jaschers/psnet: v1.0

PSNet is the first application of pattern spectra on convolutional neural networks (CNNs) for the event reconstruction of imaging atmospheric Cherenkov telescopes (IACTs). We train a CNN on pattern spectra of gamma-ray events from the Cherenkov Telescope Array (CTA) for energy reconstruction and signal-background separation. PSNet is based on Tensorflow 2.3.1 and Keras 2.4.3 and uses the ctapipe software for the data handling.

Related Organizations

University of Groningen
Netherlands

Keywords

python, Cherenkov Telescope Array, machine learning, CTA, pattern spectra, gamma-ray astronomy, IACT, Imaging Atmospheric Cherenkov Telescope, convolutional neural network, CNN

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