Abstract

Ion velocity distribution functions in solar wind are often found to be non-Maxwellian. Streams of accelerated particles and temperature anisotropies are typical non-thermal features, whose origin is debated since the early years of in situ measurements. In order to disentangle the kinetic processes which may play a role in the generation of such distortions, particle double streams need to be identified and isolated. To this purpose, we have developed a numerical approach that leverages the clustering technique employed in machine learning. Here, we present the results obtained applying our technique to the ion distribution functions of a typical fast Alfvénic wind stream observed by Solar Orbiter-PAS in mid-September 2022, at a heliocentric distance of about 0.58 au. We could separate up to four ion families, namely proton core and beam and alpha core and beam. This allows us to characterize and compare their features, like the relative densities and temperatures. Differently from the better-known proton beam, alpha beam represents a relevant fraction of the alpha population, around 40%. Separating such a massive beam may shed new light on alpha kinetic features like the anomalous overheating mechanism. Moreover, the study of the velocity drift of the various ion populations indicates that both the alpha core and the alpha beam are sensitive to the Alfvénic fluctuations, and the surfing effect found in literature can be recovered only when considering the core and the beam as a single population. The similarities between proton and alpha beams would suggest a common generation mechanism, apparently due to local physical conditions in the plasma.    

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