Single-Inclusive Hadron Production in Electron-Positron Annihilation at Next-to-Next-to-Next-to-Leading Order in QCD
Single-inclusive hadron production in electron-positron annihilation (SIA) represents the cleanest process for investigating the dynamics of parton hadronization, as encapsulated in parton fragmentation functions. In this Letter, we present, for the first time, the analytical computation of quantum chromodynamics corrections to the coefficient functions for SIA at next-to-next-to-next-to-leading order (N^{3}LO) accuracy, achieving the highest precision to date for hadron production processes. Utilizing the BABAR measurement as a benchmark, we assess the phenomenological implications of this high-precision calculation. Our findings demonstrate a substantial reduction in scale uncertainties at N^{3}LO and offer an improved description of the experimental data compared to lower-order calculations. This advancement underscores the importance of higher-order corrections in achieving a more accurate understanding of hadronization processes.
Authors
- Hongxi Xing (ORCID: https://orcid.org/0000-0003-3503-7084)
- Chuan-Qi He (ORCID: https://orcid.org/0009-0004-0737-6518)
- Tong-Zhi Yang (ORCID: https://orcid.org/0000-0001-5003-5517)
- Hua Xing Zhu
Institutions
- Rosatom (Russia) (RU)
- South China Normal University (CN)
- Chinese Academy of Sciences (CN)
- Peking University (CN)
- University of Zurich (CH)
- Key Laboratory of Guangdong Province (CN)
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality (CN)
- Institute of Modern Physics (CN)
Publication Details
- Journal
- Physical Review Letters
- Published
- 2025-09-02
- DOI
- https://doi.org/10.1103/vtz2-6bnm
- Citations
- 6
- Primary Topic
- Particle physics theoretical and experimental studies
- Type
- article
- Field-Weighted Citation Impact
- 11.22
Funders
- National Science Foundation
- European Commission
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- National Natural Science Foundation of China
- Horizon 2020 Framework Programme
- European Research Council