English

Statistical analysis of intermittency and its association with proton heating in the near Sun environment

Solar and Stellar Astrophysics 2022-03-14 v2 Plasma Physics Space Physics

Abstract

We use data from the first six encounters of Parker Solar Probe and employ the Partial Variance of Increments (PVIPVI) method to study the statistical properties of coherent structures in the inner heliosphere with the aim of exploring physical connections between magnetic field intermittency and observable consequences such as plasma heating and turbulence dissipation. Our results support proton heating localized in the vicinity of, and strongly correlated with, magnetic structures characterized by PVI1PVI \geq 1. We show that on average, such events constitute 19%\approx 19\% of the dataset, though variations may occur depending on the plasma parameters. We show that the waiting time distribution (WTWT) of identified events is consistent across all six encounters following a power-law scaling at lower WTsWTs. This result indicates that coherent structures are not evenly distributed in the solar wind but rather tend to be tightly correlated and form clusters. We observe that the strongest magnetic discontinuities, PVI6PVI \geq 6, usually associated with reconnection exhausts, are sites where magnetic energy is locally dissipated in proton heating and are associated with the most abrupt changes in proton temperature. However, due to the scarcity of such events, their relative contribution to energy dissipation is minor. Taking clustering effects into consideration, we show that smaller scale, more frequent structures with PVI between, 1PVI61\lesssim PVI \lesssim 6, play the major role in magnetic energy dissipation. The number density of such events is strongly associated with the global solar wind temperature, with denser intervals being associated with higher TpT_{p}.

Keywords

Cite

@article{arxiv.2201.10067,
  title  = {Statistical analysis of intermittency and its association with proton heating in the near Sun environment},
  author = {Nikos Sioulas and Marco Velli and Rohit Chhiber and Loukas Vlahos and William H. Matthaeus and Riddhi Bandyopadhyay and Manuel E. Cuesta and Chen Shi and Trevor A. Bowen and Ramiz A. Qudsi and Michael L. Stevens and Stuart D. Bale},
  journal= {arXiv preprint arXiv:2201.10067},
  year   = {2022}
}

Comments

Accepted for publication in APJ