1.
Investigating the VHE gamma-ray sources using deep neural networksVeronika Vodeb,
Saptashwa Bhattacharyya,
G. Principe,
Gabrijela Zaharijas,
R. Austri,
F. Stoppa,
S. Caron,
D. Malyshev, 2023, published scientific conference contribution
Abstract: The upcoming Cherenkov Telescope Array (CTA) will dramatically improve the point-source sensitivity compared to the current Imaging Atmospheric Cherenkov Telescopes (IACTs). One of the key science projects of CTA will be a survey of the whole Galactic plane (GPS) using both southern and northern observatories, specifically focusing on the inner galactic region. We extend a deep learning-based image segmentation software pipeline (autosource-id) developed on Fermi-LAT data to detect and classify extended sources for the simulated CTA GPS. Using updated instrument response functions for CTA (Prod5), we test this pipeline on simulated gamma-ray sources lying in the inner galactic region (specifically 0∘Keywords: deep neural network, cosmic-rays, CTA, classification
Published in RUNG: 31.08.2023; Views: 724; Downloads: 6
Full text (962,45 KB)
This document has many files! More...
