[Paper Review] Full Data Release of the Daya Bay Reactor Neutrino Experiment

Daya Bay collaboration, F. P. An+199 more|arXiv (Cornell University)|Nov 28, 2022

Neutrino Physics Research4 citations

TL;DR

This paper presents a high-precision measurement of reactor antineutrino oscillation using data from the Daya Bay experiment at kilometer-scale baselines, employing a Geant4-based simulation to model systematic uncertainties. The analysis yields ${\rm sin}^{2}2\theta_{13} = 0.0851 \pm 0.0024$ and $\Delta m^{2}_{ee} = (2.519 \pm 0.060) \times 10^{-3}\ \text{eV}^2$, representing a 2.8% precision on $\theta_{13}$, which remains the most precise measurement to date and supports the three-neutrino paradigm.

ABSTRACT

Full Data Release of the Daya Bay Reactor Neutrino Experiment Summary The repository contains the full Daya Bay data set of inverse-beta-decay (IBD) candidates (reactor electron antineutrino interactions) with the final-state neutron captured on gadolinium. The dataset and supplementary data are sufficient to reproduce the measurement of neutrino oscillation parameters sin²2θ₁₃ and Δm²₃₂, published in Phys.Rev.Lett. 130 (2023) 16, 161802. The Daya Bay Reactor Neutrino Experiment took data from 2011 to 2020 in China. It obtained a sample of 5.55 million IBD events with the final-state neutron captured on gadolinium (nGd). This sample was collected by eight identically designed antineutrino detectors (AD) observing antineutrino flux from six nuclear power plants located at baselines between 400 m and 2 km. It covers 3158 days of operation. Code is provided elsewhere to read the dataset and produce a measurement of sin²2θ₁₃ and Δm²₃₂, consistent with the publication. Citation statement If you use the dataset, cite the following sources: [1] Daya Bay Collaboration, “Full Data Release of the Daya Bay Reactor Neutrino Experiment”, v1.0.0. Zenodo, DOI:10.5281/zenodo.17587229; 2025. [2] F. P. An et al. (Daya Bay collaboration), “Precision Measurement of Reactor Antineutrino Oscillation at Kilometer-Scale Baselines by Daya Bay”, Phys. Rev. Lett. 130,161802 (2023), DOI: 10.1103/PhysRevLett.130.161802. The dataset organization The data is provided in four different formats and is split into two categories: 1. Full dataset: IBD events in eight ADs, daily livetimes, daily efficiencies, rates of accidental backgrounds, and all the necessary inputs, needed to perform a measurement of sin²2θ₁₃ and Δm²₃₂. The size of the dataset is approximately 200 MB for each format.2. Analysis dataset: all the necessary inputs, needed to perform a measurement of sin²2θ₁₃ and Δm²₃₂, including livetimes and efficiencies. The dataset includes IBD histograms for each data taking period. Its size is around 1 MB for each format. Each category is available in four different formats: hdf5, npz, root and tsv (plain text, compressed). The detailed information on the contents of the files and formats is provided in each archive. Data availability The main storage of the data is Zenodo. A few alternative storage locations are available, including: Full dataset and analysis dataset: Zenodo: https://doi.org/10.5281/zenodo.17587229 NHEPSDC: https://doi.org/DOI:10.12402/opendata/DYB/20251205202440 Analysis dataset: GitHub: https://github.com/dayabay-experiment/dayabay-data-official PYPI: https://pypi.org/project/dayabay-data-official If you host a copy of the dataset, it should be supplemented with the current description. Feedback and contacts It is advised to use discussions and issues of the GitHub dataset repository as a main channel to provide feedback or request additional details related to the dataset itself. If a personal contact is desired, please, contact Zeyuan Yu ([e-mail]) and Maxim Gonchar ([e-mail]). Analysis code A dedicated python module dayabay-model is provided, which is able to read analysis data in any of the formats and provide predicted IBD spectra for each AD, the χ² function, or a result of any intermediate calculation. The module also contains a few minimal examples on how to work with the model and extract data from it. At this moment the latest version of dayabay-model, consistent with the dataset, is v0.4.2. More comprehensive examples of the data analysis are available in dayabay-analysis repository. Commands to perform the oscillation fit to the full Daya Bay dataset is provided as well. The code above depends on a few other Python modules, developed to support the analysis. The dependencies are automatically resolved via pip when the model is installed. Acknowledgements The results published here are in whole or in part based on the data released as Open-Access by the Daya Bay Collaboration supported by the Ministry of Science and Technology of China, the U.S. Department of Energy, the Chinese Academy of Sciences, the CAS Center for Excellence in Particle Physics, the National Natural Science Foundation of China, the New Cornerstone Science Foundation, the Guangdong provincial government, the Shenzhen municipal government, the China General Nuclear Power Group, the Research Grants Council of the Hong Kong Special Administrative Region of China, the National Science and Technology Council and the Ministry of Education in Taiwan, the U.S. National Science Foundation, the Ministry of Education, Youth, and Sports of the Czech Republic, the Charles University Research Centre UNCE, and the Joint Institute of Nuclear Research in Dubna, Russia.

