Wrapping and unwrapping multifractal fields

Abstract

We develop a powerful yet simple method that generates multifractal fields with fully controlled scaling properties. Adopting the Multifractal Random Walk (MRW) model of Bacry et al. (2001), synthetic multifractal fields are obtained from the fractional integration of non-Gaussian fluctuations, built by a non-linear transformation of log-correlated Gaussian fields. The resulting fields are parameterized by their roughness exponent $H$, intermittency $\lambda$ and multifractal range ${\xi }_{\omega }$. We retrieve all the salient features of the MRW, namely a quadratic scaling exponent spectrum ${\zeta }_q$, fat-tail statistics of fluctuations, and spatial correlations of local volatility. Such features can be finely tuned, allowing for the generation of ideal multifractals mimicking real multi-affine fields. The construction procedure is then used the other way around to unwrap experimental data -- here the roughness map of a fractured metallic alloy. Our analysis evidences subtle differences with synthetic fields, namely anisotropic filamental clusters reminiscent of dissipation structures found in fluid turbulence.

9 pages, 8 figures

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Cited by in corpus (2)

• A spatio-temporal random synthetic turbulent velocity field: The underlying Gaussian structure
• The spatio-temporal statistical structure of the turbulent dissipation field and its stochastic representation as a Gaussian Multiplicative Chaos