DUNE Collaboration(Abi, B. et al), Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., Fernandez Menendez, P., et al. (2021). Searching for solar KDAR with DUNE. J. Cosmol. Astropart. Phys., 10(10), 065–28pp.
Abstract: The observation of 236 MeV muon neutrinos from kaon-decay-at-rest (KDAR) originating in the core of the Sun would provide a unique signature of dark matter annihilation. Since excellent angle and energy reconstruction are necessary to detect this monoenergetic, directional neutrino flux, DUNE with its vast volume and reconstruction capabilities, is a promising candidate for a KDAR neutrino search. In this work, we evaluate the proposed KDAR neutrino search strategies by realistically modeling both neutrino-nucleus interactions and the response of DUNE. We find that, although reconstruction of the neutrino energy and direction is difficult with current techniques in the relevant energy range, the superb energy resolution, angular resolution, and particle identification offered by DUNE can still permit great signal/background discrimination. Moreover, there are non-standard scenarios in which searches at DUNE for KDAR in the Sun can probe dark matter interactions.
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Centelles Chulia, S., Srivastava, R., & Valle, J. W. F. (2018). Seesaw Dirac neutrino mass through dimension-six operators. Phys. Rev. D, 98(3), 035009–18pp.
Abstract: In this paper, a follow-up of [S. C. Chulia, R. Srivastava, and J. W. F. Valle, Phys. Lett. B 781, 122 (2018)], we describe the many pathways to generate Dirac neutrino mass through dimension-six operators. By using only the standard model Higgs doublet in the external legs, one gets a unique operator 1/Lambda(2) (L) over bar (Phi) over bar (Phi) over bar Phi nu(R). In contrast, the presence of new scalars implies new possible field contractions, which greatly increase the number of possibilities. Here, we study in detail the simplest ones, involving SU(2)(L) singlets, doublets, and triplets. The extra symmetries needed to ensure the Dirac nature of neutrinos can also be responsible for stabilizing dark matter.
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Centelles Chulia, S., Srivastava, R., & Valle, J. W. F. (2018). Seesaw roadmap to neutrino mass and dark matter. Phys. Lett. B, 781, 122–128.
Abstract: We describe the many pathways to generate Majorana and Dirac neutrino mass through generalized dimension-5 operators a la Weinberg. The presence of new scalars beyond the Standard Model Higgs doublet implies new possible field contractions, which are required in the case of Dirac neutrinos. We also notice that, in the Dirac neutrino case, the extra symmetries needed to ensure the Dirac nature of neutrinos can also be made responsible for stability of dark matter.
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Kosmas, T. S., Miranda, O. G., Papoulias, D. K., Tortola, M., & Valle, J. W. F. (2015). Sensitivities to neutrino electromagnetic properties at the TEXONO experiment. Phys. Lett. B, 750, 459–465.
Abstract: The possibility of measuring neutral-current coherent elastic neutrino nucleus scattering (CENNS) at the TEXONO experiment has opened high expectations towards probing exotic neutrino properties. Focusing on low threshold Germanium-based targets with kg-scale mass, we find a remarkable efficiency not only for detecting CENNS events due to the weak interaction, but also for probing novel electromagnetic neutrino interactions. Specifically, we demonstrate that such experiments are complementary in performing precision Standard Model tests as well as in shedding light on sub-leading effects due to neutrino magnetic moment and neutrino charge radius. This work employs realistic nuclear structure calculations based on the quasi-particle random phase approximation (QRPA) and takes into consideration the crucial quenching effect corrections. Such a treatment, in conjunction with a simple statistical analysis, shows that the attainable sensitivities are improved by one order of magnitude as compared to previous studies.
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DUNE Collaboration(Abud, A. A. et al), Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., Fernandez Menendez, P., et al. (2022). Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network. Eur. Phys. J. C, 82(10), 903–19pp.
Abstract: Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation.
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