Enhancing Exoplanet Transit Detection in Noisy Stellar Light Curves Using Statistical Filtering Technique

This study investigates methods to enhance exoplanet transit detection in noisy stellar light curves using simple yet robust statistical filtering techniques. Real photometric data from NASA’s Kepler Space Telescope—including observations of the enigmatic KIC 8462852 (Tabby’s Star)—were analyzed. Three filtering methods—moving average, median, and Savitzky–Golay—were implemented to mitigate noise while preserving true transit signatures. Among these, the median filter proved most effective in suppressing outliers and long-term stellar variability, while moving averages reduced high-frequency noise. Combined filtering significantly improved the signal-to-noise ratio (SNR), enabling clearer identification of subtle transit events. These findings suggest that lightweight preprocessing approaches can substantially enhance the efficiency of large-scale photometric surveys and improve the reliability of exoplanet detection pipelines.