One-to-one correspondence reconstruction at the electron-positron Higgs factory
Yuexin Wang, Hao Liang, Yongfeng Zhu, Yuzhi Che, Xin Xia, Huilin Qu, Chen Zhou, Xuai Zhuang, Manqi Ruan

TL;DR
This paper introduces a novel one-to-one correspondence reconstruction method for electron-positron Higgs factories, utilizing advanced detector technology and AI to improve particle identification and Higgs decay measurements.
Contribution
It presents a new detector concept with 5D calorimetry and a reconstruction framework combining particle flow and AI, achieving high accuracy in particle mapping and identification.
Findings
Over 90% of visible energy mapped into well-reconstructed particles
Invariant mass resolution of Higgs improved by 25%
Charged particle and photon identification efficiencies exceed 97%
Abstract
We propose one-to-one correspondence reconstruction for electron-positron Higgs factories. For each visible particle, one-to-one correspondence aims to associate relevant detector hits with only one reconstructed particle and accurately identify its species. To achieve this goal, we develop a novel detector concept featuring 5-dimensional calorimetry that provides spatial, energy, and time measurements for each hit, and a reconstruction framework that combines state-of-the-art particle flow and artificial intelligence algorithms. In the benchmark process of Higgs to di-jets, over 90% of visible energy can be successfully mapped into well-reconstructed particles that not only maintain a one-to-one correspondence relationship but also associate with the correct combination of cluster and track, improving the invariant mass resolution of hadronically decayed Higgs bosons by 25%. Performing…
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Taxonomy
TopicsMuon and positron interactions and applications · Particle Detector Development and Performance · Particle physics theoretical and experimental studies
