Speaker
Lukas Calefice
(Universitat de Barcelona/ICCUB)
Description
Machine learning techniques have a variety of use cases within the LHCb experiment. They are an essential ingredient to achieve the ultimate performance in event reconstruction and high precision in physics output. This talk will give an insight to the use of ML algorithms in online event selections performed by the LHCb trigger system, offline data analyses of physics measurements , as well as to track and electron reconstruction and particle identification algorithms. Finally, the ML use in the LHCb simulation framework and the experience of the UB LHCb group with machine learning in LHCb will be discussed.
Primary author
Lukas Calefice
(Universitat de Barcelona/ICCUB)
