Correlations Between Black Holes and Host Galaxies in the Illustris and IllustrisTNG Simulations (1910.00017v1)

Abstract: We study black hole - host galaxy correlations, and the relation between the over-massiveness (the distance from the average $M_{BH}-\sigma$ relation) of super-massive black holes (SMBHs) and star formation histories of their host galaxies in the Illustris and TNG100 simulations. We find that both simulations are able to produce black hole scaling relations in general agreement with observations at $z=0$, but with noticeable discrepancies. Both simulations show an offset from the observations for the $M_{BH}-\sigma$ relation, and the relation between $M_{BH}$ and the Sersic index. The relation between $M_{BH}$ and stellar mass $M_$ is tighter than the observations, especially for TNG100. For massive galaxies in both simulations, the hosts of over-massive SMBHs (those above the mean $M_{BH}-\sigma$ relation) tend to have larger Sersic indices and lower baryon conversion efficiency, suggesting a multidimensional link between SMBHs and properties of their hosts. In Illustris, the hosts of over-massive SMBHs have formed earlier and have lower present-day star formation rates, in qualitative agreement with the observations for massive galaxies with $\sigma>100 \rm km/s$. For low-mass galaxies, such a correlation still holds in Illustris but does not exist in the observed data. For TNG100, the correlation between SMBH over-massiveness and star formation history is much weaker. The hosts of over-massive SMBHs generally have consistently larger star formation rates throughout history. These galaxies have higher stellar mass as well, due to the strong $M_{BH}-M_$ correlation. Our findings show that simulated SMBH scaling relations and correlations are sensitive to features in the modeling of SMBHs.

• The paper finds that simulated SMBH-host galaxy scaling relations broadly align with observations but show notable offsets, especially in stellar velocity dispersions.
• The paper highlights that the TNG100 simulation produces a tighter M_BH–M_* relation and introduces horizontal bands linked to AGN feedback thresholds.
• The paper indicates that discrepancies in SMBH mass and host galaxy properties point to variations in AGN feedback effectiveness, influencing galaxy quenching processes.

Overview of Black Hole and Host Galaxy Correlations in Illustris and IllustrisTNG Simulations

The paper "Correlations Between Black Holes and Host Galaxies in the Illustris and IllustrisTNG Simulations" explores the intricate relationships between supermassive black holes (SMBHs) and their host galaxies, as modeled in the cosmological simulations of Illustris and TNG100. The paper is aimed at understanding not only the existing scaling relations between SMBHs and various properties of their host galaxies but also at exploring the implication of these relations for galaxy evolution and the physics underpinning AGN feedback mechanisms.

Key Findings

1. Black Hole Scaling Relations: Both Illustris and TNG100 simulations yield SMBH scaling relations that generally align with observational data yet exhibit notable discrepancies. Particularly, the relation between black hole mass ($M_{BH}$) and stellar velocity dispersion ($\sigma$) appears offset, with simulations underscoring slightly lower $\sigma$ values for given $M_{BH}$ due to potentially inflated galaxy sizes. TNG100 notably produces a tighter $M_{BH}$-stellar mass ($M_*$) relation, suggesting an overemphasis on how stellar mass influences black hole growth in this simulation framework.
2. Impact of Simulation Features: TNG100 introduces notable features in SMBH scaling relations, such as horizontal bands near $M_{BH} \sim 10^8 M_\odot$, tied to the feedback transition threshold. This deviation from observations could indicate overly effective feedback that impairs subsequent black hole and galaxy growth.
3. Implications of Over-Massiveness: For massive galaxies, (certain Illustris galaxies exhibiting higher $M_{BH}$ than the mean $M_{BH}-\sigma$ relation), these tend to have early-forming host galaxies with lower present-day star formation rates. This correlation implies SMBH over-massiveness might be orchestrating a swifter quenching process. Nonetheless, TNG100 does not replicate this linkage, possibly due to its excessive feedback effectiveness once black holes exceed a critical mass threshold.
4. Low-Mass Galaxy Dynamics: In Illustris, smaller galaxies also reflect a correlation between SMBH over-massiveness and the star formation history, opposing observational claims that such correlations should be minimal. This finding highlights possible differences in feedback processing between low and high-mass systems within the simulations or suggests observational biases.

Implications for Cosmological Simulations

The findings from the Illustris and TNG100 simulations accentuate the nuanced role of AGN feedback in shaping galaxy evolution. Discrepancies between the simulation outputs and empirical observations illuminate areas where the AGN feedback models might require refinements, particularly in terms of its scaling with $M_{BH}$ and star formation suppression efficacy. This paper affirms the complexity of simulating galaxy evolution, sympathizing with the interconnected nature of galactic mass assembly, black hole growth, and feedback processes.

Future Directions

Future developments in cosmological simulations might focus on enhancing the resolution and fidelity of SMBH feedback models. Fine-tuning the transition points between feedback modes based on the intrinsic properties of SMBHs and their host galaxies, rather than fixed thresholds, may yield more coherent simulation outputs aligned with observational data. Additionally, investigating the stochastic variability in SMBH accretion and the multiplicity of feedback mechanisms across different galaxy environments could further elucidate the emergent SMBH-host galaxy correlations.

Overall, this paper underscores the vital interaction between newly developed simulation models and empirical observations, guiding considerations in model refinement to better mimic the observed universe's complexity.