Growth Models and Models of Turbulence : A Stochastic Quantization Perspective

TL;DR

This paper explores growth models and turbulence models using stochastic quantization, revealing their similarities and providing a unified understanding of their predictions.

Contribution

It introduces a stochastic quantization framework to explain the connection between growth and turbulence models, offering a novel perspective.

Findings

Unified explanation of growth and turbulence models

Stochastic quantization accounts for similarities in model predictions

Provides a new theoretical approach to turbulence modeling

Abstract

We consider a class of growth models and models of turbulence based on the randomly stirred fluid. The similarity between the predictions of these models, noted a decade earlier, is understood on the basis of a stochastic quantization scheme.