Lagrangian quantum turbulence model based on alternating superfluid/ normal fluid stochastic dynamics

TL;DR

This paper introduces a superstatistical model for tracer particle dynamics in quantum turbulence, capturing velocity statistics by alternating between superfluid and normal fluid states, aligning well with experimental data.

Contribution

It presents a novel superstatistical model that combines superfluid and normal fluid dynamics with memory effects for quantum turbulence analysis.

Findings

Model accurately reproduces experimental velocity and acceleration statistics.

Superposition of power law and Gaussian distributions fits observed data.

Analytic predictions for probability densities and correlations are validated.

Abstract

Inpired by recent measurements of the velocity and acceleration statistics of Lagrangian tracer particles embedded in a turbulent quantum liquid we propose a new superstatistical model for the dynamics of tracer particles in quantum turbulence. Our model consists of random sequences S/N/S/... where the particle spends some time in the superfluid (S) and some time in the normal fluid (N). This model leads to a superposition of power law distributions generated in the superfluid and Gaussian distributions in the normal liquid, in excellent agreement with experimental measurements. We include memory effects into our analysis and present analytic predictions for probability densities and correlation functions.