Inversions Real?

One of the biggest challenges for inversion is to take seriously the issue of what is the level of confidence in features in the solution

Issues It’s time inverters started working harder – discoveries are to be made in the subtle signatures in flows and structure. –Beat down the systematics –Make better assessment of input errors –Properly take into account error correlations

Issues It’s time inverters started working harder – discoveries are to be made in the subtle signatures in flows and structure. –Beat down the systematics –Make better assessment of input errors –Properly take into account error correlations Need to do better with near-surface –Incorporate high-l data Kernels need to take into account the way freqs are measured –How to incorporate local helioseismic data: 3D models in C.Z. ? –Make higher-order representations of “surface term”

Issues It’s time inverters started working harder – discoveries are to be made in the subtle signatures in flows and structure. –Beat down the systematics –Make better assessment of input errors –Properly take into account error correlations Need to do better with near-surface –Incorporate high-l data Kernels need to take into account the way freqs are measured –How to incorporate local helioseismic data: 3D models in C.Z. ? –Make higher-order representations of “surface term” Reconcile linear and non-linear (e.g. Vorontsov) methods

Issues It’s time inverters started working harder – discoveries are to be made in the subtle signatures in flows and structure. –Beat down the systematics –Make better assessment of input errors –Properly take into account error correlations Need to do better with near-surface –Incorporate high-l data Kernels need to take into account the way freqs are measured –How to incorporate local helioseismic data: 3D models in C.Z. ? –Make higher-order representations of “surface term” Reconcile linear and non-linear (e.g. Vorontsov) methods Improve kernels for asphericities

Issues It’s time inverters started working harder – discoveries are to be made in the subtle signatures in flows and structure. –Beat down the systematics –Make better assessment of input errors –Properly take into account error correlations Need to do better with near-surface –Incorporate high-l data Kernels need to take into account the way freqs are measured –How to incorporate local helioseismic data: 3D models in C.Z. ? –Make higher-order representations of “surface term” Reconcile linear and non-linear (e.g. Vorontsov) methods Improve kernels for asphericities Test whole inference procedures with data from C.Z. simulations