Issue |
A&A
Volume 689, September 2024
|
|
---|---|---|
Article Number | A205 | |
Number of page(s) | 7 | |
Section | Astrophysical processes | |
DOI | https://doi.org/10.1051/0004-6361/202450098 | |
Published online | 16 September 2024 |
Estimating the mass-to-distance ratio for a set of megamaser AGN black holes by employing a general relativistic method
1
Instituto de Física Luis Rivera Terrazas (IFUAP), Benemérita Universidad Autónoma de Puebla, Puebla, 72570
Mexico
2
Instituto de Física y Matemáticas, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán, 58040
Mexico
Received:
23
March
2024
Accepted:
6
June
2024
Context. Motivated by the recent achievements of a full general relativistic method in determining black hole (BH) parameters, we continue to estimate the mass-to-distance ratio of the supermassive BHs hosted at the core of the active galactic nuclei (AGNs) of the megamaser galaxies NGC 1320, NGC 1194, NGC 5495, and Mrk 1029.
Aims. Our aim is to study the properties of super massive BHs at the centers of the selected AGNs by using a full general relativistic method that allows us to address the potential detection of relativistic effects within such astrophysical systems.
Methods. In order to perform statistical estimations with publicly available observational data, we used a general relativistic model that describes BH rotation curves and further employed a Bayesian fitting method.
Results. We estimated the mass-to-distance ratio of the aforementioned BHs, their position and the recessional redshifts of the host galaxies produced by both peculiar motion and cosmological expansion of the Universe. Finally, we calculated the gravitational redshift of the closest maser to the BH for each AGN. This gravitational redshift is a general relativistic effect produced by the gravitational field of the BH properly included in the modelling.
Key words: black hole physics / gravitation / masers / relativistic processes
© The Authors 2024
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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