Wrapping and unwrapping multifractal fields

Fuente: arXiv
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Autori principali: Lakhal, Samy, Ponson, Laurent, Benzaquen, Michael, Bouchaud, Jean-Philippe
Natura: Preprint
Pubblicazione: 2023
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author Lakhal, Samy
Ponson, Laurent
Benzaquen, Michael
Bouchaud, Jean-Philippe
author_facet Lakhal, Samy
Ponson, Laurent
Benzaquen, Michael
Bouchaud, Jean-Philippe
contents 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 $λ$ and multifractal range $ξ_ω$. We retrieve all the salient features of the MRW, namely a quadratic scaling exponent spectrum $ζ_q$, 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.
format Preprint
id arxiv_https___arxiv_org_abs_2310_01927
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Wrapping and unwrapping multifractal fields
Lakhal, Samy
Ponson, Laurent
Benzaquen, Michael
Bouchaud, Jean-Philippe
Statistical Mechanics
Mathematical Physics
Data Analysis, Statistics and Probability
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 $λ$ and multifractal range $ξ_ω$. We retrieve all the salient features of the MRW, namely a quadratic scaling exponent spectrum $ζ_q$, 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.
title Wrapping and unwrapping multifractal fields
topic Statistical Mechanics
Mathematical Physics
Data Analysis, Statistics and Probability
url https://arxiv.org/abs/2310.01927