Issue |
A&A
Volume 699, July 2025
|
|
---|---|---|
Article Number | L6 | |
Number of page(s) | 8 | |
Section | Letters to the Editor | |
DOI | https://doi.org/10.1051/0004-6361/202555087 | |
Published online | 07 July 2025 |
Letter to the Editor
Statistical properties of beam-driven upper-hybrid wave turbulence in the solar wind
1
Laboratoire de Physique des Plasmas (LPP), CNRS, Sorbonne Université, Observatoire de Paris, Université Paris-Saclay, Ecole polytechnique, Institut Polytechnique de Paris, 91120 Palaiseau, France
2
Institut Universitaire de France (IUF), Paris, France
3
Izmiran, Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation, Moscow, Russia
⋆ Corresponding author: annenkov.phys@gmail.com
Received:
8
April
2025
Accepted:
13
June
2025
We studied the statistical properties of beam-driven upper-hybrid wave turbulence in the solar wind by focusing on the probability density functions (PDFs) of electric field amplitudes, |E|. We used, for the first time, high-resolution and long-term 2D particle-in-cell simulations of the interaction of an electron beam with a magnetized plasma to calculate and analyse the skewness (degree of anisotropy) and the kurtosis (degree of flatness) of the PDFs of |E| and log|E|2 for various intensities of plasma magnetization (Ω = ωc/ωp) and average levels of random density fluctuations (ΔN). Using the Pearson classification, we show that the PDFs of log|E|2 predominantly align with Type VI Pearson distributions, with a shift towards Type I at high plasma magnetizations. In contrast, the PDFs of |E| are Type I Pearson distributions regardless of the Ω and ΔN values. Comparisons between simulation results and observations by the Solar Orbiter’s Time Domain Sampler instrument show a good agreement. This study also offers a promising method for understanding the dynamics of wave turbulence and indirectly estimating plasma magnetization.
Key words: plasmas / waves / Sun: flares / solar wind
© The Authors 2025
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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