# pAGN: the one-stop solution for AGN disc modeling

**Authors:** Daria Gangardt, Alessandro Alberto Trani, Clément Bonnerot, Davide Gerosa  
**arXiv:** [2403.00060](https://arxiv.org/abs/2403.00060)  
**Date:** 2024-02-29  
**Summary page:** https://www.summarizepaper.com/en/paper/2403.00060v1/

## Key points

- Authors Daria Gangardt, Alessandro Alberto Trani, Clément Bonnerot, and Davide Gerosa present the paper "pAGN: the one-stop solution for AGN disc modeling" focusing on active galactic nuclei (AGNs) and their accretion discs in high-energy astrophysics.
- The study critically reanalyzes two widely used approaches by Sirko & Goodman (2003) and Thompson et al. (2005), highlighting assumptions and exploring new aspects of their derivation.
- Development of the pAGN module for Python programming language as a public implementation of these accretion-disc models.
- Application of pAGN to investigate the evolution of stellar-mass black holes within AGN discs, including analysis of potential migration traps influencing their movement and dynamics.
- Comprehensive study with 18 pages, 8 figures, 2 tables, and accompanying code available on GitHub provides a valuable resource for researchers interested in AGN disc modeling and its implications in astrophysical phenomena.

## Summary

In their paper titled "pAGN: the one-stop solution for AGN disc modeling," authors Daria Gangardt, Alessandro Alberto Trani, Clément Bonnerot, and Davide Gerosa delve into the intricate world of active galactic nuclei (AGNs) and their surrounding accretion discs in high-energy astrophysics. These models play a crucial role in understanding the behavior of gas density and temperature within these discs as they vary radially based on underlying physical assumptions. The study critically reanalyzes two widely used approaches proposed by Sirko & Goodman (2003) and Thompson et al. (2005), shedding light on their assumptions and elucidating previously unexplored aspects of their derivation. This detailed examination leads to the development of the pAGN module for the Python programming language, marking its debut as a public implementation of these accretion-disc models. Furthermore, the researchers extend their investigation by applying pAGN to explore the evolution of stellar-mass black holes residing within AGN discs. Of particular interest is the identification and analysis of potential migration traps that may influence the movement and dynamics of these black holes within their surrounding environments. With 18 pages, 8 figures, 2 tables, and accompanying code available on GitHub, this comprehensive study offers a valuable resource for researchers seeking a deeper understanding of AGN disc modeling and its implications in astrophysical phenomena.