Chianese, M., Fiorillo, D. F. G., Hajjar, R., Miele, G., & Saviano, N. (2021). Constraints on heavy decaying dark matter with current gamma-ray measurements. J. Cosmol. Astropart. Phys., 11(11), 035–13pp.
Abstract: Among the several strategies for indirect searches of dark matter, a very promising one is to look for the gamma-rays from decaying dark matter. Here we use the most up-to-date upper bounds on the gamma-ray flux from 10(5) to 10(11) GeV, obtained from CASA-MIA, KASCADE, KASCADE-Grande, Pierre Auger Observatory, Telescope Array and EAS-MSU. We obtain global limits on dark matter lifetime in the range of masses in m(DM) = [10(7)-10(15)] GeV. We provide the bounds for a set of decay channels chosen as representatives. The constraints derived here are new and cover a region of the parameter space not yet explored. We compare our results with the projected constraints from future neutrino telescopes, in order to quantify the improvement that will be obtained by the complementary high-energy neutrino searches.
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Bhattacharya, A., Esmaili, A., Palomares-Ruiz, S., & Sarcevic, I. (2017). Probing decaying heavy dark matter with the 4-year IceCube HESE data. J. Cosmol. Astropart. Phys., 07(7), 027–36pp.
Abstract: After the first four years of data taking, the IceCube neutrino telescope has observed 54 high-energy starting events (HESE) with deposited energies between 20TeV and 2PeV. The background from atmospheric muons and neutrinos is expected to be of about 20 events, all below 100TeV, thus pointing towards the astrophysical origin of about 8 events per year in that data set. However, their precise origin remains unknown. Here, we perform a detailed analysis of this event sample (considering simultaneously the energy, hemisphere and topology of the events) by assuming two contributions for the signal events: an isotropic power-law flux and a flux from decaying heavy dark matter. We fit the mass and lifetime of the dark matter and the normalization and spectral index of an isotropic power-law flux, for various decay channels of dark matter. We find that a significant contribution from dark matter decay is always slightly favored, either to explain the excess below 100TeV, as in the case of decays to quarks or, as in the case of neutrino channels, to explain the three multi-PeV events. Also, we consider the possibility to interpret all the data by dark matter decays only, considering various combinations of two decay channels. We show that the decaying dark matter scenario provides a better fit to HESE data than the isotropic power-law flux.
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Di Bari, P., Ludl, P. O., & Palomares-Ruiz, S. (2016). Unifying leptogenesis, dark matter and high-energy neutrinos with right-handed neutrino mixing via Higgs portal. J. Cosmol. Astropart. Phys., 11(11), 044–41pp.
Abstract: We revisit a model in which neutrino masses and mixing are described by a two right-handed (RH) neutrino seesaw scenario, implying a strictly hierarchical light neutrino spectrum. A third decoupled RH neutrino, N-DM with mass M-DM, plays the role of cold dark matter (DM) and is produced by the mixing with a source RH neutrino, Ns with mass M-S, induced by Higgs portal interactions. The same interactions are also responsible for N-DM decays. We discuss in detail the constraints coming from DM abundance and stability conditions showing that in the hierarchical case, for M-DM >> M-S, there is an allowed window on M-DM values necessarily implying a contribution, from DM decays, to the high-energy neutrino flux recently detected by IceCube. We also show how the model can explain the matter-antimatter asymmetry of the Universe via leptogenesis in the quasi-degenerate limit. In this case, the DM mass should be within the range 300 GeV less than or similar to M-S < M-DM < 10PeV. We discuss the specific properties of this high-energy neutrino flux and show the predicted event spectrum for two exemplary cases. Although DM decays, with a relatively hard spectrum, cannot account for all the IceCube high-energy data, we illustrate how this extra source of high-energy neutrinos could reasonably explain some potential features in the observed spectrum. In this way, this represents a unified scenario for leptogenesis and DM that could be tested during the next years with more high-energy neutrino events.
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ANTARES Collaboration(Albert, A. et al), Alves, S., Calvo, D., Carretero, V., Gozzini, R., Hernandez-Rey, J. J., et al. (2022). Search for secluded dark matter towards the Galactic Centre with the ANTARES neutrino telescope. J. Cosmol. Astropart. Phys., 06(6), 028–20pp.
Abstract: Searches for dark matter (DM) have not provided any solid evidence for the existence of weakly interacting massive particles in the GeV-TeV mass range. Coincidentally, the scale of new physics is being pushed by collider searches well beyond the TeV domain. This situation strongly motivates the exploration of DM masses much larger than a TeV. Secluded scenarios contain a natural way around the unitarity bound on the DM mass, via the early matter domination induced by the mediator of its interactions with the Standard Model. High-energy neutrinos constitute one of the very few direct accesses to energy scales above a few TeV. An indirect search for secluded DM signals has been performed with the ANTARES neutrino telescope using data from 2007 to 2015. Upper limits on the DM annihilation cross section for DM masses up to 6 PeV are presented and discussed.
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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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