Building Semi-Analytic Black Hole Seeding Models Using IllustrisTNG Host Galaxies
Analis Eolyn Evans, Laura Blecha, Aklant Kumar Bhowmick

TL;DR
This paper develops semi-analytic black hole seeding models using IllustrisTNG simulations, exploring various criteria to better understand early black hole growth and their observable signatures across cosmic time.
Contribution
It introduces a flexible semi-analytic approach to black hole seeding within cosmological simulations, improving predictions especially for low-mass, high-redshift black holes.
Findings
Most models match low-redshift black hole mass densities with observations.
High-redshift black hole number densities vary significantly between models.
Low-mass black holes dominate at high redshift, relevant for gravitational wave detection.
Abstract
Because early black holes (BHs) grew to in less than 1 Gyr of cosmic time, BH seeding models face stringent constraints. To efficiently constrain the parameter space of possible seeding criteria, we combine the advantages of the cosmological IllustrisTNG (TNG) simulations with the flexibility of semi-analytic modeling. We identify TNG galaxies as BH seeding sites based on various criteria including a minimum gas mass of -, total host mass of -, and a maximum gas metallicity of . Each potential host is assigned a BH seed with a probability of ; these BHs are then traced through the TNG galaxy merger tree. This approach improves upon the predictive power of the simple TNG BH seeding prescription, especially in the low-mass regime at high redshift, and it is readily adaptable to other…
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Taxonomy
TopicsAstronomy and Astrophysical Research · Galaxies: Formation, Evolution, Phenomena · Radio Astronomy Observations and Technology
