Light-Curve Texture: A New Photometric Measure of Waveform Organization and Its Relationship with Stellar Evolution in Kepler Stars

Light-Curve Texture: A New Photometric Measure of Waveform Organization and Its Relationship with Stellar Evolution in Kepler Stars This archive contains the completed publication version of the study, introducing a novel analytical framework for detecting and measuring differences in the fine-scale structure of stellar light curves and investigating their astrophysical significance. The study introduces Light-Curve Texture (LT), the Smooth Light-Curve Filter (SLF), the Light-Curve Texture Index (LTI), and the Lynas Texture–Age Relation (LTAR). This version supersedes the earlier restricted second manuscript draft deposited on July 3, 2026. Using Kepler observations, the study establishes LT as an objectively measurable progression from exceptionally smooth to increasingly textured stellar light curves. The SLF first identified the smoothest light curves and revealed their clustering within distinct stellar populations, a pattern subsequently reproduced in an independent random Kepler sample. LTI then extended measurement across the full smooth-to-textured continuum. Multiple independent waveform characteristics strongly correlated with LTI, and predictive models using those characteristics recovered much of the original LTI ordering without being given the measurements used to create it. Further tests showed that this predictive ability was not dependent on any single waveform characteristic. The study then identifies LTAR: a new relationship between light-curve texture and stellar evolution. Within Solar Dwarfs and Cool Dwarfs, smoother light curves preferentially occur earlier in a star’s fractional evolutionary lifetime, while increasingly textured light curves tend to occur progressively later. The evolutionary progression remains consistent across the full stellar populations. The relationship also remains statistically significant after known variable stars are removed, indicating that LTAR extends beyond previously recognized forms of stellar variability. The archive includes the final manuscript, principal Python analysis programs, CSV data products and supporting inputs, and a README documenting the analysis and data provenance.