量子机器学习在高能物理数据处理中的应用研究
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Online
PKU Indico cross-reference:
https://indico.ihep.ac.cn/event/19501/
Join Zoom Meeting:
https://cern.zoom.us/j/64765907368?pwd=VFNMc3ZuY1I3bTdtcTE2SXJuZy9MZz09
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Abstract:
Quantum machine learning, as a interdiscipline between quantum computing and machine learning, is relatively new to the high energy physics domain. The quantum machine learning provides a brand new set of options for machine learning algorithms. In some cases they could serve as a valuable alternative, and potentially provides quantum advantage for traditional machine learning models. This talk focuses on our recent studies regarding the applications of quantum machine learning to high energy physics experiments, including particle identification, image processing as well as data analysis.
Resume:
李腾，2017年博士毕业于山东大学物理学院，2017至2020年于爱丁堡大学从事博士后研究工作，2020年起受聘于山东大学前沿交叉科学青岛研究院，任副研究员。李腾的主要研究方向为粒子物理实验数据处理软件开发，以及并行、异构计算和机器学习等新兴技术在粒子物理实验中的应用等，曾参与包括BESIII、JUNO和LHASSO等多个实验的离线软件开发工作，目前是STCF和HERD实验核心软件框架负责人。
