Automated force-free flux rope identification

Abstract

We describe a method developed to automatically identify quasi force‐free magnetotail flux ropes from in situ spacecraft magnetometer data. The method locates significant (greater than 1σ) deflections of the north‐south component of the magnetic field coincident with enhancements in other field components. The magnetic field data around the deflections are then processed using Minimum Variance Analysis (MVA) to narrow the selection down to those that exhibit the characteristics of flux ropes. The subset of candidates that fulfills the requirements are then compared to a cylindrical, linear (constant‐α) force‐free model. Those that can be well approximated as force free are then accepted. The model fit also provides a measure of the physical parameters that describe the flux rope (i.e., core field and radius). This process allows for the creation of a repeatable, consistent catalog of flux ropes. Automation allows a greater volume of data to be covered, saving time and allowing the exploration of potential selection biases. The technique is applied to MESSENGER (MErcury Surface, Space ENvironment, GEochemistry, and Ranging) magnetometer data in the Hermean magnetotail and successfully locates flux ropes, some of which match previously known encounters. Assumptions of the method and potential future applications are discussed

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