Context. The early stages of planet formation, involving dust grain growth and planetesimals formation, remain shrouded in mystery. The analysis of the scattering phase function (SPF) measured in disks surrounding young stars holds great potential for revealing crucial information about dust grain properties. Given the rapidly increasing number of high-quality datasets available, an efficient method of extracting the SPF is required. Aims. We developed DRAGyS (Disk Ring Adjusted Geometry yields Scattering phase function), a tool designed for the quick and comprehensive analysis of protoplanetary disks in which gaps and rings are present. DRAGyS directly estimates the disk geometry and extracts the total and polarized SPF from scattered light images, without requiring any radiative transfer modeling, a limitation of previous efforts. Methods. Key disk parameters – the inclination, position angle, and aspect ratio – are obtained by fitting ellipses to the disk intensity peaks from the ring surface, assuming that the disks are circular. We validated the method using simulated disk images and then applied it to archival polarized-intensity images of nine images for six protoplanetary disks. DRAGyS also provides a method of correcting for the effect of limb brightening on the SPF. Results. DRAGyS recovers well the injected geometry and the SPF from synthetic images where the parameters are known. When compared to previously published results extracted from images without taking into account limb brightening, DRAGyS yields similar results for the inclination, disk position angle, and SPF. We show that the effect of limb brightening on the SPF is significant, with consequences for the inference of dust properties. Conclusions. DRAGyS takes advantage of a fast and purely geometrical approach to estimate ringed-disk geometries. It allows for the efficient extraction of the SPF either globally or by sectors, allowing it to deal with disk asymmetries. By bypassing the need for a full modeling of the disk geometry before SPF extraction, DRAGyS is well suited for studying large samples of disk images.
Roumesy et al. (Mon,) studied this question.