Galaxy Clusters in the Big Data era with LSST

Project Summary: Galaxy clusters are the largest gravitationally bound objects in the Universe, consisting of 10s to 1000s of galaxies within a relatively small volume. They are used extensively as laboratories for galaxy evolution, as they contain galaxies that have experienced a similar environment and processes over many billions of years. They are also key cosmological indicators with the evolution of the number of galaxy clusters of a given mass being very sensitive to the Dark Matter content of the Universe. Because of their importance for both astrophysics and cosmology, it is desirable to obtain large, well-understood samples of galaxy clusters over a range of redshifts. The Large Synoptic Survey Telescope survey (LSST) is an imaging survey that will discover 10s of 1000s of new galaxy clusters, providing such a sample. It will image the entire Southern sky with an 8.4m telescope every few nights for 10 years, producing 200 petabytes of imaging data. This will be the state-of-the-art for optical surveys for many years to come.

This data science-driven project aims to develop algorithms and machine learning code to identify large numbers of distant galaxy clusters within the LSST survey. The initial algorithms will be run on existing comparable, but smaller area surveys, and the early phase of LSST that will begin operation in 2019. The algorithms and code will be designed so that they can be scaled-up to deal efficiently with the full size of the main LSST survey.