Sylabus
use of neural networks for fast simulation, generative models use of neural networks for tracking - application of Kalman filter modelling of triggering using neural networks neural networks for particle identification, event classification, event shapes, fast calorimeter simulation application of neural networks in accelerator physics - detection of anomalies in beam position monitoring, suggestion of correction tools for optimization of linear optics, optimization of the collimation system, lifetime and performance optimization and detection of hidden correlations
Anotace
• use of neural networks for fast simulation, generative models
• use of neural networks for tracking – application of Kalman filter
• modelling of triggering using neural networks
• neural networks for particle identification, event classification, event shapes, fast calorimeter simulation
• application of neural networks in accelerator physics – detection of anomalies in beam position monitoring, suggestion of correction tools for optimization of linear optics, optimization of the collimation system, lifetime and performance optimization and detection of hidden correlations