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Charged particle distributions and robustness of the neural network pixel clustering in ATLAS
  Thesis defense

Friday 09 September 2016
from 13:00 to 15:00
at FB51
Speaker : Edvin Sidebo (Physics Department)
Abstract : The thesis contains a study of the robustness of the artificial neural network used in the ATLAS track reconstruction algorithm as a tool to recover tracks in dense environments. Different variations, motivated by potential discrepancies between data and simulation, are performed to the neural network's input while monitoring the corresponding change in the output. Within resaonable magnitudes, the neural networks prove to be robust to most variations.

Nordita  | Last modified 09 September 2016 09:15  |  HELP