Toward a deeper understanding of a basic cascade

TL;DR

This paper introduces a new discrete version of the p-model cascade using a novel sampling method, simplifying analysis and providing clearer insights into multifractal phenomena related to turbulence and chaos.

Contribution

It presents an original discrete p-model cascade with a new sampling approach, making proofs straightforward and formulas explicit for better understanding of multifractal analysis.

Findings

Simplified proofs and explicit formulas for the discrete p-model.

Enhanced understanding of multifractal features through elementary methods.

Potential to improve multifractal analysis techniques.

Abstract

Towards the end of the last century, B. Mandelbrot saw the importance, revealed the beauty, and robustly promoted (multi-)fractals. Multiplicative cascades are closely related and provide simple models for the study of turbulence and chaos. For pedagogical reasons, but also due to technical difficulties, continuous stochastic models have been favoured over discrete cascades. Particularly important are the $\alpha$ and the $p$ model. It is the aim of this contribution to introduce original concepts that shed new light on a variant of the latter paradigmatic cascade and allow key features to be derived in a rather elementary fashion. To this end, we introduce and study a discrete version of the $p$ model which is based on a new kind of sampling. Technical machinery can be kept simple, therefore proofs are straightforward and formulas are explicit. It is hoped that the proposed line of investigation may enhance understanding and simplify received multifractal analyses.