Clustering of magnetic reconnection exhausts in the solar wind: An automated detection study

Abstract

Context. Magnetic reconnection is a fundamental process in astrophysical plasmas that enables the dissipation of magnetic energy at kinetic scales. Detecting this process in situ is therefore key to furthering our understanding of energy conversion in space plasmas. However, reconnection jets typically scale from seconds to minutes in situ, and as such, finding them in the decades of data provided by solar wind missions since the beginning of the space era is an onerous task. Aims. In this work, we present a new approach for automatically identifying reconnection exhausts in situ in the solar wind. We apply the algorithm to Solar Orbiter data obtained while the spacecraft was positioned at between 0.6 and 0.8 AU and perform a statistical study on the jets we detect. Methods. The method for automatic detection is inspired by the visual identification process and strongly relies on the Walén relation. It is enhanced through the use of Bayesian inference and physical considerations to detect reconnection jets with a consistent approach. Results. Applying the detection algorithm to one month of Solar Orbiter data near 0.7 AU, we find an occurrence rate of seven jets per day, which is significantly higher than in previous studies performed at 1 AU. We show that they tend to cluster in the solar wind and are less likely to occur in the tenuous solar wind (< 10 cm−3 near 0.7 AU). We discuss why the source and the degree of Alfvénicity of the solar wind might have an impact on magnetic reconnection occurrence. Conclusions. By providing a tool to quickly identify potential magnetic reconnection exhausts in situ, we pave the way for broader statistical studies on magnetic reconnection in diverse plasma environments.