We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS DR7). Each algorithm is defined by a set of parameters which, when var
ied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of $884,126$ SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: $14le rle21$ ($85.2%$) and $rge19$ ($82.1%$). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT and Ball et al. (2006). We find that our FT classifier is comparable or better in completeness over the full magnitude range $15le rle21$, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes ($r>19$), our classifier is the only one able to maintain high completeness ($>$80%) while still achieving low contamination ($sim2.5%$). Finally, we apply our FT classifier to separate stars from galaxies in the full set of $69,545,326$ SDSS photometric objects in the magnitude range $14le rle21$.
The Cl1604 supercluster at z=0.9 is one of a small handful of such structures discovered in the high redshift universe, and is the first target observed as part of the Observations of Redshift Evolution in Large Scale Environments (ORELSE) Survey. To
date, Cl1604 is the largest structure mapped at z~1, with the most constituent clusters and the largest number of spectroscopically confirmed member galaxies. In this paper we present the results of a spectroscopic campaign to create a three-dimensional map of Cl1604 and to understand the contamination by fore- and background large scale structures. Combining new Deep Imaging Multi-object Spectrograph observations with previous data yields redshifts for 1,383 extragalactic objects in a ~ 0.08 sq. deg region, 449 of which are supercluster members. We examine the complex three dimensional structure of Cl1604, providing velocity dispersions for eight of the member clusters and groups. Our extensive spectroscopic dataset is used to examine potential biases in cluster velocity dispersion measurements in the presence of overlapping structures and filaments. We also discuss other structures found along the line-of-sight, including a filament at z=0.6 and two serendipitously discovered clusters/groups at z~1.2.
