Experimental confirmation of long-memory correlations in star-wander data

TL;DR

This study experimentally confirms that atmospheric turbulence affecting stellar images exhibits long-memory correlations, which are crucial for improving atmospheric modeling and adaptive optics systems.

Contribution

First experimental verification of long-memory correlations in star-wander data using multifractal analysis techniques.

Findings

Turbulence-degraded stellar wavefronts show long-memory monofractal behavior.

Multifractal detrended fluctuation analysis effectively detects fractal structures.

Results enhance understanding of atmospheric turbulence effects on astronomical imaging.

Abstract

In this letter we have analyzed the temporal correlations of the angle-of-arrival fluctuations of stellar images. Experimentally measured data were carefully examined by implementing multifractal detrended fluctuation analysis. This algorithm is able to discriminate the presence of fractal and multifractal structures in recorded time sequences. We have confirmed that turbulence-degraded stellar wavefronts are compatible with a long-memory correlated monofractal process. This experimental result is quite significant for the accurate comprehension and modeling of the atmospheric turbulence effects on the stellar images. It can also be of great utility within the adaptive optics field.