Astro Seminar Series - VIA ZOOM

Wednesday, January 11, 2023 11:30 am - 11:30 am EST (GMT -05:00)
Angelo Ricarte

Dr. Angelo Ricarte is a theoretical astrophysicist and Black Hole Initiative (BHI) fellow at the BHI at Harvard University.  He completed his undergraduate education at the University of California at Berkeley in 2013 before completing a Ph.D. in astronomy at Yale University in 2019.  Angelo studies supermassive black holes from event horizon to cosmological scales, having worked on topics including black hole-galaxy coevolution across cosmic time, signatures of black hole "seeding" in the early universe, and most recently, theoretical interpretation of spatially resolved black hole images.  He is an active member of the Event Horizon Telescope collaboration, within which he produces simulated images from general relativistic magnetohydrodynamics simulations and tries to bridge the gap between observations and theory.

Title: Unveiling Black Hole Accretion with the Event Horizon Telescope--and Beyond

Abstract: Using a global very long baseline interferometry (VLBI) network, the Event Horizon Telescope (EHT) collaboration has produced the first spatially resolved images of black holes on horizon scales.  This has given us an opportunity to test models of black hole accretion flows on these scales for the first time, constraining parameters such as black hole spin, magnetic field state, and the electron temperature.  Polarized data of M87* prefer a magnetically arrested disk with strong poloidal fields, and the same may be true for Sgr A* as well.  Moving forward, the next-generation Event Horizon Telescope (ngEHT) aims to make polarized, multi-frequency movies with improved dynamic range that can simultaneously image disk and jet.  Future data products will hopefully include circular polarization, spectral index maps, and rotation measure maps, each of which provides new insights into aspects of the accretion flow. These data provide important insights into the astrophysics black hole accretion and jets, which we can use to improve sub-grid models in galaxy-scale simulations.