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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Miranda, O. G., Pasquini, P., Tortola, M., & Valle, J. W. F. (2018). Exploring the potential of short-baseline physics at Fermilab. Phys. Rev. D, 97(9), 095026–9pp.
Abstract: We study the capabilities of the short-baseline neutrino program at Fermilab to probe the unitarity of the lepton mixing matrix. We find the sensitivity to be slightly better than the current one. Motivated by the future DUNE experiment, we have also analyzed the potential of an extra liquid Argon near detector in the LBNF beamline. Adding such a near detector to the DUNE setup will substantially improve the current sensitivity on nonunitarity. This would help to remove CP degeneracies due to the new complex phase present in the neutrino mixing matrix. We also study the sensitivity of our proposed setup to light sterile neutrinos for various configurations.
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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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Terol-Calvo, J., Tortola, M., & Vicente, A. (2020). High-energy constraints from low-energy neutrino nonstandard interactions. Phys. Rev. D, 101(9), 095010–14pp.
Abstract: Many scenarios of new physics predict the existence of neutrino nonstandard interactions, new vector contact interactions between neutrinos, and first generation fermions beyond the Standard Model. We obtain model-independent constraints on the Standard Model effective field theory at high energies from bounds on neutrino nonstandard interactions derived at low energies. Our analysis explores a large set of new physics scenarios and includes full one-loop running effects below and above the electroweak scale. Our results show that neutrino nonstandard interactions already push the scale of new physics beyond the TeV. We also conclude that bounds derived by other experimental probes, in particular by low-energy precision measurements and by charged lepton flavor violation searches, are generally more stringent. Our study constitutes a first step toward the systematization of phenomenological analyses to evaluate the impact of neutrino nonstandard interactions for new physics scenarios at high energies.
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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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