Informal Astro Talk
An optimization-based approach to neutrino flavor evolution in core-collapse supernovae
We assess the utility of an optimization-based data assimilation (D.A.) technique for treating the problem of nonlinear neutrino flavor transformation in core collapse supernovae. Our motivation is to explore an "integration-blind" technique for eventual application to cases that present difficulties for traditional numerical integration---inelastic back-scattering, for example. Here we consider a simple steady-state model involving two neutrino beams and forward-scattering only. As this model can be solved via numerical integration, we have an independent consistency check for D.A. solutions. We find that the procedure can capture key features of flavor evolution over the entire trajectory, even given measurements of neutrino flavor only at the two endpoints. Further, the procedure permits an examination of the sensitivity of flavor evolution to estimates of unknown model parameters, and it efficiently identifies locations of degeneracies in parameter space. D.A. offers the opportunity to determine, for more realistic larger-scale models, which components of the corresponding physical system must be measured in order to yield complete information regarding unknown model parameters and flavor evolution histories.