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Gariazzo, S., Giunti, C., Laveder, M., & Li, Y. F. (2018). Model-independent (nu)over-bar(e) short-baseline oscillations from reactor spectral ratios. Phys. Lett. B, 782, 13–21.
Abstract: We consider the ratio of the spectra measured in the DANSS neutrino experiment at 12.7 and 10.7 m from a nuclear reactor. These data give a new model-independent indication in favor of short-baseline (nu) over bar (e) oscillations which reinforce the model-independent indication found in the late 2016 in the NEOS experiment. The combined analysis of the NEOS and DANSS spectral ratios in the framework of 3+1 active-sterile neutrino mixing favor short-baseline (nu) over bar (e) oscillations with a statistical significance of 3.7 sigma. The two mixing parameters sin(2)2 nu ee and Delta m(41)(2) are constrained at 2 sigma a narrow-Delta m(41)(2) island at Delta m(41)(2) similar or equal to 1.3 eV(2), with sin(2)2 nu(ee)= 0.049 +/- 0.023(2 sigma). We discuss the implications of the model-independent NEOS+DANSS analysis for the reactor and Gallium anomalies. The NEOS+DANSS model-independent determination of short-baseline (nu) over bar (e) oscillations allows us to analyze the reactor rates without assumptions on the values of the main reactor antineutrino fluxes and the data of the Gallium source experiments with free detector efficiencies. The corrections to the reactor neutrino fluxes and the Gallium detector efficiencies are obtained from the fit of the data. In particular, we confirm the indication in favor of the need for a recalculation of the (235)Ureactor antineutrino flux found in previous studies assuming the absence of neutrino oscillations.
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Gariazzo, S., & Mena, O. (2019). Cosmology-marginalized approaches in Bayesian model comparison: The neutrino mass as a case study. Phys. Rev. D, 99(2), 021301–6pp.
Abstract: We propose here a novel method which singles out the a priori unavoidable dependence on the underlying cosmological model when extracting parameter constraints, providing robust limits which only depend on the considered dataset. Interestingly, when dealing with several possible cosmologies and interpreting the Bayesian preference in terms of the Gaussian statistical evidence, the preferred model is much less favored than when only two cases are compared. As a working example, we apply our approach to the cosmological neutrino mass bounds, which play a fundamental role not only in establishing the contribution of relic neutrinos to the dark matter of the Universe but also in the planning of future experimental searches of the neutrino character and of the neutrino mass ordering.
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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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Gariazzo, S. (2020). Constraining power of open likelihoods, made prior-independent. Eur. Phys. J. C, 80(6), 552–6pp.
Abstract: One of the most criticized features of Bayesian statistics is the fact that credible intervals, especially when open likelihoods are involved, may strongly depend on the prior shape and range. Many analyses involving open likelihoods are affected by the eternal dilemma of choosing between linear and logarithmic prior, and in particular in the latter case the situation is worsened by the dependence on the prior range under consideration. In this letter, we revive a simple method to obtain constraints that depend neither on the prior shape nor range and, using the tools of Bayesian model comparison, extend it to overcome the possible dependence of the bounds on the choice of free parameters in the numerical analysis. An application to the case of cosmological bounds on the sum of the neutrino masses is discussed as an example.
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Di Valentino, E., Gariazzo, S., & Mena, O. (2021). Most constraining cosmological neutrino mass bounds. Phys. Rev. D, 104(8), 083504–7pp.
Abstract: We present here up-to-date neutrino mass limits exploiting the most recent cosmological data sets. By making use of the cosmic microwave background temperature fluctuation and polarization measurements, supernovae Ia luminosity distances, baryon acoustic oscillation observations and determinations of the growth rate parameter, we are able to set the most constraining bound to date, Sigma m(v) < 0.09 eV at 95% C.L. This very tight limit is obtained without the assumption of any prior on the value of the Hubble constant and highly compromises the viability of the inverted mass ordering as the underlying neutrino mass pattern in nature. The results obtained here further strengthen the case for very large multitracer spectroscopic surveys as unique laboratories for cosmological relics, such as neutrinos: that would be the case of the Dark Energy Spectroscopic Instrument survey and of the Euclid mission.
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