Survey of Radiative, Two-Temperature Magnetically Arrested Simulations of the Black Hole M87* I: Turbulent Electron Heating
Abstract: We present a set of eleven two-temperature, radiative, general relativistic magnetohydrodynamic (2TGRRMHD) simulations of the black hole M87* in the magnetically arrested (MAD) state, surveying different values of the black hole spin $a_$. Our 3D simulations self-consistently evolve the temperatures of separate electron and ion populations under the effects of adiabatic compression/expansion, viscous heating, Coulomb coupling, and synchrotron, bremsstrahlung, and inverse Compton radiation. We adopt a sub-grid heating prescription from gyrokinetic simulations of plasma turbulence. Our simulations have accretion rates $\dot{M}=(0.5-1.5)\times10{-6}\dot{M}_{\rm Edd}$ and radiative efficiencies $\epsilon_{\rm rad}=3-35\%$. We compare our simulations to a fiducial set of otherwise identical single-fluid GRMHD simulations and find no significant changes in the outflow efficiency or black hole spindown parameter. Our simulations produce an effective adiabatic index for the two-temperature plasma of $\Gamma_{\rm gas}\approx1.55$, larger than the $\Gamma_{\rm gas}=13/9$ value often adopted in single-fluid GRMHD simulations. We find moderate ion-to-electron temperature ratios in the 230 GHz emitting region of $R=T_{\rm i}/T_{\rm e}{\approx}5$. While total intensity 230 GHz images from our simulations are consistent with Event Horizon Telescope (EHT) results, our images have significantly more beam-scale linear polarization ($\langle|m|\rangle\approx 30\%$) than is observed in EHT images of M87 ($\langle|m|\rangle<10\%$). We find a trend of the average linear polarization pitch angle $\angle\beta_2$ with black hole spin consistent with what is seen in single-fluid GRMHD simulations, and we provide a simple fitting function for $\angle\beta_2(a_*)$ motivated by the wind-up of magnetic field lines by black hole spin in the Blandford-Znajek mechanism.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.