Solar Vortex Detection With Velocity Field Normalisation: Eliminating False Positives

TL;DR

This paper introduces a velocity field normalization technique that improves the detection accuracy of small-scale solar vortices by reducing false positives and revealing more vortical flows in high-resolution simulations.

Contribution

The authors propose a simple preprocessing step normalizing the velocity field to enhance vortex detection accuracy in solar photosphere simulations, reducing false positives and revealing more vortices.

Findings

Normalization removes most false positives in vortex detection.

The $ ext{Gamma}$ method detects true vortices but misses many flows.

Normalisation increases detected vortices by a factor of four to five.

Abstract

Small-scale vortices in the solar photosphere play a central role in transporting mass, energy, and momentum into the upper solar atmosphere, yet reliably detecting these structures remains rather challenging. We address this problem by introducing a simple preprocessing step that normalises the velocity field by its magnitude. Our method preserves flow topology while suppressing shear-induced artefacts that lead to spurious detections in non-uniform, high-rotation environments. For validation, we apply this approach to high-resolution Bifrost simulations and evaluate vortex detection using four commonly employed methods: IVD, the $\lambda_2$-criterion, the Q-criterion, and the $\Gamma$ method. We assess which structures exhibit physically consistent rotation by using the $d$-criterion to automatically detect rotational plasma-flow features, which we use as an approximate ground truth. We find that, in the unnormalised field, a substantial fraction of detections made by the first three methods are false positive detections. Normalisation removes most of these. The $\Gamma$ method detects true vortices but misses a large number of vortical flows. The normalisation step yields better-defined and more realistic vortex boundaries. As the $\Gamma$ method underpins most observational analyses, current studies likely capture only a subset of vortical flows. By comparison, the other three methods detect four to five times more vortices after normalisation, suggesting that the true photospheric vortex coverage may be underestimated by a similar factor. Overall, this physically motivated preprocessing step enhances the accuracy and physical realism of vortex detection and offers a practical enhancement for analysing vortical flows in turbulent flows.