Using a nested anomaly detection machine learning algorithm to study the neutral triple gauge couplings at an \(e^+e^-\) collider

DOI10.1016/J.NUCLPHYSB.2022.115735zbMath1491.81027arXiv2111.10543OpenAlexW4220660205MaRDI QIDQ2122543

Li-Hua Cai, Ji-Chong Yang, Yu-Chen Guo

Publication date: 6 April 2022

Published in: Nuclear Physics. B (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2111.10543

zbMATH Keywords

anomaly detection algorithm

Mathematics Subject Classification ID

Module categories in associative algebras (16D90) Unified quantum theories (81V22) Signal detection and filtering (aspects of stochastic processes) (60G35) Anomalies in quantum field theory (81T50) Alternative quantum mechanics (including hidden variables, etc.) (81Q65)

Uses Software

• FeynRules
• DELPHES
• MadGraph5_aMC@NLO
• IsolationForest

Cites Work

• Probing the effects of dimension-eight operators describing anomalous neutral triple gauge boson interactions at FCC-hh
• Unnamed Item

This page was built for publication: Using a nested anomaly detection machine learning algorithm to study the neutral triple gauge couplings at an \(e^+e^-\) collider