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arXiv · 2208.13503

Performance studies of jet flavor tagging and measurement of $R_b(R_c)$ using ParticleNet at CEPC

Libo Liao·Shudong Wang·Weimin Song·Zhaoling Zhang·Gang Li
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Abstract

Jet flavor tagging plays a crucial role in the measurement of relative partial decay widths of $Z$ boson, denoted as $R_b$($R_c$), which is considered as a fundamental test of the Standard Model and sensitive probe to new physics. In this study, a Deep Learning algorithm, ParticleNet, is employed to enhance the performance of jet flavor tagging. The combined efficiency and purity of $c$-tagging is improved by more than 50\% compared to the Circular Electron Positron Collider (CEPC) baseline software. In order to measure $R_b$($R_c$) with this new flavor tagging approach, we have adopted the double-tagging method. The precision of $R_b$($R_c$) is improved significantly, in particular to $R_c$, which has seen a reduction in statistical uncertainty by 40\%.

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Libo Liao, Shudong Wang, Weimin Song, Zhaoling Zhang, Gang Li. 2022-08-29. Performance studies of jet flavor tagging and measurement of $R_b(R_c)$ using ParticleNet at CEPC. https://doi.org/10.1142/s0217751x23501683

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