期刊
EUROPEAN PHYSICAL JOURNAL C
卷 81, 期 7, 页码 -出版社
SPRINGER
DOI: 10.1140/epjc/s10052-021-09389-x
关键词
-
资金
- U.S. Department of Energy, Office of Science [DE-AC02-05CH11231, DE-AC02-76SF00515]
- DOE [DOE-SC0010008]
- Spanish Research Agency (Agencia Estatal de Investigacion) [FPA2016-78022-P, PID2019-110058GB-C22]
- IFT Centro de Excelencia Severo Ochoa [SEV-2016-0597]
- European Union [690575]
This study compares the autoencoder (AE) with the Classification Without Labels (CWoLa) technique for anomaly detection at the LHC, finding that they have complementary sensitivity in identifying new physics signals.
Anomaly detection techniques are growing in importance at the Large Hadron Collider (LHC), motivated by the increasing need to search for new physics in a model-agnostic way. In this work, we provide a detailed comparative study between a well-studied unsupervised method called the autoencoder (AE) and a weakly-supervised approach based on the Classification Without Labels (CWoLa) technique. We examine the ability of the two methods to identify a new physics signal at different cross sections in a fully hadronic resonance search. By construction, the AE classification performance is independent of the amount of injected signal. In contrast, the CWoLa performance improves with increasing signal abundance. When integrating these approaches with a complete background estimate, we find that the two methods have complementary sensitivity. In particular, CWoLa is effective at finding diverse and moderately rare signals while the AE can provide sensitivity to very rare signals, but only with certain topologies. We therefore demonstrate that both techniques are complementary and can be used together for anomaly detection at the LHC.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据