Cargando…
Improving Fast Inference Jet Detection Neural Networks in the CMS Trigger System
The Large Hadron Collider (LHC) is already one of the largest sources of data in the world. By redevelopments before the end of 2027, its upgrade named High-Luminosity Large Hadron Collider (HL-LHC) will gather data by a factor of ten beyond LHC’s initial specifications. The objective is to allow ob...
Autor principal: | Abdollah Chalaki, Mohammad |
---|---|
Lenguaje: | eng |
Publicado: |
2021
|
Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2783308 |
Ejemplares similares
-
Ultra-fast Machine Learning Inference for triggering at CMS Experiment
por: Asif, Farheen
Publicado: (2021) -
Graph Neural Network Architectures for Fast Simulation and Muon Momentum Inference at the CMS Detector
por: Hariri, Ali
Publicado: (2021) -
Analysis of Muon Trigger Efficiencies for the CMS Detector
por: Wunsch, Stefan
Publicado: (2016) -
Fast inference on FPGA for the ATLAS Muon Trigger
por: Carnesale, Maria
Publicado: (2023) -
Fast Inference on FPGAs for HEP trigger systems
por: Javed, Hamza
Publicado: (2019)