Journal Article

McFACTS I: Testing the LVK AGN Channel with Monte Carlo for AGN Channel Testing and Simulation (McFACTS)

McPike, Emily, McKernan, Barry, d, K.E. Saavik, Postiglione, Jake, Nathaniel, Kaila, Cook, Harrison E, Delfavero, Vera, Ray, Shawn, O’Shaughnessy, Richard

2025

Overview

Active galactic nuclei (AGNs) are a promising source of the binary black hole 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 AGNs and NSCs have implications for Λ cold dark matter models of AGN feedback and models of AGN-driven supermassive black hole merger and growth. Here we present several qualitative studies of the AGN channel using new public, open-source, fast, reproducible code McFACTS (https://github.com/mcfacts/mcfacts): Monte Carlo for AGN channel Testing and Simulation. We demonstrate several important features for testing the AGN channel, including: (i) growth to large-mass intermediate-mass black hole 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, χeff) anticorrelation 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 (χp), (v) a high rate of extreme mass ratio inspirals are driven by an initial population of embedded retrograde BH, and (vi) both LVK and LISA are powerful probes of models of AGN disks and their embedded populations.

• Publisher: IOP Publishing
• Subject: Active galactic nuclei / Black holes / Cold dark matter / Dark matter / Disks / Gravitational waves / Initial mass function / Parameters / Qualitative research / Source code / Star clusters / Supermassive black holes / Swamps