Open Access
Issue
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
Article Number 01290
Number of page(s) 8
DOI https://doi.org/10.1051/epjconf/202533701290
Published online 07 October 2025
  1. G. Abbiendi et al., Letter of Intent: the MUonE project (CERN, Geneva, 2019). CERN-SPSC-2019-026, SPSC-I-252. https://cds.cern.ch/record/2677471 [Google Scholar]
  2. G. Abbiendi et al., Measuring the leading hadronic contribution to the muon g-2 via µe scattering. Eur. Phys. J. C 77, 139 (2017). https://doi.org/10.1140/epjc/s10052-017-4633-z [Google Scholar]
  3. G. Hall et al., Proposal for phase 1 of the MUonE experiment (CERN, Geneva, 2024). CERN-SPSC-2024-015, SPSC-P-370. https://cds.cern.ch/record/2896293 [Google Scholar]
  4. R. N. Pilato, Feasibility study of the MUonE experiment (University of Pisa, 2023) 149 [Google Scholar]
  5. G. Ballerini et al., A feasibility test run for the MUonE project. Nucl. Instrum. Methods Phys. Res. A 936, 636–637 (2019). https://doi.org/10.1016/j.nima.2018.10.148 [Google Scholar]
  6. D. P. Aguillard et al., Measurement of the Positive Muon Anomalous Magnetic Moment to 0.20 ppm. Phys. Rev. Lett. 131, 161802 (2023). https://doi.org/10.1103/PhysRevLett. 131.161802 [CrossRef] [PubMed] [Google Scholar]
  7. M. Della Morte et al., The hadronic vacuum polarization contribution to the muon g 2 from lattice QCD. J. High Energy Phys. 2017, 020 (2017). https://doi.org/10.1007/JHEP10(2017)020 [Google Scholar]
  8. N. Doble, L. Gatignon, G. von Holtey, F. Novoskoltsev, The upgraded muon beam at the SPS. Nucl. Instrum. Methods Phys. Res. A 343(2), 351-362 (1994). https://doi.org/10.1016/0168-9002(94)90212-7 [Google Scholar]
  9. CMS Collaboration, The Phase-2 Upgrade of the CMS Outer Tracker. Nucl. Instrum. Methods Phys. Res. A 979, 164432 (2020). https://doi.org/10.1016/j.nima.2020.164432 [Google Scholar]
  10. M. Al-Turany et al., Extending the FairRoot framework to allow for simulation and reconstruction of free streaming data. J. Phys.: Conf. Ser. 513, 022001 (2014). https://doi. org/10.1088/1742-6596/513/2/022001 [Google Scholar]
  11. S. Agostinelli et al., Geant4—a simulation toolkit. Nucl. Instrum. Methods Phys. Res. A 506, 250–303 (2003). https://doi.org/10.1016/S0168-9002(03)01368-8 [CrossRef] [Google Scholar]
  12. M. Alacevich et al., Muon-electron scattering at NLO. J. High Energy Phys. 2019, 155 (2019). https://doi.org/10.1007/JHEP02(2019)155 [Google Scholar]
  13. C. R. Qi et al., PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space. arXiv preprint (2017). https://doi.org/10.48550/arXiv.1706.02413 [Google Scholar]
  14. M. Yeung et al., Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation. Comput. Med. Imaging Graph. 95, 102026 (2022). https://doi.org/10.1016/j.compmedimag.2021.102026 [Google Scholar]
  15. D. P. Kingma, and J. Ba, Adam: A Method for Stochastic Optimization. arXiv preprint arXiv:1412.6980 (2017). https://arxiv.org/abs/1412.6980 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.