This project will create simulations of the growth of galaxies and supermassive black holes over cosmic time. The simulations produced as part of this project will use techniques that provide much higher resolution of the inner regions of galaxies where gas is falling into the central supermassive black hole and emitting radiation that influences the rate at which gas can continue to fall in. The increased resolution allows for more accurate modeling of the physics involved in the interaction between gas in the galaxy and the growth of the supermassive black hole. The project will also use these simulations to train undergraduate students in developing visualizations from large data sets. These students will be drawn from populations that are underrepresented in the sciences.
The project will perform high resolution cosmological hydrodynamic simulations of the growth of galaxies. It will incorporate better multi-phase gas physics from the interstellar medium of galaxies along with explicit treatments of black hole growth and feedback on sub-parsec scales comparable to the size of the accretion disk. The simulations will be done using a novel hyper-Lagrangian refinement technique that increases the resolution dramatically near the black hole. The simulations will help to identify the mechanisms responsible for gas transport across large scales and eventually fueling AGN. They will improve our understanding of the impact of accretion-disk winds and radiative AGN feedback prescriptions for larger scale cosmological simulations, and will help to interpret galaxy and massive black hole observables across redshifts. The project will involve undergraduates and graduates directly in the research and will support undergraduates in a program that will recruit underrepresented groups to work on developing Python-based visualizations of the results of the project.
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.
