Using Cosmic Beasts to Uncover the Nature of Dark Matter

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The nature of dark matter is the most elusive question in modern physics. Only 5% of the Universe by weight consists of standard model particles. The remaining 95% would be composed of 'Dark Matter' and 'Dark Energy'. These are invisible, and most particle physics theories predict dark matter to interact so weakly with standard model particles that it will remain fundamentally undetectable in terrestrial experiments. If these theories are correct, dark matter can only be studied where it gathers in sufficient quantities for its gravity to affect things around it we can see. I propose to track the behaviour of dark matter in galaxy clusters (the most massive structures in the universe, also called 'cosmic beasts'), to distinguish between the 3 leading models: cold, warm and self-interacting dark matter.My proposal exploits a dramatic recent increase in observations of galaxy clusters by the world's biggest telescopes, reflecting the field's recognition as a top priority goal. I have been awarded observing time on the Hubble Space Telescope in the largest category of programme (>100 orbits) to obtain the deepest ever imaging of clusters' surroundings, plus follow-up spectroscopy from the largest telescope on Earth (VLT). I designed these observations to map clusters' dark matter, via the effect of 'gravitational lensing', which distorts and magnifies objects behind the cluster. I will use these data (i) by themselves, (ii) to calibrate the largest (but shallow) Hubble imaging awarded to the host institute (iii) to set the agenda for, and optimise facilities like Euclid, Athena and the James Webb Space Telescope through the 2020s.Cosmological simulations indicate that galaxy clusters are the best laboratories to distinguish between models of dark matter, because they are still growing. Clusters grow by merging with each other; every merger acts like a gigantic particle collider. The properties of dark matter are revealed by its trajectory through a collision, which should be between that of stars and of (hydrogen) gas. The properties of stars and hydrogen are well understood, so they bookend measurements of dark matter like the calibration points on a thermometer at 0C and 100C. Traditional research programmes usually separate measurements of dark matter, stars and gas, because they require observations from different (infrared, ultraviolet, X-ray) telescopes. I have developed a multiwavelength analysis, to enable previously impossible measurements such as the time-scale on which dark matter and gas is funneled into clusters, how quickly clusters reach equilibrium, and constraints on possible dark matter particle interactions.I have also led the establishment of a new research area, which I will expand during the FLF. When transient events (such as supernova explosions) happen behind a galaxy cluster, light from the explosion can be gravitationally lensed and visible along more than one line of sight. Measuring the time delay between multiply-imaged versions of a supernova increases the resolution with which the cluster's dark matter can be mapped. Furthermore, predicting the time delay is one of those rare, precious occasions in astrophysics where a hypothesis can be subjected to a true Popperian test, within the timescale of a few years. I have intentionally scheduled my HST and VLT observations to enable the discovery and monitoring of transient events. They also offer the (high risk/high reward) possibility of discovering electromagnetic counterparts to lensed gravitational wave events.My UKRI FLF research programme will thus exploit the latest multiwavelength data from world-class facilities. It uses my high-precision techniques to analyse big data, and will be interpreted within the world-leading theoretical framework of Durham's state-of-the-art cosmological simulations.