The dichotomy between low-frequency-peaked BL Lacs and flat-spectrum radio quasars

Author:

Cheng Y P1,Kang S J2ORCID,Zheng Y G13

Affiliation:

1. Department of Physics, Yunnan Normal University , Kunming 650092, China

2. School of Physics and Electrical Engineering, Liupanshui Normal University , Liupanshui, Guizhou 553004, China

3. National Astronomical Observatories Yunnan Normal University Astronomical Education Base , Kunming 650092, China

Abstract

ABSTRACT By comparing the Fourth Fermi Large Area Telescope active galactic nuclei (AGNs) Catalog Data Release 2 (4LAC-DR2) and the Radio Fundamental Catalog (RFC-2021b), we obtain an AGN sample containing 2816 AGNs. We calculate the γ-ray loudness (Gγ) of the sample sources, and establish the relevant relationship between several gamma/radio properties. The results show that: 1) the synchrotron peak frequency ($\nu _\mathrm{peak}^S$) strongly correlates with the γ-ray photon spectral index (Γγ), γ-ray luminosity (Lγ), and radio luminosity (LR); 2) the low-synchrotron-peaked BL Lac objects (LBLs) and the flat-spectrum radio quasars (FSRQs) partially overlap in log $\nu _\mathrm{peak}^S\!-\!\Gamma _\gamma$, log Lγ–Γγ, log LR–Γγ, log Gγ–Γγ, log $\nu _\mathrm{peak}^S\!-\!$log Lγ, log $\nu _\mathrm{peak}^S\!-\!$log LR, and log $\nu _\mathrm{peak}^S\!-\!$log Gγ space. We plotted the distribution of redshift (z), $\nu _\mathrm{peak}^S$, Γγ, Lγ, VLBI 8.4 GHz flux density ($S_{\rm {8.4\, GHz}}$), and Gγ to distinguish FSRQs and LBLs. We note that $\nu _\mathrm{peak}^S$, Γγ, and $S_{8.4\, {\rm GHz}}$ show similar bimodal distributions. To further determine whether FSRQs are misjudged as LBLs, we examined the Compton dominance (CD), and found that CD < 1 for only two out of 39 sources. This measurement provides further evidence that FSRQs may be mistaken for LBLs.

Funder

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Hunting for the candidates of misclassified sources in LSP BL Lacs using machine learning;Monthly Notices of the Royal Astronomical Society;2023-08-17

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