Binning is sinning. This phrase appears in our recent paper on correlation-function estimation. Our solution to the problem of binning is very deep (imho): Not only do we obviate binning in the radial-separation direction, we also obviate binning in any other quantity on which you think the clustering might depend (like angle wrt the line of sight, galaxy luminosity, and so on).
Abby Williams (NYU), Kate Storey-Fisher (NYU), and I are using the new unbinned estimator to look for variations in galaxy clustering with position within the Hubble volume. Traditionally this might be done by splitting the space into boxels, and measuring the clustering in boxels separately; are there variations? But binning is sinning: Now Storey-Fisher has made an estimator that can estimate the parameters of a clustering model with an explicit gradient or variation with position. And Williams has made simulated cosmological volumes that contain clustering gradients for testing purposes. We're close to making a (toy) measurement!
No comments:
Post a Comment