Measurement of reactor neutrino oscillation with the first JUNO data

Abstract Neutrino oscillations (see refs. 1,2 and references therein), a quantum effect manifesting at macroscopic scales, are governed by lepton flavour mixing angles and neutrino mass-squared differences3 that are fundamental parameters of particle physics, representing phenomena beyond the Standard Model. Precision measurements of these parameters are essential for testing the completeness of the three-flavour framework, determining the mass ordering of neutrinos and probing possible new physics. The Jiangmen Underground Neutrino Observatory (JUNO)4 is a 20-ktonne liquid-scintillator detector located 52.5 km from multiple reactor cores, designed to resolve the interference pattern of reactor neutrinos with sub-percent precision5,6. Here we report, using the first 59.1 days of data collected since detector completion in August 2025, the first simultaneous high-precision determination of two neutrino oscillation parameters, \({\sin }^{2}{\theta }_{12}=0.3092\,\pm \,0.0087\) and \(\Delta {m}_{21}^{2}=(7.50\,\pm \,0.12)\times 1{0}^{-5}\,{\mathrm{eV}}^{2}\) for the normal mass ordering scenario, improving the precision by a factor of 1.6 relative to the combination of all previous measurements. These results advance the basic understanding of neutrinos, validate the design of the detector and indicate the readiness of JUNO for resolving the neutrino mass ordering with a larger dataset. The rapid achievement with a short exposure highlights the potential of JUNO to push the frontiers of precision neutrino physics and paves the way for its broad scientific programme. This is a preview of subscription content, access via your institution Access options Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription £17.99 / 30 days cancel any time Subscribe to this journal Receive 52 print issues and online access £199.00 per year only £3.83 per issue Buy this article - Purchase on SpringerLink - Instant access to the full article PDF. £ 29.95 Prices may be subject to local taxes which are calculated during checkout Data availability Raw experimental data from the JUNO detectors are not publicly accessible due to their complexity and volume. Source data for Figs. 3, 4, and Extended Data Fig. 2 are, however, provided. Furthermore, inquiries regarding the data and posteriors used in this result may be directed to the collaboration. Code availability The JUNO Collaboration develops and maintains the code used for the simulation of the experimental apparatus and statistical analysis of the raw data used in this result. This code is shared among the Collaboration, but because of the size and complexity of the codebases, it is not publicly distributed. Inquiries regarding the algorithms and methods used in this result may be directed to the Collaboration. References Kajita, T. Nobel lecture: discovery of atmospheric neutrino oscillations. Rev. Mod. Phys. 88, 030501 (2016). McDonald, A. B. Nobel lecture: the Sudbury Neutrino Observatory: observation of flavor change for solar neutrinos. Rev. Mod. Phys. 88, 030502 (2016). Navas, S. et al. Review of particle physics. Phys. Rev. D 110, 030001 (2024). JUNO Collaboration. JUNO physics and detector. Prog. Part. Nucl. Phys. 123, 103927 (2022). Abusleme, A. et al. Potential to identify neutrino mass ordering with reactor antineutrinos at JUNO. Chin. Phys. 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Unified approach to the classical statistical analysis of small signals. Phys. Rev. D 57, 3873–3889 (1998). Acknowledgements We acknowledge the continued cooperation and support of the China General Nuclear Power Group in the construction and operation of the JUNO experiment. We also recognize the computing resources provided by the Chinese Academy of Sciences, IN2P3, INFN and JINR, which are essential for data processing and analysis within the JUNO Collaboration. We acknowledge the financial and institutional support from the Chinese Academy of Sciences, the National Key R&D Program of China, the People’s Government of Guangdong Province, the Tsung–Dao Lee Institute of Shanghai Jiao Tong University, and the China Center of Advanced Science and Technology in China. We appreciate the contributions from the Institut National de Physique Nucléaire et de Physique des Particules (IN2P3) in France, the Istituto Nazionale di Fisica Nucleare (INFN) in Italy, the Fonds de la Recherche Scientifique (F.R.S.–FNRS) and the Institut Interuniversitaire des Sciences Nucléaires (IISN) in Belgium, and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) in Brazil. We also acknowledge the support of the Agencia Nacional de Investigación y Desarrollo (ANID) and the ANID–Millennium Science Initiative Program (ICN2019044) in Chile; the European Structural and Investment Funds, the Ministry of Education, Youth and Sports, and the Charles University Research Center in the Czech Republic; the Deutsche Forschungsgemeinschaft (DFG), the Helmholtz Association, and the Cluster of Excellence PRISMA+ in Germany; and the Joint Institute for Nuclear Research (JINR) and Lomonosov Moscow State University in Russia. We further thank the Slovak Research and Development Agency in the Slovak Republic, the National Science and Technology Council (NSCT) and MOE in Taiwan, China, the Program Management Unit for Human Resources and Institutional Development, Research