# TESS Program G08187

Title: Beam: Correcting Scattered Light In TESS Ffis

PI: Muthukrishna, Daniel - Massachusetts Institute Of Technology

Type: SMALL

Summary: This proposal introduces BEAM (Background Elimination with Advanced Machine learning), a novel approach that leverages generative AI to model and remove scattered light from TESS FFIs. TESS Cycle 8's unique observing strategy featuring rolled pointings and longer continuous observations provides an unprecedented opportunity to model time-varying scattered light patterns. The proposed work will deliver a \texttt{pip}-installable Python package for background modeling and scattered light corrected FFIs with pixel-level uncertainty estimates. This project will significantly enhance photometric precision across various TESS science cases, including exoplanet detection, asteroseismology, stellar variability studies, transients, and time-domain astronomy.