Efficient Starspot Reconstruction via Light-curve Inversion with Bipartite Regularization

Light-curve inversion (LI) is a powerful imaging technique and widely used in stellar surface imaging and starspot reconstruction. It can be used to reconstruct a high-resolution image from a light curve of a star via the conversion from temporal resolution to spatial resolution. However, as an ill-posed problem, accurate resulting spot-to-photosphere brightness ratio (SBR) is hard to achieve because of the limitation of the single regularization of the traditional LI method. To address the existing problems, we propose a new method, namely LI with bipartite regularization (LIBR), to extend the capability of LI. This new method employs adaptive SBR adjustment in each iteration of the fitting process to obtain accurate intensity distribution. As shown in the simulations, the SBR produced by the LIBR method indicates that the model can mimic the actual stellar surface as closely as possible. Therefore, it becomes possible to be used for analyzing starspots from massive high-quality observed data derived from the Kepler Space Telescope and the Transiting Exoplanet Survey Satellite.