| Detection of a high-confidence quasi-periodic oscillation in radio light curve of the high redshift FSRQ PKS J0805–0111 |
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| 作者姓名： | Guo-Wei Ren Hao-Jing Zhang Xiong Zhang Nan Ding Xing Yang Fu-Ting Li Pei-Lin Yan Xiao-Lin Xu |
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| 作者单位： | College of Physics and Electronics;Department of Astronomy;School of Physical Science and Technology |
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| 基金项目： | supported by the National Natural Science Foundation of China(Grant No.11663009);the High-Energy Astrophysics Science and Technology Innovation Team of Yunnan Higher School;the OVRO40-m monitoring program(Fan&Wu 2018)which is supported in part by NASA grants NNX08AW31G;NNX11A043G and NNX14AQ89G,and NSF grants AST-0808050 and AST-1109911。 |
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| 摘 要： | In this work,we have searched for quasi-periodic oscillations(QPOs)in the 15 GHz light curve of the FSRQ PKS J0805-0111 monitored by the Owens Valley Radio Observatory(OVRO)40 m telescope during the period from 2008 January 9 to 2019 May 9,using the weighted wavelet Z-transform(WWZ)and the Lomb-Scargle Periodogram(LSP)techniques.This is the first time to search for a periodic radio signal in the FSRQ PKS J0805-0111 by these two methods.Both methods consistently reveal a repeating signal with a periodicity of 3.38±0.8 yr(>99.7%confidence level).In order to determine the significance of the periods,the false alarm probability method was applied,and a large number of Monte Carlo simulations were performed.As possible explanations,we discuss a number of scenarios including the thermal instability of thin disks scenario,the spiral jet scenario and the binary supermassive black hole scenario.We expect that the binary black hole scenario,where the QPO is caused by the precession of binary black holes,is the most likely explanation.FSRQ PKS J0805-0111 thus could be a good binary black hole candidate.In the binary black hole scenario,the distance between the primary black hole and the secondary black hole is about 1.71×1016 cm.
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| 关 键 词： | active galactic nuclei:flat spectrum radio quasar:individual:PKS J0805–0111 galaxies:jets method:time series analysis |
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