Efforts to incorporate neutrino Fast Flavor Instability in merger simulations

Neutrino flavor oscillation in compact object mergers will significantly affect the merger dynamics and the electron fraction. Particularly, Fast Flavor Instability close to the central object in neutron star merger simulations can change r-process abundance. Over the years, various approaches have been taken to incorporate flavor oscillation during post-processing, while a few recent works have included it in situ. However, given the high cost of numerical transport, solving the quantum kinetic equation directly in a merger simulation is far from feasible. In this talk, I will present our efforts to incorporate Fast Flavor Oscillation (FFO) in mergers using subgrid modeling. I will present a machine-learning model and an analytical mixing scheme that can predict the outcome of FFO on post-merger snapshots and compare their performance. I will also discuss the challenges of incorporating these models into the available neutrino transport scheme.