Sandner, S., Hernandez, P., Lopez-Pavon, J., & Rius, N. (2023). Predicting the baryon asymmetry with degenerate right-handed neutrinos. J. High Energy Phys., 11(11), 153–37pp.
Abstract: We consider the generation of a baryon asymmetry in an extension of the Standard Model with two singlet Majorana fermions that are degenerate above the electroweak phase transition. The model can explain neutrino masses as well as the observed matter-antimatter asymmetry, for masses of the heavy singlets below the electroweak scale. The only physical CP violating phases in the model are those in the PMNS mixing matrix, i.e. the Dirac phase and a Majorana phase that enter light neutrino observables. We present an accurate analytic approximation for the baryon asymmetry in terms of CP flavour invariants, and derive the correlations with neutrino observables. We demonstrate that the measurement of CP violation in neutrino oscillations as well as the mixings of the heavy neutral leptons with the electron, muon and tau flavours suffice to pin down the matter-antimatter asymmetry from laboratory measurements.
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Lineros, R. A., & Pereira dos Santos, F. A. (2014). Inert scalar dark matter in an extra dimension inspired model. J. Cosmol. Astropart. Phys., 10(10), 059–17pp.
Abstract: In this paper we analyze a dark matter model inspired by theories with extra dimensions. The dark matter candidate corresponds to the first Kaluza-Klein mode of an real scalar added to the Standard Model. The tower of new particles enriches the calculation of the relic abundance. For large mass splitting, the model converges to the predictions of the inert singlet dark matter model. For nearly degenerate mass spectrum, coannihilations increase the cross-sections used for direct and indirect dark matter searches. Moreover, the Kaluza-Klein zero mode can mix with the SM higgs and further constraints can be applied.
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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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Super-Kamiokande Collaboration(Abe, K. et al), & Molina Sedgwick, S. (2022). Neutron tagging following atmospheric neutrino events in a water Cherenkov detector. J. Instrum., 17(10), P10029–41pp.
Abstract: We present the development of neutron-tagging techniques in Super-Kamiokande IV using a neural network analysis. The detection efficiency of neutron capture on hydrogen is estimated to be 26%, with a mis-tag rate of 0.016 per neutrino event. The uncertainty of the tagging efficiency is estimated to be 9.0%. Measurement of the tagging efficiency with data from an Americium-Beryllium calibration agrees with this value within 10%. The tagging procedure was performed on 3,244.4 days of SK-IV atmospheric neutrino data, identifying 18,091 neutrons in 26,473 neutrino events. The fitted neutron capture lifetime was measured as 218 +/- 9 μs.
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ANTARES Collaboration(Adrian-Martinez, S. et al), Aguilar, J. A., Bigongiari, C., Dornic, D., Emanuele, U., Gomez-Gonzalez, J. P., et al. (2011). First Search For Point Sources Of High-Energy Cosmic Neutrinos With The Antares Neutrino Telescope. Astrophys. J. Lett., 743(1), L14–6pp.
Abstract: Results are presented of a search for cosmic sources of high-energy neutrinos with the ANTARES neutrino telescope. The data were collected during 2007 and 2008 using detector configurations containing between 5 and 12 detection lines. The integrated live time of the analyzed data is 304 days. Muon tracks are reconstructed using a likelihood-based algorithm. Studies of the detector timing indicate a median angular resolution of 0.5 +/- 0.1 deg. The neutrino flux sensitivity is 7.5 x 10(-8)(E(v)/GeV)(-2) GeV(-1) s(-1) cm(-2) for the part of the sky that is always visible (delta < -48 deg), which is better than limits obtained by previous experiments. No cosmic neutrino sources have been observed.
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