Algol Light Curve and Spectrometry Analysis

This project will make observations of the eclipsing binary star system Algol (Beta Persei), in order to garner further information about the characteristics of its 2 main stars and their orbital period. We plan to use photometric and spectroscopic analysis, archival datasets, and artificial intelligence to assist us in planning, gathering and analyzing our data as well as with helping refine the orbital period of Algol. Using software such as MPO Canopus and TESS data, we plan to construct high-resolution light curves and validate Algol’s periodic behavior. Through our utilization of a spectrometer, we plan to take direct measurements of radial velocities, spectral line profiles, and temperature variations, allowing for more precise determination of stellar masses, radii, and orbital inclination.

AI-assisted calibration techniques -- including real-time feedback loops for optimizing image quality and anomaly detection for identifying inconsistencies in calibration frames -- ensure high-fidelity data acquisition. On the operational side, AI-assisted decision-making supports target prioritization based on orbital relevance and autonomous scheduling of observations to maximize telescope efficiency under variable conditions.

This research lays the groundwork for a follow-on project focused on asteroid occultation detection during eclipsing binary observations. Occultation timing and spectral analysis will be used to determine asteroid diameters, geometric albedos, and surface compositions, contributing to Assured Positioning, Navigation, and Timing (PNT) and Air and Missile Defense by improving orbital models of near-Earth objects (NEOs). The project aligns with Army Research Areas in Artificial Intelligence, Autonomy, Quantum-enhanced sensing, and RF Electronic Materials, supporting future applications in networked surveillance, long-range precision fires, and hypersonic flight mission planning.