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Systematic Optical/NIR Discovery of Large Scale Structure at Intermediate and High Redshift

Authors: Hung, Denise; Lemaux, Brian C.; Lubin, Lori M.; Gal, Roy R.; Cucciati, Olga; Le Fèvre, Olivier; Shen, Lu; +1 Authors

Systematic Optical/NIR Discovery of Large Scale Structure at Intermediate and High Redshift

Abstract

Voronoi tessellation Monte-Carlo (VMC) mapping is a powerful new technique for finding galaxy overdensities when combined with rich optical and near-infrared multi-band imaging and a wealth of spectroscopy. I will show how we were able to use this technique to measure precise systemic redshifts, estimate the total gravitating mass, and maintain high levels of purity and completeness even with moderate levels of spectroscopy across more than an order of magnitude in total structure mass at z~1 with the Observations of Redshift Evolution in Large-Scale Environments (ORELSE) survey. I will also show how we used the discovered structures to construct a cluster mass function and perform basic cosmological fitting that previously was only accomplished in the local universe for optical datasets. At higher redshifts (z>2), VMC mapping has already been integral to the detection and characterization of individual large-scale structures in the VIMOS Ultra Deep Survey (VUDS) and Charting Cluster Construction with VUDS and ORELSE (C3VO) survey. I will present preliminary results of new systematic structure searches at 2<z<5 both from the original VUDS survey and those enabled by recent spectroscopy obtained with Keck as part of the C3VO survey. Our successes with VMC mapping across a huge redshift baseline (0.5<z<5) and very different surveys attest to its potential to find structure in any number of current and future spectroscopically rich galaxy surveys in the high-redshift Universe.

Keywords

galaxies: high redshift, galaxies: clusters, galaxies: protoclusters

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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