Visit ASIAA Homepage Registration Deadline: January 31, 2019 (Taiwan Time)
Panchromatic Panoramic Studies of Galaxy Clusters: from HSC to PFS and ULTIMATE
March 11(Mon)-13(Wed), 2019
ASIAA, Taipei, Taiwan

Oral Presentation

Arizona Cluster Redshift Survey (ACReS)

Author(s): Eiichi Egami, Maria Pereira, Christopher Haines, Graham Smith, Alexis Finoguenov, and the ACReS/LoCuSS teams

Presenter: Eiichi Egami (University of Arizona)

The Arizona Cluster Redshift Survey (ACReS) is a large optical spectroscopic survey of 30 massive clusters at z=0.15-0.3 using MMT/Hectospec, which is a 300-fiber multi-object spectrograph with a circular field of view of a 1-deg diameter. Now completed, ACReS has acquired reliable spectra for ~24,000 objects, ~10,000 of which are cluster members, i.e., >300 members per cluster, reaching well into the cluster infall regions (up to a few virial radii). Compared to other similar surveys, ACReS has the following advantages: (1) the existence of a large extensive multi-wavelength data set obtained by the Local Cluster Substructure Survey (LoCuSS) covering X-ray (Chandra and XMM-Newton), UV (GALEX), optical (Subaru/Suprime-Cam and HST/ACS), near-infrared (UKIRT/WFCAM), mid-infrared (Spitzer/MIPS 24 micron), and far-infrared (Herschel/PACS+SPIRE), (2) availability of high-quality strong/weak-lensing mass maps produced by the combined analysis of the HST and Subaru images, and (3) unbiased stellar-mass-based target selection utilizing the near-infrared data, complete down to M(star)~10^10 Msun at cluster redshifts. Here, we will describe the survey design, present the available data set (publicly released for the first time), and provide an overview of science programs conducted so far, such as the study of slow-quenching of star formation in cluster galaxies and identification of infalling X-ray groups. With the samples of high-redshift clusters rapidly expanding, ACReS (with LoCuSS) provides a robust baseline sample of low-redshift clusters, and can be regarded as a precursor for PFS cluster surveys.

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