I am so frustrated! I don't know what I am doing wrong. It doesn't match at all. I am having one of those moments where I feel like nothing I do ever works and I am a complete failure as a grad student. I mean, I'm in my 5th year of my PhD and don't have a single paper published, nor a working project. Everything that I am doing that does work is someone else's code (i.e. Alexia or David) and therefore has nothing to do with my talent or skills. Rage Rage Rage!
Here is a histogram of the "redshifts" (converted to units of comoving line-of-sight distance (Gpc/h) away from the observer) of the photometric data set (based on the Sloan photo-z's):
This is what the reconstruction should look like. However, when I do the reconstruction I get the following:
(The green is the reconstruction)
This actually paints a better picture than I actually have because
1) The normalization doesn't work and so I am tuning the normalization to match the answer (can't do this when I don't know the answer).
2) This is with really course binning. If I use finer binning (which is what we would ideally want to do), I get worse results:
What is up with the reconstruction going to zero (~1, 1.6, 1.9 Gpc/h)? I am so confused about that. Something that Adam and I discussed last night was that we would hope that this method would work at least as well as simply taking a histogram of the redshifts of the spectroscopic data set. In this case the spectroscopic data is actually from the same data as the photometric set, so the redshift distributions of the two sets are almost identical:
The fact that the reconstruction is significantly worse than this is really disheartening. I give up for today. I'm going to work on likelihood stuff in rebellion! (and post a sad facebook status message so people feel sorry for me and make me feel better)
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