Abstract
Strong gravitational lensing of time variable sources such as quasars and supernovae creates observable time delays between the multiple images. Time delays can provide a powerful cosmographic probe through the ``time-delay distance'' involving the ratio of lens, source, and lens-source distances. However, light curves of lensed images have measurement gaps, noise, systematics such as microlensing from substructure along an image line of sight, and no a priori functional model, making robust time-delay estimation challenging. Using Gaussian process techniques, we demonstrate success in accurate blind reconstruction of time delays and reduction in uncertainties for real data.
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