Abstract This study investigates the intrinsic electric dipole moment (EDM) of the lepton, 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^- ^+^- process and optimize the analysis methodology for EDM extraction. Machine learning techniques are implemented to efficiently identify signal events (^^⁰_), resulting 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 lepton momentum reconstruction and derive the squared spin density matrix along with optimal observables, which maximize the sensitivity to d_. The relationship between these observables and the EDM is established, with the estimated sensitivity of |d_| < 3. 89 10^-18\, e at 68\% confidence level. These results provide a foundation for future experimental measurements of the lepton EDM in STCF experiments. Content from this work may be used under the terms of the Creative Commons Attribution 3. 0 licence. Any further distribution of this work must maintain attribution to the author (s) and the title of the work, journal citation and DOI. Article funded by SCOAP3 and published under licence by Chinese Physical Society and the Institute of High Energy Physics of the Chinese Academy of Science and the Institute of Modern Physics of the Chinese Academy of Sciences and IOP Publishing Ltd.
Sun et al. (Sat,) studied this question.
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