marginalizing over images

MJ Vakili delivered to me a draft manuscript on his prior over galaxy images. In the introduction, it notes that the only other times things like this have been done it has been to reduce the dimensionality of the space in which galaxy images are modeled or represented. This is a baby step, of course, towards a prior on images, but only a baby step, because principal component coefficients don't, in themselves, have a probabilistic interpretation or result in a generative model.

On the board in my office, Vakili explained how he would use the prior over images to make the best possible measurement of weak gravitational-lensing shear; it involves marginalizing out the unsheared galaxy image, which requires the prior of which we speak. The cool thing is that this solves—in principle—one of the ideas Marshall and I hatched at KIPAC@10, which was to use the detailed morphological features in galaxies that go beyond just overall ellipticity to measure the shear field. Now that's in principle; will it work in practice? Vakili is going to look at the GREAT3 data.

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