Article
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Detection of Periodic Radio Signal from the Blazar J1043+2408
Version 1
: Received: 14 September 2018 / Approved: 17 September 2018 / Online: 17 September 2018 (06:00:08 CEST)
A peer-reviewed article of this Preprint also exists.
Bhatta, G. Detection of Periodic Radio Signal from the Blazar J1043+2408. Galaxies 2018, 6, 136. Bhatta, G. Detection of Periodic Radio Signal from the Blazar J1043+2408. Galaxies 2018, 6, 136.
Abstract
Search for periodic signals from blazars has become widely discussed topic in recent years. This is because periodic signals bear imprints of the processes occurring near the innermost regions of blazars which are mostly inaccessible to our direct view. Such signals provide insights into various aspect of blazar studies including disk-jet connection, magnetic field configuration and, more importantly, strong gravity near the supermassive black holes and release of gravitational waves from the binary supermassvie black hole systems. In this work, we report detection of a periodic signal in the radio light curves of the blazar J1043+2408 spanning ~10.5 years. We performed multiple methods of time series analysis, namely, epoch folding, Lomb-Scargle periodogram, and discrete auto-correlation function. All three methods consistently reveal a repeating signal with a periodicity of ~563 days. To robustly account for the red-noise processes usually dominant in the blazar variability and other possible artifacts, a large number of Monte Carlo simulations were performed. This allowed us to estimate a high significance (99.9% local and 99.4% global) against possible spurious detection. As possible explanations, we discuss a number of scenarios including binary supermassive black hole system, Lense-Thirring precession, and jet swing and precession.
Keywords
supermassive black holes: non-thermal radiation; active galactic nuclei: BL lacertae objects: individual: J1043+2408; galaxies: jets; method: time series analysis
Subject
Physical Sciences, Astronomy and Astrophysics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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