SJET: An Interactive Solar Jet Extraction Tool

Abstract

Solar jets are dynamic collimated plasma flows in the solar atmosphere that play crucial roles in coronal heating and solar wind acceleration. Their complex and diverse morphologies pose significant challenges for developing universal algorithms for automatic identification and extraction, particularly for on-disk jets affected by projection effects and background contamination. We present SJET, an interactive tool for solar jet feature extraction using multiple algorithms developed in Python that integrates five thresholding algorithms with morphological operations. SJET implements a novel method for identifying start and end points based on circular regions that objectively determines jet propagation direction by exploiting morphological asymmetry, combined with modeling the axis using quadratic B\'ezier curves for accurate extraction of geometric parameters including length, width, curvature, and deflection angles. Validation analyses using Solar Orbiter/EUI high-resolution image and SDO/AIA observations demonstrate SJET's effectiveness across different observational conditions, with good agreement compared to traditional analysis methods, though the tool's accuracy remains dependent on user-defined threshold parameters and region of interest selection. SJET provides a solution to method inconsistency in solar jet research through standardized processing workflows, establishing a technical foundation for large-sample statistical studies.