1. Methods for automatic processing • Requirements • Accurate enough • Useful for doing significant science • Accepted by majority of community • Robust • Useful on most of the solar disk • Errors limited • Fast enough • Real time • Post facto • Others?

2. Considerations • No manual intervention by definition • Excludes AZAM? • Semel: “locations with poor solutions are interesting” • Test auto methods against gold standard • Is AZAM the gold standard? • Any auto method will leave some discontinuities (some may be real, some due to noise or algorithm problems)

3. Considerations • May not need to disambiguate every image in a time series (but, flare changes) • Photospheric magnetic field is intermittent, not continuous, so prefer a method that minimizes dependence on continuity

4. Meeting the requirements • Only c2 and c3 seem promising enough (pending noise sensitivity tests) • Need to accelerate these by a large factor (but seems possible by coding in C) • Is there hope of improving other methods? • Is there some new approach that is better?

5. Personal opinion • The more good additional information that can be added to the c2/3 error metrics, the better (e.g. height gradient of |B| or div BHorizontal) • A hybrid approach may be helpful (one method for network and another for active regions) • Are we fooling ourselves with non-linear spatial averaging of real solar fields? • Should work harder on getting physically useful information that does not depend upon disambiguation