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Title: Identifying TeV Source Candidates among Fermi -LAT Unclassified Blazars

Abstract

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.

Authors:
 [1]; ORCiD logo [2];  [3];  [1];  [4]; ORCiD logo [3]
  1. Istituto Nazionale di Astrofisica (INAF), Firenze (Italy)
  2. SLAC National Accelerator Lab., Menlo Park, CA (United States)
  3. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
  4. Lab. de Instrumentacao e Fisica Experimental de Particulas, Lisboa (Portugal)
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1604569
Grant/Contract Number:  
[AC02-76SF00515]
Resource Type:
Accepted Manuscript
Journal Name:
The Astrophysical Journal (Online)
Additional Journal Information:
[Journal Name: The Astrophysical Journal (Online); Journal Volume: 887; Journal Issue: 1]; Journal ID: ISSN 1538-4357
Publisher:
Institute of Physics (IOP)
Country of Publication:
United States
Language:
English

Citation Formats

Chiaro, G., Meyer, M., Mauro, M. Di, Salvetti, D., Mura, G. La, and Thompson, D. J. Identifying TeV Source Candidates among Fermi -LAT Unclassified Blazars. United States: N. p., 2019. Web. doi:10.3847/1538-4357/ab46ad.
Chiaro, G., Meyer, M., Mauro, M. Di, Salvetti, D., Mura, G. La, & Thompson, D. J. Identifying TeV Source Candidates among Fermi -LAT Unclassified Blazars. United States. doi:10.3847/1538-4357/ab46ad.
Chiaro, G., Meyer, M., Mauro, M. Di, Salvetti, D., Mura, G. La, and Thompson, D. J. Tue . "Identifying TeV Source Candidates among Fermi -LAT Unclassified Blazars". United States. doi:10.3847/1538-4357/ab46ad.
@article{osti_1604569,
title = {Identifying TeV Source Candidates among Fermi -LAT Unclassified Blazars},
author = {Chiaro, G. and Meyer, M. and Mauro, M. Di and Salvetti, D. and Mura, G. La and Thompson, D. J.},
abstractNote = {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 = {10.3847/1538-4357/ab46ad},
journal = {The Astrophysical Journal (Online)},
number = [1],
volume = [887],
place = {United States},
year = {2019},
month = {12}
}

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