学术报告
学术报告
Learning Physics at Future e-e+ Colliders with Machine
admin 230 阅读 2020-11-11

报告人:Prof. Tao Liu ,Hong Kong University of Science and Technology

开始日期:2020-05-07

开始时间:2020-05-07 16:00~17:00

活动地点:在线

活动介绍
Abstract

Information deformation and loss in jet clustering are one of the major limitations for precisely measuring hadronic events at future e−e+ colliders. Because of their dominance in data, the measurements of such events are crucial for advancing the precision frontier of Higgs and electroweak physics in the next decades. In a recent arXiv paper (https://arxiv.org/pdf/2004.15013.pdf), the speaker and his collaborators showed that this difficulty can be well-addressed by synergizing the event-level information into the data analysis, with the techniques of deep neutral network. In relation to that, they introduced a CMB-like observable scheme, where the event-level kinematics is encoded as the Fox-Wolfram (FW) moments at leading order and multi-spectra at higher orders. Then they developed a series of jet-level (w/ and w/o the FW moments) and event-level classifiers, and analyze their sensitivity performance comparatively with two-jet and four-jet events. As an application, they analyzed measuring Higgs decay width at e−e+ colliders with the data of 5ab−1@240GeV. The precision obtained is significantly better than the baseline ones presented in documents. In this talk, the speaker will give an overview on these aspects and discuss their potential impacts for future collider-physics study.   

Biography

Liu's research mainly focus on particle physics and its connection to cosmology. Liu received his PhD in Physics at University of Pennsylvania in 2007. Then he worked as McCormick fellow in Enrico Fermi Institute at University of Chicago during 2007-2010. After that, he moved to University of California at Santa Barbara to continue his postdoctoral research. He joined the Hong Kong University of Science and Technology (HKUST) in 2013 as a junior faculty. Now he is an associate professor at HKUST. 

负责分部
粒子与核物理
其他信息
Location: Online seminar
Password: 44847907

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