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Srivastava, R., Ternes, C. A., Tortola, M., & Valle, J. W. F. (2018). Zooming in on neutrino oscillations with DUNE. Phys. Rev. D, 97(9), 095025–11pp.
Abstract: We examine the capabilities of the DUNE experiment as a probe of the neutrino mixing paradigm. Taking the current status of neutrino oscillations and the design specifications of DUNE, we determine the experiment's potential to probe the structure of neutrino mixing and CP violation. We focus on the poorly determined parameters theta(23) and delta(cp) and consider both two and seven years of run. We take various benchmarks as our true values, such as the current preferred values of theta(23) and delta(cp), as well as several theory-motivated choices. We determine quantitatively DUNE's potential to perform a precision measurement of theta(23), as well as to test the CP violation hypothesis in a model-independent way. We find that, after running for seven years, DUNE will make a substantial step in the precise determination of these parameters, bringing to quantitative test the predictions of various theories of neutrino mixing.
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Ternes, C. A., Gariazzo, S., Hajjar, R., Mena, O., Sorel, M., & Tortola, M. (2019). Neutrino mass ordering at DUNE: An extra nu bonus. Phys. Rev. D, 100(9), 093004–10pp.
Abstract: We study the possibility of extracting the neutrino mass ordering at the future Deep Underground Neutrino Experiment using atmospheric neutrinos, which will be available before the muon neutrino beam starts being operational. The large statistics of the atmospheric muon neutrino and antineutrino samples at the far detector, together with the baselines of thousands of kilometers that these atmospheric (anti) neutrinos travel, provide ideal ingredients to extract the neutrino mass ordering via matter effects in the neutrino propagation through Earth. Crucially, muon capture by argon provides excellent charge tagging, allowing us to disentangle the neutrino and antineutrino signature. This is an important extra benefit of having a liquid argon time projection chamber as a far detector, that could render an similar to 3.5 sigma extraction of the mass ordering after approximately 7 yr of exposure.
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DUNE Collaboration(Abi, B. et al), Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., Fernandez Menendez, P., et al. (2020). Neutrino interaction classification with a convolutional neural network in the DUNE far detector. Phys. Rev. D, 102(9), 092003–20pp.
Abstract: The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure CP-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional neural network has been developed to provide highly efficient and pure selections of electron neutrino and muon neutrino charged-current interactions. The electron neutrino (antineutrino) selection efficiency peaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between 2-5 GeV. The muon neutrino (antineutrino) event selection is found to have a maximum efficiency of 96% (97%) and exceeds 90% (95%) efficiency for reconstructed neutrino energies above 2 GeV. When considering all electron neutrino and antineutrino interactions as signal, a selection purity of 90% is achieved. These event selections are critical to maximize the sensitivity of the experiment to CP-violating effects.
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De Romeri, V., Giunti, C., Stuttard, T., & Ternes, C. A. (2023). Neutrino oscillation bounds on quantum decoherence. J. High Energy Phys., 09(9), 097–24pp.
Abstract: We consider quantum-decoherence effects in neutrino oscillation data. Working in the open quantum system framework we adopt a phenomenological approach that allows to parameterize the energy dependence of the decoherence effects. We consider several phenomenological models. We analyze data from the reactor experiments RENO, Daya Bay and KamLAND and from the accelerator experiments NOvA, MINOS/MINOS+ and T2K. We obtain updated constraints on the decoherence parameters quantifying the strength of damping effects, which can be as low as Gamma ij less than or similar to 8 x 10-27 GeV at 90% confidence level in some cases. We also present sensitivities for the future facilities DUNE and JUNO.
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de Gouvea, A., De Romeri, V., & Ternes, C. A. (2020). Probing neutrino quantum decoherence at reactor experiments. J. High Energy Phys., 08(8), 049–17pp.
Abstract: We explore how well reactor antineutrino experiments can constrain or measure the loss of quantum coherence in neutrino oscillations. We assume that decoherence effects are encoded in the size of the neutrino wave-packet, sigma. We find that the current experiments Daya Bay and the Reactor Experiment for Neutrino Oscillation (RENO) already constrain sigma >1.0x10(-4) nm and estimate that future data from the Jiangmen Underground Neutrino Observatory (JUNO) would be sensitive to sigma <2.1x10(-3) nm. If the effects of loss of coherence are within the sensitivity of JUNO, we expect sigma to be measured with good precision. The discovery of nontrivial decoherence effects in JUNO would indicate that our understanding of the coherence of neutrino sources is, at least, incomplete.
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