Like many astronomical missions and data sets, the NASA Kepler satellite imaging is crowded; there is no part of the imaging that contains reliably isolated stars. For this reason, it is hard to infer (from the data) the point-spread function of the instrument simply; any PSF inference requires modeling the images as a crowded image of many overlapping stars (of unknown brightnesses and positions). However, when a star is subject to a planetary or stellar transit, the change in the scene during the transit should be modeled well as a PSF-shaped deficit. So we should be able to infer the PSF from these deficits. The transits are rare, so they rarely overlap. They are also very faint (low-amplitude) events, but (a) the eclipsing-binary stellar transits are not so faint (and very common), and (b) Kepler has good signal-to-noise even on planetary transits.
John Gizis points out (on the twitters) that you can also use any kind of variable star. Brad Tucker points out that you can use supernovae too.
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