A convolutional neural network with alpha and Size pre-cuts separates gamma-ray events from cosmic-ray background in TAIGA-IACT data at a level comparable to the standard Hillas method, yielding a Crab Nebula signal at about 6 sigma in 21 hours.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
astro-ph.IM 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Gamma/hadron separation in the TAIGA experiment with neural network methods
A convolutional neural network with alpha and Size pre-cuts separates gamma-ray events from cosmic-ray background in TAIGA-IACT data at a level comparable to the standard Hillas method, yielding a Crab Nebula signal at about 6 sigma in 21 hours.