Inductive magnetic footpoint tracking by combining the minimum energy fit with the local correlation tracking and doppler velocity

Time-dependent magneto-hydrodynamic simulations of active region coronal magnetic field require the underlying photospheric magnetic footpoint velocities. The minimum energy fit (MEF) is a new velocity inversion technique to infer the photospheric magnetic footpoint velocities using a pair of vector magnetograms, introduced by Longcope (2004). The MEF selects the smallest overall flow from several consistent flows by minimizing an energy functional. The inferred horizontal and vertical flow fields by the MEF can be further constrained by incorporating the partial or imperfect velocity information obtained through independent means. This hybrid method is expected to give a velocity close to the true magnetic footpoint velocity. Here, we demonstrate that a combination of the MEF, the local correlation tracking (LCT) and Doppler velocity is capable of inferring the velocity close to the photospheric flow.