Back to Work (back to Reconstruction)

I need to do a better job of balancing working on both the Newman Project and BOSS Likelihood target selection. I feel like it's been months since I have worked on the Newman stuff. Luckily Alexia was in Mexico and helped me get up to speed again.

Martin White gave me a halo mock catalog (I was using the wrong one for a while) and I have applied the following selection function to the photometric data set:

This corresponds to the following redshift distribution (phi):

The blue line is a histogram of the redshifts of the mock data, and the green line is the phi we are imposing (by both geometry and the selection function, you can see they match pretty well). I believe the difference in these two is based on actual structure, not an problem with implementing the selection function.

On the spectroscopic data, I imposed no selection function, and so the distribution was based purely on the geometry and structure of the data. Because the geometry is a sphere, we expect more objects at greater redshifts (larger volume at greater r):

I decided to start with a small run with data sets of approximately equal size. The photometric data set has 25,887 objects, and the spectroscopic data set has 25,470 objects. The redshift bins are 50 Mpc/h wide and go from 0 - 500 Mpc/h. Here are the 2D cross-correlation functions and the 3D auto-correlation functions of the mock data:

Here is the reconstruction. It is using an old version of crl (I'm having trouble downloading the newest version from the repository). It doesn't seem to be doing that good of a job reconstructing:

Maybe updating crl will help things? Thoughts Alexia?