Memory effects in turbulent transport
Alexander Hubbard, Axel Brandenburg (Nordita)

TL;DR
This paper investigates how turbulent transport in magnetic fields and passive scalars exhibits memory effects, depending on the past history of the mean field, and introduces integral kernels to model these effects.
Contribution
The study demonstrates the presence of memory effects in turbulent transport and develops analytical models for integral kernels to better predict mean field growth or decay.
Findings
Memory effects depend on the frequency or growth rate of the mean field.
Integral kernels can accurately describe the characteristic timescale of memory effects.
Steady state transport coefficients may misestimate dynamo growth rates.
Abstract
In the mean-field theory of magnetic fields, turbulent transport, i.e. the turbulent electromotive force, is described by a combination of the alpha effect and turbulent magnetic diffusion, which are usually assumed to be proportional respectively to the mean field and its spatial derivatives. For a passive scalar there is just turbulent diffusion, where the mean flux of concentration depends on the gradient of the mean concentration. However, these proportionalities are approximations that are valid only if the mean field or the mean concentration vary slowly in time. Examples are presented where turbulent transport possesses memory, i.e. where it depends crucially on the past history of the mean field. Such effects are captured by replacing turbulent transport coefficients with time integral kernels, resulting in transport coefficients that depend effectively on the frequency or the…
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