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The relationship between black hole accretion rate and gas properties at the Bondi radius

Published online by Cambridge University Press:  29 January 2021

De-Fu Bu*
Affiliation:
Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, Chinese Academy of Sciences, 80 Nandan Road, Shanghai 200030, China email: dfbu@shao.ac.cn
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Abstract

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The mass accretion rate determines the black hole accretion mode and the corresponding efficiency of active galactic nuclei (AGNs) feedback. In large-scale simulations studying galaxy formation and evolution, the Bondi radius can be at most marginally resolved. In these simulations, the Bondi accretion formula is always used to estimate the black hole accretion rate. The Bondi solution can not represent the real accretion process. We perform 77 simulations with varying density and temperature at Bondi radius. We find a formula to calculate the black hole accretion rate based on gas density and temperature at Bondi radius. We find that the formula can accurately predict the luminosity of observed low-luminosity AGNs. This formula can be used in sub-grid models in large-scale simulations with AGNs feedback.

Type
Contributed Papers
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of International Astronomical Union

References

Bu, D. & Yang, X. 2019, MNRAS, 484, 172410.1093/mnras/stz050CrossRefGoogle Scholar
Ciotti, L. & Ostriker, J. P. 2001, ApJ, 551, 13110.1086/320053CrossRefGoogle Scholar
Fabian, A. C. 2012, ARA&A, 50, 45510.1146/annurev-astro-081811-125521CrossRefGoogle Scholar
Gaspari, M., Ruszkowski, M., & Oh, S. P. 2013, MNRAS, 432, 340110.1093/mnras/stt692CrossRefGoogle Scholar
Guo, F. 2016, ApJ, 826, 1710.3847/0004-637X/826/1/17CrossRefGoogle Scholar
Higginbottom, N., Knigge, C., Long, K. S. et al. 2019, MNRAS, 484, 463510.1093/mnras/stz310CrossRefGoogle Scholar
Igumenshchev, I. V. & Narayan, R. 2002, ApJ, 566, 13710.1086/338077CrossRefGoogle Scholar
Li, S. & Begelman, M. C. 2014, ApJ, 786, 610.1088/0004-637X/786/1/6CrossRefGoogle Scholar
Moscibrodzka, M. 2006, A&A, 450, 93Google Scholar
Pellegrini, S. 2005, ApJ, 624, 15510.1086/429267CrossRefGoogle Scholar
Springel, V., Di Matteo, T., & Hernquist, L. 2005, MNRAS, 361, 77610.1111/j.1365-2966.2005.09238.xCrossRefGoogle Scholar
Waters, T., Aykutalp, A., Proga, D., et al. 2019, arXiv:1910.01106Google Scholar
Xie, F. & Yuan, F. 2012, MNRAS, 427, 158010.1111/j.1365-2966.2012.22030.xCrossRefGoogle Scholar
Xie, F., Yuan, F., & Ho, L., C. 2017, ApJ, 844, 4210.3847/1538-4357/aa7950CrossRefGoogle Scholar
Yuan, F., Bu, D., & Wu, M. 2012, ApJ, 761, 13010.1088/0004-637X/761/2/130CrossRefGoogle Scholar
Yuan, F. & Narayan, R. 2014, ARA&A, 52, 52910.1146/annurev-astro-082812-141003CrossRefGoogle Scholar
Yuan, F., Yoon, D., Li, Y., et al. 2018, ApJ, 857, 12110.3847/1538-4357/aab8f8CrossRefGoogle Scholar