Massive Galaxies from the CARLA survey

Organisateur : Simona Mei (GEPI)

Date prévue : 18-20 septembre 2017
Date définitive : 2017-09-18

At present, around ten clusters are known at z>1.6. Current surveys are extending our samples of an order of magnitude, and give us insights on galaxy and large-scale structure evolution at the very first epochs of cluster formation.

Clusters Around Radio-loud AGN program (CARLA; Galametz et al. 2012; Wylezalek et al. 2013) is one of the major surveys of clusters and proto-clusters at high redshift and searches for overdensities around radio-loud AGNs. Twenty of the ~200 CARLA cluster candidates (Wylezalek et al. 2013, 2014), with 1.4 < z < 2.8, have been observed with the HST WFC3 in F140W imaging and G141 grism spectroscopy (PI: Daniel Stern; Noirot et al. 2016). HST observations permitted us to confirm cluster candidates and obtain galaxy morphology. Galaxy colors are available from combined space and ground-based observations. Recent results from Noirot et al. (2016) have shown that these high redshift overdensities host galaxies with different stellar populations, with some having already formed a red sequence and others showing star-forming galaxies overdensities. We recently had a program accepted at IRAM/NOEMA, in collaboration with F. Combes and P. Salome, and ALMA, we will dedicate the last day to discuss results from these two programs and plan for the future.

We propose to host a collaboration meeting to discuss recent CARLA results, and prepare follow-up programs with both optical and radio telescopes, with the goal to understand how the first clusters and their galaxies form.

We will invite members of the Spitzer South Pole Telescope Deep Field (SSDF; Ashby et al. 2013) collaboration to discuss similarities and differences in two cluster/proto-cluster samples. In fact, the SSDF cluster sample (Rettura et al. 2014) has been selected using similar galaxy colors as CARLA, but most of the candidates do not host a radio loud AGN. A comparison of our findings will permit us to asses selection effects and biases when drawing conclusions about galaxy evolution.