Large mosaic multiCCD camera is the key instrument for modern digital sky survey. DECam is an extremely red sensitive 520 Megapixel camera designed for the incoming Dark Energy Survey (DES). It is consist of sixty two 4k$times$2k and twelve 2k x 2k 2
50-micron thick fully-depleted CCDs, with a focal plane of 44 cm in diameter and a field of view of 2.2 square degree. It will be attached to the Blanco 4-meter telescope at CTIO. The DES will cover 5000 square-degrees of the southern galactic cap in 5 color bands (g, r, i, z, Y) in 5 years starting from 2011. To achieve the science goal of constraining the Dark Energy evolution, stringent requirements are laid down for the design of DECam. Among them, the flatness of the focal plane needs to be controlled within a 60-micron envelope in order to achieve the specified PSF variation limit. It is very challenging to measure the flatness of the focal plane to such precision when it is placed in a high vacuum dewar at 173 K. We developed two image based techniques to measure the flatness of the focal plane. By imaging a regular grid of dots on the focal plane, the CCD offset along the optical axis is converted to the variation the grid spacings at different positions on the focal plane. After extracting the patterns and comparing the change in spacings, we can measure the flatness to high precision. In method 1, the regular dots are kept in high sub micron precision and cover the whole focal plane. In method 2, no high precision for the grid is required. Instead, we use a precise XY stage moves the pattern across the whole focal plane and comparing the variations of the spacing when it is imaged by different CCDs. Simulation and real measurements show that the two methods work very well for our purpose, and are in good agreement with the direct optical measurements.
We present a large catalog of optically selected galaxy clusters from the application of a new Gaussian Mixture Brightest Cluster Galaxy (GMBCG) algorithm to SDSS Data Release 7 data. The algorithm detects clusters by identifying the red sequence plu
s Brightest Cluster Galaxy (BCG) feature, which is unique for galaxy clusters and does not exist among field galaxies. Red sequence clustering in color space is detected using an Error Corrected Gaussian Mixture Model. We run GMBCG on 8240 square degrees of photometric data from SDSS DR7 to assemble the largest ever optical galaxy cluster catalog, consisting of over 55,000 rich clusters across the redshift range from 0.1 < z < 0.55. We present Monte Carlo tests of completeness and purity and perform cross-matching with X-ray clusters and with the maxBCG sample at low redshift. These tests indicate high completeness and purity across the full redshift range for clusters with 15 or more members.
The red sequence is an important feature of galaxy clusters and plays a crucial role in optical cluster detection. Measurement of the slope and scatter of the red sequence are affected both by selection of red sequence galaxies and measurement errors
. In this paper, we describe a new error corrected Gaussian Mixture Model for red sequence galaxy identification. Using this technique, we can remove the effects of measurement error and extract unbiased information about the intrinsic properties of the red sequence. We use this method to select red sequence galaxies in each of the 13,823 clusters in the maxBCG catalog, and measure the red sequence ridgeline location and scatter of each. These measurements provide precise constraints on the variation of the average red galaxy populations in the observed frame with redshift. We find that the scatter of the red sequence ridgeline increases mildly with redshift, and that the slope decreases with redshift. We also observe that the slope does not strongly depend on cluster richness. Using similar methods, we show that this behavior is mirrored in a spectroscopic sample of field galaxies, further emphasizing that ridgeline properties are independent of environment.
