Aachen 2019 – scientific programme

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T: Fachverband Teilchenphysik

T 77: Deep Learning III

T 77.1: Talk

Thursday, March 28, 2019, 16:00–16:15, H06

Studies of Energy Reconstruction with Deep Learning at the LHC — •Simon Schnake, Hartmut Stadie, and Peter Schleper — Institut für Experimentalphysik, Uni Hamburg

The higher energies and luminosities in the up coming LHC phases are increasing the requirements on detector and analysis methods. One way to achieve this is to apply deep learning to different areas of the data analysis. The recent developments in the field make it a suitable candidate for exploration. This could significantly increase the accuracy and precision of the experiment. In this talk different approaches of energy reconstruction with deep learning are shown. Also some techniques to tackle distribution problems are presented.