Computer Science – Numerical Analysis
Scientific paper
Jul 1994
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1994apj...429..391c&link_type=abstract
The Astrophysical Journal, Part 1 (ISSN 0004-637X), vol. 429, no. 1, p. 391-399
Computer Science
Numerical Analysis
20
Chaos, Flow Distribution, Magnetic Field Configurations, Numerical Analysis, Solar Magnetic Field, Geophysical Fluid Flow Cells, Small Perturbation Flow, Two Dimensional Models, White Noise
Scientific paper
We generate, both analytically and numerically, artifical, two-dimensional images composed of a known self-similar, and thus multifractal measured with added Gaussian white noise. These are used to interpret observed, line-of-sight, solar magnetic field distributions noisy multifractals. The range of self-similar scaling of observed, distributions is extended beyond that of previous work. Our interpretation of the data is then used to confront theoretical models for the generation of small-scale solar magnetic fields. We investigate the multifractial structure of the field generated by two-dimensional, random cell dynamos and find that self-similarity is relatively enhanced for more intermittent distributions and strong correlations between cells. An optimum value of the intercellular diffusion coefficient maximizes the degree of intermittency. The simulated field from a linear, kinematic, fast dynamo with two-dimensional, chaotic, 'ABC' flow displays scaling properties resembling those of observed solar fields. We suggest that the chaotic element of this model is the crucial ingredient for the long-range correlations that lead to multifractal scaling.
Cadavid Carlos A.
Kayleng-Knight A.
Lawrence John K.
Ruzmaikin Aleksandr
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