Resolving the Azimuthal Ambiguity in Vector Magnetogram Data with the Divergence-Free Condition: Application to Discrete Data

TL;DR

This paper presents a method leveraging the divergence-free property of magnetic fields to resolve azimuthal ambiguity in solar vector magnetogram data, using synthetic tests to identify the most robust approach.

Contribution

It introduces a divergence minimization algorithm that effectively resolves ambiguity by utilizing derivatives of magnetic field components from discrete measurements.

Findings

The divergence minimization method is most robust.

Effective away from disk center with full derivative information.

Synthetic data tests validate the approach.

Abstract

We investigate how the divergence-free property of magnetic fields can be exploited to resolve the azimuthal ambiguity present in solar vector magnetogram data, by using line-of-sight and horizontal heliographic derivative information as approximated from discrete measurements. Using synthetic data we test several methods that each make different assumptions about how the divergence-free property can be used to resolve the ambiguity. We find that the most robust algorithm involves the minimisation of the absolute value of the divergence summed over the entire field of view. Away from disk centre this method requires the sign and magnitude of the line-of-sight derivatives of all three components of the magnetic field vector.