Significant Excess of ElectronLike Events in the MiniBooNE Short-Baseline Neutrino Experiment

TL;DR

The MiniBooNE experiment observed a significant excess of electron-like events in neutrino and antineutrino modes, supporting potential physics beyond the standard three-neutrino model, consistent with previous LSND findings.

Contribution

This paper reports an increased dataset showing a persistent excess of electron-like events, suggesting possible new physics beyond the standard neutrino paradigm.

Findings

Observed a 4.7 sigma excess of events

Data consistent with LSND anomaly

Supports the possibility of sterile neutrinos

Abstract

The MiniBooNE experiment at Fermilab reports results from an analysis of $\nu_e$ appearance data from $12.84 \times 10^{20}$ protons on target in neutrino mode, an increase of approximately a factor of two over previously reported results. A $\nu_e$ charged-current quasielastic event excess of $381.2 \pm 85.2$ events ($4.5 \sigma$) is observed in the energy range $200<E_\nu^{QE}<1250$~MeV. Combining these data with the $\bar \nu_e$ appearance data from $11.27 \times 10^{20}$ protons on target in antineutrino mode, a total $\nu_e$ plus $\bar \nu_e$ charged-current quasielastic event excess of $460.5 \pm 99.0$ events ($4.7 \sigma$) is observed. If interpreted in a two-neutrino oscillation model, ${\nu}_{\mu} \rightarrow {\nu}_e$, the best oscillation fit to the excess has a probability of $21.1\%$, while the background-only fit has a $\chi^2$ probability of $6 \times 10^{-7}$ relative to the best fit. The MiniBooNE data are consistent in energy and magnitude with the excess of events reported by the Liquid Scintillator Neutrino Detector (LSND), and the significance of the combined LSND and MiniBooNE excesses is $6.0 \sigma$. A two-neutrino oscillation interpretation of the data would require at least four neutrino types and indicate physics beyond the three neutrino paradigm.Although the data are fit with a two-neutrino oscillation model, other models may provide better fits to the data.