McFACTS I: Testing the LVK AGN channel with Monte Carlo For AGN Channel Testing & Simulation (McFACTS)

TL;DR

This paper introduces McFACTS, a Monte Carlo simulation tool for testing the AGN channel as a source of gravitational wave events, exploring various astrophysical parameters and their observational signatures.

Contribution

The paper presents a new open-source simulation code, McFACTS, for modeling and testing the AGN channel's role in black hole mergers and gravitational wave signals.

Findings

Migration traps facilitate growth of large mass IMBHs.

Flat initial mass functions reveal hierarchical merger features.

Anti-correlation between mass ratio and effective spin tests prograde merger bias.

Abstract

Active galactic nuclei (AGN) are a promising source of the binary black hole (BBH) mergers observed in gravitational waves with LIGO-Virgo-Kagra (LVK). Constraining the AGN channel allows us to limit AGN parameter space (disk density, size, average lifetime) and nuclear star cluster (NSC) parameter space. Constraints on AGN and NSCs have implications for $\Lambda$CDM models of AGN feedback and models of AGN-driven SMBH merger and growth. Here we present several qualitative studies of the AGN channel using new public, open-source, fast, reproducible code \texttt{McFACTS}\footnote{https://github.com/mcfacts/mcfacts}:Monte Carlo for AGN channel Testing \& Simulation. We demonstrate several important features for testing the AGN channel, including: i) growth to large mass IMBH is helped by the presence of migration traps or swamps, ii) flat BH initial mass functions highlight hierarchical merger features in the mass spectrum, iii) the ($q,\chi_{\rm eff}$) anti-correlation is a strong test of the bias to prograde mergers in the AGN channel, iv) spheroid encounters can drive a fraction of mergers with high in-plane spin components ($\chi_{\rm p}$), v) a high rate of extreme mass ratio inspirals (EMRIs) are driven by an initial population of embedded retrograde BH, vi) Both LVK and LISA are powerful probes of models of AGN disks and their embedded populations.