Validation of the MPFF-IFO Framework for Detection of Anomalous Celestial Objects

This paper validates the application of the Multidimensional Potential Fractal Framework capacity of Ibaguner Fractal Operator (IFO) to astronomical data analysis. Through an iterative human-AI collaborative process, we developed and refined a compact, efficient algorithm for identifying celestial objects with anomalous orbital characteristics. The final implementation successfully detects objects with comet-like kinematics within a simulated dataset, demonstrating the framework's robustness and readiness for deployment on real astronomical catalogs. This work establishes IFO as a powerful trans-disciplinary tool for anomaly detection in complex systems.