Statistics of solar wind electron breakpoint energies using machine learning techniques

Abstract

<jats:p>Solar wind electron velocity distributions at 1 au consist of a thermal “core” population and two suprathermal populations: “halo” and “strahl”. The core and halo are quasi-isotropic, whereas the strahl typically travels radially outwards along the parallel or anti-parallel direction with respect to the interplanetary magnetic field. Using Cluster-PEACE data, we analyse energy and pitch angle distributions and use machine learning techniques to provide robust classifications of these solar wind populations. Initially, we used unsupervised algorithms to classify halo and strahl differential energy flux distributions to allow us to calculate relative number densities, which are of the same order as previous results. Subsequently, we applied unsupervised algorithms to phase space density distributions over ten years to study the variation of halo and strahl breakpoint energies with solar wind parameters. In our statistical study, we find both halo and strahl suprathermal breakpoint energies display a significant increase with core temperature, with the halo exhibiting a more positive correlation than the strahl. We conclude low energy strahl electrons are scattering into the core at perpendicular pitch angles. This increases the number of Coulomb collisions and extends the perpendicular core population to higher energies, resulting in a larger difference between halo and strahl breakpoint energies at higher core temperatures. Statistically, the locations of both suprathermal breakpoint energies decrease with increasing solar wind speed. In the case of halo breakpoint energy, we observe two distinct profiles above and below 500 km s<jats:sup>−1</jats:sup>. We relate this to the difference in origin of fast and slow solar wind.</jats:p>

Ambipolar Electric Field and Potential in the Solar Wind Estimated from Electron Velocity Distribution Functions

“…At radial distances between 1 and 3 au, they find that E BP /T cP varies between 1 and 4 and depends mainly on the density of the modeled solar wind. In a more recent study, including Cluster data, Bakrania et al (2020) obtain the ratio of 5.5 at 1 au as well as an anti-correlation between the strahl-E BP and the solar wind velocity.…”

Parker Solar Probe observations of suprathermal electron flux enhancements originating from Coronal Hole boundaries

“…Here we focus on peaks in suprathermal electron flux at stream interfaces, as reported by Crooker et al (2010). Electrons in the solar wind have a suprathermal component (breakpoint around 40-50 eV at 1 AU, Bakrania, M. R. et al 2020), which is composed primarily of a quasi-isotropic halo, and a field-aligned, anti-sunward, beam known as the 'strahl'. Velocity filtration arguments, in which electrons inhabiting the high energy tails of the coronal electron velocity distribution possess sufficient energy to escape into the solar wind, are one explanation for the existence of these populations in the solar wind (Feldman et al 1975;Scudder 1992a,b;Maksimovic et al 1997).…”

Radial evolution of thermal and suprathermal electron populations in the slow solar wind from 0.13 to 0.5 au : Parker Solar Probe Observations

“…We have applied a new fitting routine to electron VDF measurements, which for the first time incorporates breakpoint energies obtained from a machine learning algorithm (Bakrania et al 2020). This new technique was applied to a large data set of PSP SPAN observations at varying distance from the Sun.…”

“…However the K-means algorithm is now finding the 'break' in pitch angle. A detailed description of this method and an analysis of its effectiveness is provided by Bakrania et al (2020). Arthur (2007) details a comprehensive and more general account of the K-means algorithm.…”