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The data is publicly available (as is the code), so you could just use it. The data itself is organized by region of the sky being imaged, so that calculation h
by KenoFischer 8y ago
The data is publicly available (as is the code), so you could just use it. The data itself is organized by region of the sky being imaged, so that calculation has already been done for us (and at the distance the stars/galaxies are at the difference in distance due to the Earth orbit doesn't matter). In the actual application, both the noise and the psf are modeled based on the actual telescope, so just adding arbitrary noise is a bit of a different problem, but probably a good start. Do note also that Celeste is a generative model (including modeling the noise), so you could just use it to generate a bunch of images for you.
- petermcneeley 8y agoI see you have the forward function to render out "color" given the properties of the stars that contribute to this region in space. All you have to do is find the highest probable property values that would generate that set of pixels. Sounds extremely parallizable which is probably why you managed to get the most out of the xeon phi.
- KenoFischer 8y agoIt's not quite that easy because of a) the noise (you're fitting distributions not values) and b) the fact that multiple light sources affect a given pixel, so you have to be a bit clever. But yes, you can get parallelism by spatial partition.