Deep Learning for the classification of quenched jets
Abstract An important aspect of the study of Quark-Gluon Plasma (QGP) in ultrarelativistic collisions of heavy ions is the ability to identify, in experimental data, a subset of the jets that were strongly modified by the interaction with the QGP. In this work, we propose studying Deep Learning tech...
Guardado en:
Autores principales: | L. Apolinário, N. F. Castro, M. Crispim Romão, J. G. Milhano, R. Pedro, F. C. R. Peres |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
SpringerOpen
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/896cea2d79134c30b19fa6e5bb18ae18 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Wilson line correlators beyond the large-N c
por: Johannes Hamre Isaksen, et al.
Publicado: (2021) -
Spin asymmetries in electron-jet production at the future electron ion collider
por: Zhong-Bo Kang, et al.
Publicado: (2021) -
Collective flow in single-hit QCD kinetic theory
por: Aleksi Kurkela, et al.
Publicado: (2021) -
Detecting an axion-like particle with machine learning at the LHC
por: Jie Ren, et al.
Publicado: (2021) -
A comparative study of Higgs boson production from vector-boson fusion
por: A. Buckley, et al.
Publicado: (2021)