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MicroBooNE and the electron-neutrino Interpretation of the MiniBooNE Low-Energy Excess

Authors: Soler, Ivan Martinez;

MicroBooNE and the electron-neutrino Interpretation of the MiniBooNE Low-Energy Excess

Abstract

The existence of an eV sterile neutrino has been motivated by the LSND results and, more recently by the Low-Energy Excess (LEE) observed in MiniBooNE. This new fermion would profoundly impact particle physics, astrophysics, and cosmology. A new generation of experiments is looking for it. The latest results from MicroBooNE appear to disfavor the interpretation of the LEE just in terms of flavor oscillation. This outcome is based on the non-observation of an electron-neutrino event excess in MicroBooNE compatible with LEE. Following the same procedure, we explore the impact that MiniBooNE's uncertainties on the LEE might have on excluding the excess by MicroBooNE. Our results indicate that many excess templates are still compatible with MiniBooNE results, but MicroBooNE cannot exclude them with a large significance. Finally, we perform a complete four-neutrino analysis of the data released, including the energy resolution and the covariance matrix. We explore the sensitivity in the Inclusive and the CCQE channels. Although the present data allow the exploration of a fraction of the allowed parameter space, it is not completely covered, and therefore the scenario cannot be excluded.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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