Searching for TeV Candidates in 4LAC High-synchrotron-peaked Frequency BL Lac Objects

Abstract

The next generation of TeV detectors is expected to have a significantly enhanced performance. It is therefore constructive to search for new TeV candidates for observation. This paper focuses on TeV candidates among the high-synchrotron-peaked BL Lacertae objects (HBLs) reported in the fourth catalog of active galactic nuclei detected by the Fermi's Large Area Telescope, i.e., 4LAC. By cross-matching the Fermi data with radio and optical observations, we collected the multiwavelength features of 180 HBLs with known redshift. The data set contains 39 confirmed TeV sources and 141 objects whose TeV detection has not yet been reported (either not yet observed, or observed but not detected). Using two kinds of supervised machine-learning (SML) methods, we searched for new possible TeV candidates (PTCs) among the nondetected objects by assessing the similarity of their multi-wavelength properties to existing TeV-detected objects. The classification results of the two SML classifiers were combined and the 24 highest-confidence PTCs were proposed as the best candidates. We calculate, here, the 12 year averaged Fermi spectra of these PTCs and estimate their detectability by extrapolating the Fermi spectrum and including the extragalactic background light attenuation. Four candidates are suggested to have a high likelihood of being detected by the Large High Altitude Air Shower Observatory and 24 are candidates for the Cerenkov Telescope Array observations.

publication in ApJ. 14 pages, 6 figures, 4 tables

References in corpus (16)

• The Milky Way as a Kiloparsec-Scale Axionscope
• The extragalactic background light revisited and the cosmic photon-photon opacity
• Hints of the existence of Axion-Like-Particles from the gamma-ray spectra of cosmological sources
• 2WHSP: A catalog of HE and VHE gamma-ray blazars and blazar candidates
• 1WHSP: an IR-based sample of $\sim$1,000 VHE $\gamma$-ray blazar candidates
• Blazar Flaring Patterns (B-FlaP): Classifying Blazar Candidates of Uncertain type in the third Fermi-LAT catalog by Artificial Neural Networks
• 3FGLzoo. Classifying 3FGL Unassociated Fermi-LAT Gamma-ray Sources by Artificial Neural Networks
• Evaluating the optical classification of Fermi BCUs using machine learning
• Evidence for the Secondary Emission as the Origin of Hard Spectra in TeV Blazars
• An investigation on the factors affecting machine learning classifications in $\gamma$-ray astronomy
• TeV-peaked candidate BL Lac objects
• Evaluating the classification of Fermi BCUs from the 4FGL Catalog Using Machine Learning
• Modelling the multi-wavelength emission of flat spectrum radio quasar 3C 279
• Extreme & High Synchrotron Peak Blazars beyond 4FGL: The 2BIGB $\gamma$-ray catalogue
• Machine Learning applied to Multifrequency Data in Astrophysics: Blazar Classification
• Identifying TeV Source Candidates among Fermi-LAT Unclassified Blazars

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• Very High Energy Flat Spectral Radio Quasar Candidates