Speaker
Description
Solar flares are transient energetic events triggered by electromagnetic plasma instabilities arising within regions of the solar corona. These events are characterized by a broadband radiative emission and energetic particle release and, in synergy with other transient solar phenomena, play a key role in shaping space climate. Despite decades of observations, the statistical properties and physical mechanisms underlying flare occurrence remain incompletely understood, limiting our ability to develop robust predictive models.
In this study, we analyze the solar soft X-ray emission measured by the GOES mission from January 2002 to December 2024 to investigate the statistical properties of interevent times between flares. Consistent with previous work, we find that the interevent time distribution follows a power law behavior across timescales ranging from 10^2 to 10^5 minutes, indicative of scale invariance. More notably, we report for the first time that the interevent time distribution is also invariant under scale transformation, i.e., flare flux integral selection, an unexpected property that significantly narrows the class of viable physical models.
By analyzing the fluctuations in the GOES time series and comparing them with theoretical expectations from the literature, we find that the observed behavior is consistent with the statistical properties of magnetohydrodynamic turbulence. This provides strong evidence that the flare timing is not stochastic but governed by underlying physical processes that are, in principle, predictable.
Our results suggest that solar flares, while complex, may be predicted within a physically constrained framework.
