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Compton-thick AGN in the NuSTAR era. VIII. A joint NuSTAR–XMM-newton monitoring of the changing-look Compton-thick AGN NGC 1358

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Buchner,  J.
High Energy Astrophysics, MPI for Extraterrestrial Physics, Max Planck Society;

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Citation

Marchesi, S., Zhao, X., Torres-Albà, N., Ajello, M., Gaspari, M., Pizzetti, A., et al. (2022). Compton-thick AGN in the NuSTAR era. VIII. A joint NuSTAR–XMM-newton monitoring of the changing-look Compton-thick AGN NGC 1358. The Astrophysical Journal, 935(2): 114. doi:10.3847/1538-4357/ac80be.


Cite as: https://hdl.handle.net/21.11116/0000-000C-144B-A
Abstract
We present the multi-epoch monitoring with NuSTAR and XMM-Newton of NGC 1358, a nearby Seyfert 2 galaxy whose properties made it a promising candidate X-ray changing-look active galactic nucleus (AGN), i.e., a source whose column density could transition from its 2017 Compton-thick (having LOS hydrogen column density NH,LOS > 1024 cm-2) state to a Compton-thin (NH,LOS < 1024 cm-2) one. The multi-epoch X-ray monitoring confirmed the presence of significant NH,LOS variability over timescales of weeks to years, and allowed us to confirm the changing-look nature of NGC 1358, which has most recently been observed in a Compton-thin status. Multi-epoch monitoring with NuSTAR and XMM-Newton is demonstrated to be highly effective in simultaneously constraining three otherwise highly degenerate parameters: the torus average column density and covering factor, and the inclination angle between the torus axis and the observer. We find a tentative anticorrelation between column density and luminosity, which can be understood under the framework of chaotic cold accretion clouds driving recursive AGN feedback. The monitoring campaign of NGC 1358 has proven the efficiency of our newly developed method to select candidate NH,LOS-variable, heavily obscured AGN, which we plan to soon extend to a larger sample to better characterize the properties of the obscuring material surrounding accreting supermassive black holes, as well as to constrain AGN feeding models.