John Stott

Science Collaboration(s): 

My research focuses on the evolution of galaxies with environment, encompassing both cluster galaxy evolution and the reasons for the peak in star formation rate seen at cosmic noon. I plan to use LSST to study the evolution of galaxies within clusters out to z=1.5 and beyond, with the kind of representative, evolution matched, cluster mass samples that only LSST can provide. I have also recently been using novel machine learning and computer vision techniques to detect galaxy clusters in preparation for LSST. We have performed a successful proof of concept with SDSS: . The plan is to also use this method to confirm clusters within the LSST footprint selected by other methods, such as X-ray, SZ and red sequence detection. These clusters will be characterised using machine learning to obtain their redshifts and richnesses etc. Again, we have a proof of concept with SDSS, which extracts accurate photo-z for cluster galaxies:

We are currently testing out both our galaxy evolution research and cluster finding techniques on the Subaru HSC survey data and potentially DP0.

I am a member of the Galaxies SC, DESC and the LSST: UK. Executive Board.