6,021 research outputs found
Statistics of Solar Wind Electron Breakpoint Energies Using Machine Learning Techniques
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 and/or anti-parallel direction with
respect to the interplanetary magnetic field. With 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 use 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
apply 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.
We relate this to the difference in origin of fast and slow solar wind.Comment: Published in Astronomy & Astrophysics, 11 pages, 10 figure
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