow ranges around 1 eV remains consistent with both cosmology and SBL data.
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ANTARES Collaboration(Albert, A. et al), Colomer, M., Gozzini, R., Hernandez-Rey, J. J., Illuminati, G., Khan-Chowdhury, N. R., et al. (2021). Monte Carlo simulations for the ANTARES underwater neutrino telescope. J. Cosmol. Astropart. Phys., 01(1), 064–20pp.
Abstract: Monte Carlo simulations are a unique tool to check the response of a detector and to monitor its performance. For a deep-sea neutrino telescope, the variability of the environmental conditions that can affect the behaviour of the data acquisition system must be considered, in addition to a reliable description of the active parts of the detector and of the features of physics events, in order to produce a realistic set of simulated events. In this paper, the software tools used to produce neutrino and cosmic ray signatures in the telescope and the strategy developed to represent the time evolution of the natural environment and of the detector efficiency are described.
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Al Kharusi, S. et al, & Colomer, M. (2021). SNEWS 2.0: a next-generation supernova early warning system for multi-messenger astronomy. New J. Phys., 23(3), 031201–34pp.
Abstract: The next core-collapse supernova in the Milky Way or its satellites will represent a once-in-a-generation opportunity to obtain detailed information about the explosion of a star and provide significant scientific insight for a variety of fields because of the extreme conditions found within. Supernovae in our galaxy are not only rare on a human timescale but also happen at unscheduled times, so it is crucial to be ready and use all available instruments to capture all possible information from the event. The first indication of a potential stellar explosion will be the arrival of a bright burst of neutrinos. Its observation by multiple detectors worldwide can provide an early warning for the subsequent electromagnetic fireworks, as well as signal to other detectors with significant backgrounds so they can store their recent data. The supernova early warning system (SNEWS) has been operating as a simple coincidence between neutrino experiments in automated mode since 2005. In the current era of multi-messenger astronomy there are new opportunities for SNEWS to optimize sensitivity to science from the next galactic supernova beyond the simple early alert. This document is the product of a workshop in June 2019 towards design of SNEWS 2.0, an upgraded SNEWS with enhanced capabilities exploiting the unique advantages of prompt neutrino detection to maximize the science gained from such a valuable event.
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