Preliminary Statistical Analysis of Magnetic Switchbacks with an Automated Algorithm during Parker Solar Probe Encounters 

Under ideal conditions, open magnetic field lines originating from the Sun follow the Parker Spiral topology. In reality, conditions are often not ideal and deflections in field lines from this path are observed. A class of these deflections, known as magnetic switchbacks, are accompanied by correlated velocity enhancements, revealing a highly Alfvénic behavior. Even though this phenomenon was previously identified in in-situ data at distances between 0.3-3 au from missions such as Helios and Ulysses in 1990s, the interest in the scientific community increased when Parker Solar Probe (PSP) revealed the unexpectedly frequent nature of these structures at closer distances to the Sun. In light of this discovery, the formulation of a solid definition and the development of robust detection methods became crucial for further analysis, as this interest brought along various views on the definition and the properties of switchbacks. So far, the research has relied mainly on manual or semi-automatic detection methods which are both time consuming with the increasing amount of data and prone to subjective interpretation that might result in significant differences across studies. To address this issue, we have developed a fully automated detection algorithm to minimize the subjectivity and the time required to analyze the data. The algorithm relies on the two fundamental characteristics of switchbacks: the deflection angle from the Parker spiral and the degree of Alfvénicity. Using these properties, we apply multiple detection criteria with varying thresholds to reveal how switchback properties depend on the chosen definitions. We will present our preliminary results focusing on the occurrence rate and duration of the switchbacks at different heliodistances during the first 21 PSP encounters.