The Solar Memory From Hours to Decades
Markus J. Aschwanden, Jay R. Johnson

TL;DR
This paper analyzes solar flare waiting times to classify the Sun's dynamical systems, revealing different memory timescales from hours to months and establishing a relationship between flare activity and nonlinear growth models.
Contribution
It introduces a method to distinguish linear and nonlinear solar events using waiting time distributions and polynomial growth models, advancing understanding of solar activity dynamics.
Findings
Power law slopes of waiting times range from 2.1 to 2.4, matching predictions.
Most solar events exhibit nonlinear evolution with specific growth time relationships.
Memory timescales vary from hours for flare clustering to months for the solar dynamo.
Abstract
Waiting time distributions allow us to distinguish at least three different types of dynamical systems, such as (i) linear random processes (with no memory); (ii) nonlinear, avalanche-type, nonstationary Poisson processes (with memory during the exponential growth of the avalanche rise time); and (iii) chaotic systems in the state of a nonlinear limit cycle (with memory during the oscillatory phase). We describe the temporal evolution of the flare rate with a polynomial function, which allows us to distinguish linear () from nonlinear () events. The power law slopes of observed waiting times (with full solar cycle coverage) cover a range of , which agrees well with our prediction of . The memory time can also be defined with the time evolution of the logistic equation, for which we…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
