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README.md

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neutrino-dnn

Deep-learning applied to neutrino property reconstruction

Goal

To reconstruct neutrino properties from an incoming signal using deep-learning & neural networks. The network is to be trained and evaluated on simulated data.

Author

  • The author of this project is Sigfrid Stjärnholm (sigge.stjarnholm@gmail.com).
  • The project is performed as part of a Bachelor thesis at Uppsala University, Sweden, in the spring of 2021.
  • The project supervisor is Christian Glaser, The Division of High Energy Physics, Department of Physics and Astronomy, Uppsala University, Sweden.