Cargando…
Mass-decorrelated Xbb Tagger using Adversarial Neural Network
One key task performed by the ATLAS experiment at the LHC is the Xbb tagging, which refers to the identification of Higgs bosons decaying into bottom quark pairs ($H$ → $b$$\bar{b}$. Deep neural networks (DNN) have been adopted to develop Xbb taggers. While DNN-based taggers are generally performan...
Autor principal: | Chen, Shihlung |
---|---|
Lenguaje: | eng |
Publicado: |
2022
|
Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2799494 |
Ejemplares similares
-
Constructing mass-decorrelated hadronic decay taggers in ATLAS
por: Sogaard, Andreas
Publicado: (2019) -
Constructing mass-decorrelated hadronic decay taggers in ATLAS
por: Sogaard, Andreas
Publicado: (2019) -
Calibration of the mass-decorrelated ParticleNet tagger for boosted $\mathrm{b}\bar{\mathrm{b}}$ and $\mathrm{c}\bar{\mathrm{c}}$ jets using LHC Run 2 data
por: CMS Collaboration
Publicado: (2022) -
Identification of highly Lorentz-boosted heavy particles using graph neural networks and new mass decorrelation techniques
por: CMS Collaboration
Publicado: (2020) -
Decorrelated Jet Substructure Tagging using Adversarial Neural Networks
por: Shimmin, Chase Owen
Publicado: (2017)