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John Stott supervises 3 postgraduate research students. If these students have produced research profiles, these are listed below:

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Dr John Stott

Lecturer in Astrophysics

John Stott

Physics Building



Tel: +44 1524 592396

PhD supervision

Environmental quenching of galaxies:
As the Universe ages, galaxies find themselves drawn together into filaments, groups and clusters. Galaxies entering these dense environments can experience processes which can ultimately lead to a dramatic change in their appearance and internal properties. This project will discover how galaxies are transformed (`quenched’) from blue star-forming spiral discs (like our own Milky Way) into passive red elliptical galaxies, through interactions with their environment. To achieve this we need to resolve and examine the influence of environment on the processes that take place within the galaxies themselves. This is done with Integral Field Units (IFUs), which can measure a spectrum at each spatial position of a galaxy, giving a 3-dimensional picture of its gas dynamics, star formation and chemical composition.

Galaxy clusters in the Big Data era with LSST:
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 (LSST) survey (https://www.lsst.org/) 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 will be designed so that they can be scaled-up to deal efficiently with the full size of the main LSST survey.

Research Interests

My research concentrates on distant star-forming galaxies and the evolution of the members of rich galaxy clusters. I am co-PI of the QSO Sightline And Galaxy Evolution survey (QSAGE), a 96 orbit Cycle 24 Hubble Space Telescope program. QSAGE uses the light from distant accreting black holes to probe the gas in the outskirts of galaxies, in order to discover why galaxies were forming stars at a much higher rate in the past and the nature of feedback processes. I am a core member of the KMOS Redshift One Spectroscopic Survey (KROSS) a resolved Halpha survey of 800 typical star-forming galaxies at redshift 1.

An up to date list of my publications on NASA ADS can be found here and my Google Scholar page is here

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