PAGN: the one-stop solution for AGN disc modelling

Abstract

Models of accretion discs surrounding active galactic nuclei (AGNs) find vast applications in high-energy astrophysics. The broad strategy is to parametrize some of the key disc properties such as gas density and temperature as a function of the radial coordinate from a given set of assumptions on the underlying physics. Two of the most popular approaches in this context were presented by Sirko & Goodman and Thompson et al. We present a critical reanalysis of these widely used models, detailing their assumptions and clarifying some steps in their derivation that were previously left unsaid. Our findings are implemented in the pAGN module for the Python programming language, which is the first public implementation of these accretion-disc models. We further apply pAGN to the evolution of stellar-mass black holes embedded in AGN discs, addressing the potential occurrence of migration traps.