Skip to main content

Full Data Release of the Daya Bay Reactor Neutrino Experiment. Analysis dataset.

Project description

Full Data Release of the Daya Bay Reactor Neutrino Experiment

zenodo github pypi github-code pypi-code CC BY 4.0

Summary

The repository contains the full (analysis) 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 analysis dataset contains all the necessary inputs, needed to perform a measurement of sin²2θ₁₃ and Δm²₃₂. It 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 one of dedicated readme files: hdf5, npz, root, tsv.

Data availability

The main storage of the data is Zenodo. A few alternative storage locations are available, including:

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 (yuzy@ihep.ac.cn) and Maxim Gonchar (gonchar@jinr.ru).

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dayabay_data_official-1.0.1.tar.gz (5.3 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dayabay_data_official-1.0.1-py3-none-any.whl (5.5 MB view details)

Uploaded Python 3

File details

Details for the file dayabay_data_official-1.0.1.tar.gz.

File metadata

  • Download URL: dayabay_data_official-1.0.1.tar.gz
  • Upload date:
  • Size: 5.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.13

File hashes

Hashes for dayabay_data_official-1.0.1.tar.gz
Algorithm Hash digest
SHA256 3517eb9d6037402f2447a83d1d8e23e76af98ae8d1b00d37e341f92dccf220c6
MD5 9901690c09af6b46f6550be9724f05ad
BLAKE2b-256 342a3179d398606694c864efd70aad05f65347fea379b99bdd70ebef8a2cda79

See more details on using hashes here.

File details

Details for the file dayabay_data_official-1.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for dayabay_data_official-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4578d71a741041d7b729dc7cacaa0836efe852d8f407d222ff8916c190dcfadf
MD5 360c0ae3f0f643b8ca5c0a19baa24690
BLAKE2b-256 08ed3737fec345f00c4ffcb2dec3f69355b8cdb4eee135a1cd76db29b5d02753

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page