Tracking shocked dust: state estimation for a complex plasma during a shock wave

TL;DR

This paper introduces a novel particle tracking algorithm using multiple extended Kalman filters and an interacting multiple model to accurately estimate dust particle kinematics in a complex plasma during shock waves, enabling detailed physical property analysis.

Contribution

The paper presents a new tracking algorithm that significantly improves the accuracy of dust particle kinematics estimation in complex plasmas during shock events.

Findings

Enhanced accuracy in dust particle kinematics estimation.

Successful calculation of pressure-volume diagrams from shock data.

Ability to determine physical properties like kinetic energy and temperature with high precision.

Abstract

We consider a two-dimensional complex (dusty) plasma crystal excited by an electrostatically-induced shock wave. Dust particle kinematics in such a system are usually determined using particle tracking velocimetry. In this work we present a particle tracking algorithm which determines the dust particle kinematics with significantly higher accuracy than particle tracking velocimetry. The algorithm uses multiple extended Kalman filters to estimate the particle states and an interacting multiple model to assign probabilities to the different filters. This enables the determination of relevant physical properties of the dust, such as kinetic energy and kinetic temperature, with high precision. We use a Hugoniot shock-jump relation to calculate a pressure-volume diagram from the shocked dust kinematics. Calculation of the full pressure-volume diagram was possible with our tracking algorithm, but not with particle tracking velocimetry.