ETD system

Electronic theses and dissertations repository

 

Tesi etd-09202017-095045


Thesis type
Tesi di laurea magistrale
Author
CARTA, ANTONIO
URN
etd-09202017-095045
Title
Deep learning models for track reconstruction in particle physics
Struttura
INFORMATICA
Corso di studi
INFORMATICA
Commissione
relatore Dott. Bacciu, Davide
relatore Dott. Pantaleo, Felice
Parole chiave
  • machine learning
  • Deep learning
  • neural networks
  • track reconstruction
  • high-energy phisics
  • CERN
  • CMS
  • convolutional neural networks
Data inizio appello
06/10/2017;
Consultabilità
completa
Riassunto analitico
Track reconstruction is one of the most expensive tasks performed during the analysis due to its combinatorial nature and the high number of fake tracks generated. In this thesis we develop a deep learning model capable of recognizing fake tracks using only two hit shapes of a track seed.
File