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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2411.19469 |
| Etiquetas: |
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- This study investigates the intrinsic electric dipole moment (EDM) of the $τ$ lepton, which is an important quantity in the search for physics beyond the Standard Model (BSM). In preparation for future measurements at the Super Tau-Charm Facility (STCF), we employ Monte Carlo simulations of the $e^+e^- \rightarrow τ^+τ^-$ process and optimize the analysis methodology for EDM extraction. Machine learning techniques are implemented to efficiently identify signal events ($τ^\pm\rightarrowπ^\pmπ^0ν_τ$), which result in a significant improvement in signal-to-noise ratio. Our optimized event selection algorithm achieves $80.0\%$ signal purity with $6.3\%$ efficiency. We develop an analytical approach for $τ$ lepton momentum reconstruction and derive the squared spin density matrix along with optimal observables, which maximize the sensitivity to $d_τ$. The relationship between these observables and the EDM is established with the estimated sensitivity of $|d_τ| < 3.89\times 10^{-18}\,e\cdot\mathrm{cm}$ at a $68\%$ confidence level. These results provide a foundation for future experimental measurements of the $τ$ lepton EDM in STCF experiments.