Skip to content

Scripts and logics to train tracking models for the ultra-fast simulation of the LHCb experiment

License

Notifications You must be signed in to change notification settings

landerlini/lb-trksim-train

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

LHCb Tracking Parametrization Training

Scripts and logics to train tracking models for the ultra-fast simulation of the LHCb experiment.

The ultra-fast simulation of the LHCb experiment is based on a combination of simple parametrization and machine-learning models that concur to the parametrization of the overall response of the whole detector.

We organize in this package the code to train and validate the machine-learning models used to parametrize the response of the tracking system.

This includes:

  • the geometrical acceptance of the detector
  • the tracking efficiency
  • the resolution on the position and the momentum of the reconstructed tracks
  • the covariance matrix of the track parameters in its closest approach to the beam direction

See also

  • lb-pidgan-train for the training of the models describing the PID

Dependencies

How to train the models

The pipeline is described in a Snakefile so

snakemake -j <number-of-cores> all 

should be enough to train the whole set of models.

About

Scripts and logics to train tracking models for the ultra-fast simulation of the LHCb experiment

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published