Collaborative Research: Hunting for Warped Accretion Disks and Jets around Supermassive Black Holes

Recent years have seen dramatic advances in our understanding of black holes and the accretion disks feeding them. The Event Horizon Telescope (EHT) is an array of radio telescopes spread out across the Earth, which can spatially resolve the event horizon of nearby supermassive black holes. One of the biggest outstanding questions is whether the accretion disk is spinning in the same direction as the black hole or is tilted with respect to the black hole.

In such tilted systems the accretion disk can get warped. In this collaborative project, the PIs will leverage recent improvements to the EHT array with advances in (machine-learning based) image-reconstruction algorithms and high resolution numerical simulations to look for signatures of warping in EHT observations. The PIs will involve junior scientists including undergraduates and high school students in their groups, and will actively recruit students from marginalized identities for these positions.

The PIs will also engage with the public through the media and public talks, and they will strive to develop visually stunning and informative materials to accompany the main results.

The PIs will develop and analyze an extensive general relativistic magnetohydrodynamic (GRMHD) simulation library that spans a wide range of parameters. Their simulations will include the effects of accretion disk tilt, account for the two-temperature nature of the plasma, and incorporate the effects of radiative cooling. Tilt is particularly interesting, since recent numerical simulations demonstrated that warps form in tilted accretion disks around spinning black holes.

Warped disks in high-accretion rate sources may form nozzle shocks, which dissipate energy orders of magnitude faster than magneto-rotational instability (MRI) driven turbulence. Subsequently, the PIs will compare their new simulation library with EHT observations. In addition, they have developed a new dictionary learning algorithm using simulations as a training set to more accurately analyze EHT data.

Their algorithm does not suffer from spurious artifacts such as bright "knots" seen along the ring in previous EHT images, and it achieves a significantly higher spatial resolution than traditional image reconstruction methods.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.