and Innovation (PMU–B), Chulalongkorn University, and Suranaree University of Technology in Thailand, the Science and Technology Facilities Council (STFC) in the United Kingdom, and the University of California at Irvine and the National Science Foundation (NSF) in the United States. Author information Authors and Affiliations Consortia Contributions The JUNO detector was designed, constructed, commissioned and is being operated by the JUNO Collaboration. All aspects of the hardware and software developments, data taking, detector calibration, data processing, Monte Carlo simulation, as well as data analysis, were performed by JUNO members, who also discussed and approved scientific results. All authors reviewed and approved the final version of the paper. Ethics declarations Competing interests The authors declare no competing interests. Peer review Peer review information Nature thanks Antonio Marrone, Robert Svoboda, Patricia Vahle, Zoya Vallari and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. Additional information Extended data figures and tables Extended Data Fig. 1 Reactor neutrino oscillation at different baselines. Survival probability \({{\mathcal{P}}}_{ee}\) of 4 MeV reactor \({\overline{\nu }}_{e}\) vs. baseline. Red: slow solar oscillation (\(\Delta {m}_{21}^{2}\)); blue: total \({\mathcal{P}}ee\) including fast atmospheric oscillations (\(\Delta {m}_{31}^{2}\)). Experimental baselines: JUNO (orange, 52.5 km) near solar oscillation maximum, Daya Bay near/far (pink), KamLAND (green). Circle sizes scale with detector sizes. Extended Data Fig. 2 Energy scale non-linearity calibration. a, Scintillator non-linearity from γ calibration sources deployed at the detector’s center: single-γ sources (solid circle), multiple-γ sources (hollow rhombus), and the best-fit curve (red). b, Measured cosmogenic 12B β− spectrum (points) compared to prediction (purple line), with a best-fit 12N component (green dashed line)of 2.7% identified via its high-energy shoulder. c, Measured 11C β+ spectrum (points) and the best-fit model (green line). d, Non-linearity response model for electrons (blue), γ’s (red), and positrons (green). Extended Data Fig. 3 Spatial distribution of reactor neutrino candidates. Prompt-event counts versus reconstructed cubic radius (R3) are shown for the three vertex algorithms: OMILREC (blue), VTREP (green), and JVertex (orange). Horizontal bars indicate R3 bin widths; vertical dashed lines mark the FV boundary (16.5 m) and detector edge (17.7 m). The inset shows the uniform event density within the FV, with the dashed line indicating the mean count level. The rising counts beyond the FV are primarily due to accidental coincidences, with minor contributions from fast- and double-neutron backgrounds. Extended Data Fig. 4 Reactor neutrino candidates characteristics. a, Two-dimensional prompt-versus-delayed energies (with enlarged delayed energy window) showing the 214Bi-214Po cluster at Ed ~ 1 MeV and the IBD selection region (dashed red box). The inset shows the delayed-energy spectrum, featuring a clear neutron-capture peak at Ed ≃ 2.23 MeV (blue dashed line). b, Temporal correlation following an exponential decay with a fitted neutron-capture time of τ = 203.1 ± 7.7 μs. The deviation of the first point is due to the Δt > 5 μs cut and is therefore not included in the fit. c, Spatial separation Δd of the prompt and delayed vertices. Extended Data Fig. 5 9Li/8He background analysis. a, Measured 9Li/8He rates across muon visible energy, comparing data before and after the SPN veto. The residual 9Li/8He rates are shown prior to efficiency correction but after the application of all selection cuts. b, Spatial- and temporal-distribution of IBD candidates before the SPN cut shown relative to preceding SPN events. A clear cluster of 9Li/8He events is visible at the origin. The red box indicates the SPN veto criteria. Extended Data Fig. 6 Temporal distribution of reactor neutrinos. Rates of antineutrino candidates (after subtraction of the mean background rates), shown in one week time bins (black points with statistical error) are compared to the prediction (red line). Arrows indicate operations on the cores YJ1 and YJ4 of the Yangjiang nuclear power plants. The power plants reduced the power output due to the occurrence of Super Typhoon Ragasa on September 24th. Extended Data Fig. 7 Three analyses post-fit comparison. Post-fit pulls of selected nuisance parameters in the three independent JUNO analysis chains. From left to right, these parameters correspond to the detection efficiency, the double-neutron rate, the 9Li/8He rate, the geoneutrino rate, and the 214Bi-214Po rate. Coloured markers with vertical error bars show the best-fit shift and 1σ uncertainty of each parameter relative to its prior, (xfit − xprior)/σprior, for Analyses I–III, while the shaded band denotes the ± 1σ prefit range and the dashed line indicates zero pull. Supplementary information Supplementary Information (download PDF ) PDF of The JUNO Collaboration author list, and their affiliations. Rights and permissions About this article Cite this article The JUNO Collaboration. Measurement of reactor neutrino oscillation with the first JUNO data. Nature 654, 343–348 (2026). https://doi.org/10.1038/s41586-026-10538-z Received: Accepted: Published: Version of record: Issue date: DOI: https://doi.org/10.1038/s41586-026-10538-z