Comparing Methods for Protoplanetary Disk Modeling Across 652 Observations

Abstract

This study revisits protoplanetary disk modeling through the lens of convolutional analysis. Our protocol combines convolutional estimation with a lightweight validation pipeline designed to be reproducible by student laboratories. Our measurements agree with theoretical predictions to within 26%, resolving an open discrepancy in the literature. These findings suggest a practical path toward broader adoption in resource-constrained settings.