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The aim of this study is to search for unclassified blazars that are likely detectable with Cherenkov telescopes within reasonable observation times , using Artificial Neural Network (ANN) algorithm that can realistically observed with IACTs or CTA in 50 or 5 hours.
The 3FGL catalogue contains two classes of source with uncertain classification that offer opportunities to identify HBLs and subsequently TeV candidates according with the TeV catalog census : (i) the 573 BCU and (ii) 1010 UCSs. Recently in https://arxiv.org/abs/1602.00385 the authors applied a number of machine-learning techniques to classify 3FGL UCSs as pulsars or AGN. The authors found 334 pulsars, 559 sources of AGN type (UCS$_agn$) type and 117 remained uncertain.In https://arxiv.org/abs/1705.09832 the 559 UCS_agn have been further analyzed with the ANN algorithm and 271 UCS_bll, 185 UCS_fsrq and 103 UCS_bcu have been identifyied .
The resulting 573 BCU and 103 UCS_bcu 559 AGN type sources represent the first targets for this search and we apply an optimized version of the ANN described in https://arxiv.org/abs/1709.05727 in order to compute the likelihood distribution of HBL and non-HBL sources
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ref.contact Graziano Chiaro chiaro@lambrate.iasf graziano.chiaro@inaf.it
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