Motivation & Objective

• To achieve a high-precision determination of the reactor antineutrino mixing angle $\theta_{13}$ using data from the Daya Bay experiment.
• To measure the effective mass-squared difference $\Delta m^{2}_{ee}$ with improved precision, constraining the neutrino mass hierarchy.
• To validate the three-neutrino mixing paradigm by comparing results with muon neutrino and antineutrino disappearance measurements from other experiments.
• To reduce systematic uncertainties through a detailed Geant4-based simulation of detector response and background contributions.
• To provide a full data release of the Daya Bay experiment for future global analysis and cross-validation.

Proposed method

• The analysis uses prompt-energy spectra from three experimental halls (EH1, EH2, EH3) to extract antineutrino rates and oscillation patterns as a function of baseline and energy.
• A $\chi^{2}$-minimization fit is performed in the $\Delta m^{2}_{ee}$–$\sin^{2}2\theta_{13}$ parameter space, incorporating systematic uncertainties as nuisance parameters.
• Systematic uncertainties are modeled as pulls in a vector $\bm{\nu}$, with detector and background effects simulated using Geant4.
• The oscillation probability is evaluated using the standard three-neutrino formula, with $\Delta m^{2}_{32}$ derived from $\Delta m^{2}_{ee}$ under normal or inverted mass hierarchy assumptions.
• The best-fit values are determined by minimizing $\chi^{2}$, with confidence intervals derived from $\Delta\chi^{2}$ scans.
• Multiple fitting methods are applied, and results are cross-checked to ensure consistency within 0.2 standard deviations.

Experimental results

Research questions

• RQ1 What is the most precise measurement of the reactor antineutrino mixing angle $\theta_{13}$ at kilometer-scale baselines?
• RQ2 How well does the measured $\Delta m^{2}_{ee}$ value agree with the three-neutrino mixing framework and other experiments?
• RQ3 To what extent do the Daya Bay results support the three-neutrino paradigm when compared with muon neutrino and antineutrino disappearance measurements?
• RQ4 What is the precision of the $\Delta m^{2}_{ee}$ determination, and how does it constrain the neutrino mass hierarchy?
• RQ5 How do the systematic uncertainties from detector response and backgrounds affect the final oscillation parameter extraction?

Key findings

• The measured value of $\sin^{2}2\theta_{13} = 0.0851 \pm 0.0024$ represents a precision of 2.8%, the most accurate determination to date.
• The effective mass-squared difference is measured as $\Delta m^{2}_{ee} = (2.519 \pm 0.060) \times 10^{-3}\ \text{eV}^2$, with a precision of about 2.4%.
• The best-fit $\chi^{2}$ value is 559 for 517 degrees of freedom, indicating a good fit to the data.
• The measured antineutrino energy spectra in all three experimental halls show excellent agreement with the best-fit oscillation model.
• The results are consistent with previous Daya Bay measurements and with independent measurements from RENO, Double Chooz, T2K, NOvA, MINOS/MINOS+, IceCube, and SuperK.
• The agreement across different experiments strongly supports the validity of the three-neutrino mixing framework.