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(Seminar) Hunting “Strange” Signals via Deep Learning
2019-11-19     Text Size:  A

CAS Key Laboratory of Theoretical Physics

Institute of Theoretical Physics

Chinese Academy of Sciences

 Seminar

Title

题目

Hunting “Strange” Signals via Deep Learning

Speaker

报告人

Yuichiro Nakai

Affiliation

所在单位

Tsung-Dao Lee Institute and Shanghai Jiao Tong University

Date

日期

3:00pm, Nov 19, 2019, Tuesday

Venue

地点

ITP South Building 6420

Abstract

摘要

Deep learning is receiving increased attention throughout physics community as well as the real world. In this talk, after a brief introduction of deep learning, I will present two of my recent research on this technique applied to collider physics. The first part of the talk is on the possibility of strange-quark tagging, the last missing piece among quark and gluon identifications in jets. I will describe how to overcome the most difficult classification between strange and down quark jets. Neural networks feed jet images and learn features of strange jets in a supervised way. The second part is on an unsupervised learning technique called autoencoder as a tool for new physics search. The key idea of the autoencoder is that it learns to map background events back to themselves, but fails to reconstruct anomalous events that it has never encountered before. The reconstruction error can then be used as an anomaly threshold. As the first baby step, the example of finding top and gluino jets from background QCD jets will be discussed.

Contact Person

所内联系人

舒菁
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