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| Paper: |
Full LST-1 Data Reconstruction Using Convolutional Neural Networks |
| Volume: |
535, Astronomical Data Analysis Software and Systems XXXI |
| Page: |
79 |
| Authors: |
Jurysek, J.; Lyard, E.; Walter, R. |
| Abstract: |
The Cherenkov Telescope Array (CTA) will be the world’s largest and most sensitive ground-based gamma-ray observatory in the energy range from a few tens of GeV to tens of TeV. The LST-1 prototype, currently in its commissioning phase, is the first of the four largest CTA telescopes, that will be built in the northern site of CTA in La Palma, Canary Islands, Spain. In this contribution, we present a full-image reconstruction method using a modified InceptionV3 deep convolutional neural network applied on non-parametrized shower images. We evaluate the performance of optimized networks on Monte Carlo simulations of LST-1 shower images and compare the results with the performance of the standard reconstruction method. We also show how both methods work on real-data reconstruction. |
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