| Issue |
A&A
Volume 700, August 2025
|
|
|---|---|---|
| Article Number | A166 | |
| Number of page(s) | 9 | |
| Section | The Sun and the Heliosphere | |
| DOI | https://doi.org/10.1051/0004-6361/202555358 | |
| Published online | 15 August 2025 | |
Evidence of nonlinear signatures in the solar wind proton density at the L1 Lagrange point
Instituto de Fisica del Noroeste Argentino, CONICET and Universidad Nacional de Tucumán, Av. Independencia 1800, Tucuman CP 4000, Argentina
⋆ Corresponding author: djzamora@conicet.gov.ar
Received:
1
May
2025
Accepted:
30
June
2025
Context. The solar wind is a medium characterized by strong turbulence and significant field fluctuations on various scales. Recent observations have revealed that magnetic turbulence exhibits a self-similar behavior. Similarly, high-resolution measurements of the proton density have shown comparable characteristics, prompting several studies of the multifractal properties of these density fluctuations.
Aims. This work aims to investigate whether low-resolution measurements of the solar wind proton density exhibit nonlinear and multifractal structures. We also aim to interpret these features within the framework of non-extensive statistical mechanics.
Methods. We performed a systematic analysis of hourly resolution proton density data obtained from various spacecraft located at the Lagrange point L1, recorded over 17 years. We analyzed the multifractal nature of the fluctuations and tested for consistency with the q-triplet formalism from non-extensive statistical mechanics.
Results. We find that low-resolution solar wind proton density data also display nonlinear and multifractal signatures. Our analysis provides a validation of the q-triplet predicted by non-extensive statistical theory. To the best of our knowledge, this represents the most rigorous and systematic validation to date of the q-triplet in the solar wind.
Key words: plasmas / turbulence / solar wind / interplanetary medium
© 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.
This article is published in open access under the Subscribe to Open model. Subscribe to A&A to support open access publication.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.