Precision measurement of neutrino oscillation parameters with 10 years of data from the NOvA experiment

Abstract

This Letter reports measurements of muon-neutrino disappearance and electron-neutrino appearance and the corresponding antineutrino processes between the two NOvA detectors in the NuMI neutrino beam. These measurements use a dataset with double the neutrino mode beam exposure that was previously analyzed, along with improved simulation and analysis techniques. A joint fit to these samples in the three-flavor paradigm results in the most precise single-experiment constraint on the atmospheric neutrino mass splitting, $Δm^2_{32}= 2.431^{+0.036}_{-0.034} (-2.479^{+0.036}_{-0.036}) \times 10^{-3}~\mathrm{eV}^2$ if the mass ordering is normal (inverted). In both orderings, a region close to maximal mixing with $\sin^2 θ_{23}=0.55^{+0.02}_{-0.06}$ is preferred. The NOvA data show a mild preference for the normal mass ordering with a Bayes factor of 2.4 (corresponding to 70% of the posterior probability), indicating that the normal ordering is 2.4 times more probable than the inverted ordering. When incorporating a 2D $Δm^2_{32}\text{--}\sin^2 2θ_{13}$ constraint based on Daya Bay data, this preference strengthens to a Bayes factor of 6.6 (87%).

Figures (17)

• Figure 1: Observed and predicted energy spectra, for $\nu_\mu$ CC selected events in the ND (a) and FD (b), and for $\nu_e$ CC selected events in the FD (c). In the $\nu_\mu$ spectra all subsamples have been combined, while in the $\nu_{e}$ spectra the four selections (Low-energy, low PID, high PID and peripheral) are shown separated. The best-fit prediction is extracted from the frequentist fit to the data with the Daya Bay 1D constraint on $\sin^2{2\theta_{13}}$DayaBay:2022orm. The predicted FD spectra have smaller systematic errors than the ND spectrum as a result of the extrapolation procedure. The corresponding antineutrino spectra and quartile-separated samples are shown in the supplemental material supplemental.
• Figure 2: Comparisons of the 90% intervals for $\Delta m^2_{32}$ -- $\sin^2\theta_{23}$ in the normal MO with NOvA 2020 results and superimposed contours from other experiments T2K:2024wfnIceCube:2024xjjt2k_collaboration_2022_6908532MINOS:2020llmSuper-Kamiokande:2023ahc, including the 2024 joint NOvA-T2K analysis novat2k_nature2025.The NOvA results are with the 1D Daya Bay constraint on $\theta_{13}$ applied DayaBay:2022orm. Contours labeled B are from Bayesian analyses, while those labeled F are from frequentist analyses, used when Bayesian results were not available.
• Figure 3: Bi-event plot showing the posterior probability for the predicted number of $\nu_e$ and $\bar{\nu}_e$ events in purple, with the 1 $\sigma$ credible interval and the FD data point marked. The two ovals, red for the inverted MO and blue for the normal MO, show the prediction with all the parameters fixed at the NOvA best-fit, varying only $\delta_{\textrm{CP}}$, with four $\delta_{\textrm{CP}}$ points marked.
• Figure 4: A comparison of the NOvA and Daya Bay constraints in the $\sin^2 2 \theta_{13}$ -- $\Delta m^2_{32}\xspace$ plane under the assumption of normal (top) or inverted (bottom) MO. The 2D binned NOvA posterior shown in color in the left panels is without any external constraints on $\theta_{13}$. Panels on the right illustrate the effect of applying a 2D $\sin^2\theta_{13}\textrm{--}\Delta m^2_{32}$ constraint from Daya Bay DayaBay:2022orm on the MO preference.
• Figure S1: Observed and predicted energy spectra, for $\bar{\nu}_\mu$ CC selected events in the ND (left) and FD (middle), and for $\bar{\nu}_e$ CC selected events in the FD (right). In the $\bar{\nu}_\mu$ spectra all hadronic energy fraction quartiles and transverse momentum quantiles have been combined, while in the $\bar{\nu}_e$ spectra the three selections (low PID, high PID, and peripheral) are shown separated. The best-fit prediction is extracted from a frequentist fit to the data (best-fit values in Table \ref{['table_freq_BF']}) with the Daya Bay 1D constraint on $\sin^2 2\theta_{13}$DayaBay:2022orm.