Statistics – Computation
Scientific paper
May 2006
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006sptz.prop30150w&link_type=abstract
Spitzer Proposal ID #30150
Statistics
Computation
Scientific paper
We propose to obtain IRAC imaging as part of a multiwavelength campaign to characterize a unique sample of galaxy clusters: shear-selected clusters from the Deep Lens Survey (DLS). Shear selection is a new technique which uses weak gravitational lensing to detect the clusters based on their gravitational effects alone. Thus it is unbiased with respect to baryon content and star formation history, a key difference from X-ray and optical cluster selection. Understanding the biases in current traditionally selected samples is extremely important because mass, not emitted light, is the key cluster property for cosmology. The clustering of mass in different cosmologies and dark matter scenarios is well understood theoretically and quite tractable computationally, but the observed X-ray and optical emission result from complex gastrophysics which is not yet well modeled. Therefore a key question is whether a shear-selected cluster sample will reveal clusters with properties different from current X-ray and optically selected samples. The focus of this proposal is using IRAC data to derive the stellar mass content and star formation history of these clusters, to be compared with optically and X-ray selected clusters. As an added benefit, the infrared photometry will complement the existing data on these clusters (deep BVRz' optical imaging, mass maps, Chandra spectro-imaging, and spectroscopy) in many ways. For example, they will greatly improve the photometric redshifts, allowing for better identification of cluster members and more accurate lensing analyses.
Margoniner Vera
Wittman David
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