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The Solar Memory From Hours to Decades View all abstracts by submitter

Markus J. Aschwanden   Submitted: 2021-07-29 11:43

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 \lambda(t) ∝ t^p with a polynomial function, which allows us to distinguish linear (p ≈ 1) from nonlinear (p ≳ 2) events. The power law slopes α of observed waiting times (with full solar cycle coverage) cover a range of α =2.1-2.4, which agrees well with our prediction of α = 2.0+1/p = 2.3-2.5. The memory time can also be defined with the time evolution of the logistic equation, for which we find a relationship between the nonlinear growth time τ_G = τrise/(4p) and the nonlinearity index p. We find a nonlinear evolution for most events, in particular for the clustering of solar flares (p=2.2±0.1), partially occulted flare events (p=1.8±0.2), and the solar dynamo (p=2.8±0.5). The Sun exhibits memory on time scales of ≈2 hours to 3 days (for solar flare clustering), 6 to 23 days (for partially occulted flare events), and 1.5 month to 1 year (for the rise time of the solar dynamo).

Authors: Aschwanden, M.J. and Johnson, J.R.
Projects: None

Publication Status: submitted
Last Modified: 2021-08-01 20:58
Go to main E-Print page  A physics-based method that can predict imminent large solar flares  Solar chromosphere heating and generation of plasma outflows by impulsively generated two-fluid Alfvn waves  Edit Entry  Download Preprint  Submitter's Homepage Delete Entry 

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