Solar Vortex Detection With Velocity Field Normalisation: Eliminating False Positives

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.