Article

Abstract

• We simulate with 3D particle in cell, the spontaneous formation of turbulent outflows in an initially laminar 3D reconnecting current layer. We observe the formation of many secondary current layers and reconnection sites in the outflow. The approach we follow is to study each individual feature within the turbulent outflow. To identify all clusters of current in the outflow we use a clustering technique widely used in unsupervised machine learning: density-based spatial clustering of applications with noise. Once the clusters are identified we measure their size and compute reconnection indicators to establish which are undergoing reconnection. With this analysis we establish that the size of the current clusters reaches all the way from its initial system scale down to subelectron skin depth scale. We observe that the smaller current clusters are more prone to reconnecting and to releasing energy. We then find the process of reconnection of the smaller current cluster to be of the recently observed electron-only type that leaves the ions essentially unaffected.

Creator

• Goldman, Martin V
• Newman, David L
• Lapenta, Giovanni
• Eriksson, Stefan

Date Issued

• 2022

Academic Affiliation

• Laboratory for Atmospheric & Space Physics

Journal Title

• The Astrophysical Journal: an international review of astronomy and astronomical physics Journal

Journal Issue/Number

• 2

Journal Volume

• 940

Last Modified

• 2024-11-20

Resource Type

• Article

Rights Statement

• In Copyright

DOI

•  https://doi.org/10.3847/1538-4357/ac98bc

ISSN

• 0004-637X

Language

• English [eng]

License

• Creative Commons BY Attribution 4.0 International

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