The correlations of stellar tidal disruption rates with properties of massive black holes and their host galaxies

Abstract

Stars can be either disrupted as tidal disruption events (TDEs) or swallowed as a whole by massive black holes (MBHs) at galactic centers when they approach sufficiently close to these MBHs. In this work, we investigate the correlations of such stellar consumption rates with both the MBH mass $M_{\mathrm{bh}}$ and the inner slope of the host galaxy mass density distribution $\alpha$. We introduce a simplified analytical power-law model with a power-law stellar mass density distribution surrounding MBHs and separate the contributions of two-body relaxation and stellar orbital precession for the stellar orbital angular momentum evolution in nonspherical galaxy potentials. The stellar consumption rates derived from this simplified model can be well consistent with the numerical results obtained with a more realistic treatment of stellar distributions and dynamics around MBHs, providing an efficient way to estimate TDE rates. The origin of the correlations of stellar consumption rates with $M_{\mathrm{bh}}$ and $\alpha$ are explained by the dependence of this analytical model on those MBH/host galaxy properties and by the separation of the stellar angular momentum evolution mechanisms. We propose that the strong positive correlation between the rates of stellar consumption due to two-body relaxation and $\alpha$ provides one interpretation for the overrepresentation of TDEs found in some rare E+A/poststarburst galaxies. We find high TDE rates for giant stars, up to those for solar-type stars. The understanding of the origin of the correlations of the stellar consumption rates will be necessary for obtaining the demographics of MBHs and their host galaxies via TDEs.

17 pages, 6 figures, ApJ in press

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Cited by in corpus (2)

• An Explanation for Overrepresentation of Tidal Disruption Events in Post-starburst Galaxies
• Self-consistent Solutions of Evolving Nuclear Star Clusters with Two-Dimensional Monte-Carlo Dynamical Simulations