Identifying TeV Source Candidates among Fermi-LAT Unclassified Blazars

Blazars, in particular the subclass of high synchrotron peaked active galactic nuclei are among the main targets for the present generation of Imaging Atmospheric Cerenkov Telescopes (IACTs), and they will remain of great importance for very high-energy γ-ray science in the era of the Cerenkov Teles...

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Veröffentlicht in:The Astrophysical journal 2019-12, Vol.887 (1), p.104
Hauptverfasser: Chiaro, G., Meyer, M., Mauro, M. Di, Salvetti, D., Mura, G. La, Thompson, D. J.
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container_issue 1
container_start_page 104
container_title The Astrophysical journal
container_volume 887
creator Chiaro, G.
Meyer, M.
Mauro, M. Di
Salvetti, D.
Mura, G. La
Thompson, D. J.
description Blazars, in particular the subclass of high synchrotron peaked active galactic nuclei are among the main targets for the present generation of Imaging Atmospheric Cerenkov Telescopes (IACTs), and they will remain of great importance for very high-energy γ-ray science in the era of the Cerenkov Telescope Array (CTA). Observations by IACTs, which have relatively small fields of view (∼few degrees), are limited by viewing conditions; therefore, it is important to select the most promising targets to increase the number of detections. The aim of this paper is to search for unclassified blazars among known γ-ray sources from the Fermi Large Area Telescope (LAT) third source catalog that are likely detectable with IACTs or CTA. We use an artificial neural network algorithm and updated analysis of Fermi-LAT data. We found 80 γ-ray source candidates, and for the highest-confidence candidates, we calculate their potential detectability with IACTs and CTA based on an extrapolation of their energy spectra. Follow-up observations of our source candidates could significantly increase the current TeV source population sample and ultimately confirm the efficiency of our algorithm to select TeV sources.
doi_str_mv 10.3847/1538-4357/ab46ad
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subjects Active galactic nuclei
Algorithms
Artificial neural networks
ASTRONOMY AND ASTROPHYSICS
Astrophysics
Blazars
Energy spectra
Gamma ray sources
Neural networks
Telescopes
title Identifying TeV Source Candidates among Fermi-LAT Unclassified Blazars
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