Status: this preprint is currently under review for the journal NPG.
Cairns-Tsallis distribution applied to differences of magnetic field intensity in solar wind
Ewin Sánchezand Pedro Vega-Jorquera
Abstract. Relevance of the Cairns-Tsallis probability distribution in its application to time series of spatial magnetic field differences is shown. In particular, we explore its ability to explain the data obtained by the Ulysses mission during solar cycles 23 and 24. Our findings reveal that the Cairns-Tsallis density function provides an optimal fit to the data, showing a sensitivity to the small time scale of magnetic field changes. Fit parameters obtained with this model were analyzed, as well as some multifractal indices obtained through corresponding time series analysis. Furthermore, significant discrepancies have been identified between our results and those obtained by other authors, highlighting the appropriateness of the Cairns-Tsallis distribution in capturing the underlying complexity in the data.
Received: 04 Sep 2024 – Discussion started: 07 Oct 2024
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We explored how the Cairns-Tsallis probability density function better explains changes in the solar wind's magnetic field. By analyzing data from NASA's Ulysses mission, we found that this model provides a more accurate fit, particularly during periods of high solar activity. This improvement helps us understand the complex behaviors of the solar wind, which plays a crucial role in the interactions between the Sun and planets.
We explored how the Cairns-Tsallis probability density function better explains changes in the...