📝 SummarXiv

Abstract

Very Long Baseline Interferometry (VLBI) provides the highest-resolution radio intensity maps, crucial for detailed studies of compact sources like active galactic nuclei (AGN) and their relativistic jets. Analyzing jet components in these maps traditionally involves manual Gaussian fitting, a time-consuming bottleneck for large datasets. To address this, we present an automated batch-processing tool, based on the Gaussian fitting capabilities of CASA, designed to streamline VLBI jet component characterization (AAP-Imfit). Our algorithm sets a detection limit, performs automatic 2D Gaussian fitting, and removes model artifacts, efficiently extracting component flux densities and positions. This method enables systematic and reproducible analysis, significantly reducing the time required for fitting extensive VLBI datasets. We validated AAP-Imfit by using VLBI observations of the blazars 3C 279 and 3C 454.3, comparing our results with published fits. The close agreement in residual root mean square (RMS) values and model/residual-to-map RMS ratios confirms the accuracy of our automated approach in reproducing original flux distributions. While visual inspection remains important for complex or faint features, this routine significantly accelerates VLBI component fitting, paving the way for large-scale statistical studies of jet dynamics.