Testing Colour-magnitude Pattern as A Method in the Search for Changing-Look AGNs

作     者：Zhu, Li-Tao Wang, Zhongxiang Devanand, P.U. Gupta, Alok C. Dogra, Karan Li, Jie Zhang, Ju-Jia Ji, Shun-Hao Sun, Si-Si 

作者机构：Department of Astronomy School of Physics and Astronomy Yunnan University Kunming650091 China Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China  Manora Peak Nainital263001 India Department of Applied Physics/Physics Mahatma Jyotiba Phule Rohilkhand University Bareilly243006 India Key Laboratory for Research in Galaxies and Cosmology Department of Astronomy University of Science and Technology of China Hefei230036 China School of Astronomy and Space Science University of Science and Technology of China Hefei230026 China Yunnan Observatories Chinese Academy of Sciences Kunming650216 China Key Laboratory for the Structure and Evolution of Celestial Objects Chinese Academy of Sciences Kunming650216 China 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2024年

核心收录：

主　　题：Active Galactic Nuclei 

摘      要：We develop a simple method to search for changing-look (CL) active galactic nucleus (AGN) candidates, and conduct a test run. In this method, optical variations of AGNs are monitored and CL-AGNs may appear to have a pattern of being bluer when in brightening flare-like events. Applying this method, previously-classified type 2 AGNs that show the bluer-when-brighter (BWB) pattern are selected. Among more than ten thousands type 2 AGNs classified in the Sloan Digital Sky Survey (SDSS), we find 73 candidates with possibly the strongest BWB pattern. We note that 13 of them have previously been reported as CL-AGNs. We have observed nine candidates, and found that five among them showed the CL transition from type 2 to type 1. In addition, we also test extending the selection to previously-classified type 1 AGNs in the SDSS by finding sources with a possible redder-when-brighter pattern, but none of the three sources observed by us is found to show the transition from type 1 to type 2. We discuss the variation properties in both the success and failure cases, and plan to observe more candidates selected with the method. From the observational results, a detailed comparison between the CL-AGNs and none CL-AGNs will help quantitatively refine the selection criteria and in turn allow us to configure the general properties of CLAGNs. © 2024, CC BY.