Cosmoparticle Projects

These projects, whose studentships will be supported by a new cosmoparticle initiative, are co-supervised by staff from different UCL research groups. However the application procedure is the same as for STFC studentship; there is no need to apply to both groups to be considered for one of these positions. Both UK and EU students are eligible to apply for the studentship.

Towards a better modelling of self-interacting dark matter

Supervisors: Tom Kitching (MSSL) & Chamkaur Ghag (HEP)

Dark matter is the transparent material that constitutes the majority of the mass content of the Universe, however its fundamental nature remains a mystery. Cosmologists have attempted to use maps of mass in galaxy clusters, created using gravitational lensing methods, to measure dark matter properties. However the theoretical interpretation of such observations is not well founded on possible dark matter particle candidates. In this PhD we will create macro-physical dark matter models for cosmology that are underpinned by possible dark matter candidates that could be detected at the LHC and with direct detection experiments. The project will start by adapting well understood weakly interacting particle models from plasma physics to the dark matter setting, and apply these to current observations of interacting clusters using Hubble Space Telescope data to measure the self-interaction cross section of dark matter. We will then construct a model for the large-scale distribution of dark matter that will enable wide-field surveys such as Euclid and LSST to measure dark matter particle properties using cross-correlation statistics.

The Bullet Cluster (NASA)

The bullet cluster (NASA)

Searching for Dark Matter with Deep Learning

Supervisors: Chamkaur Ghag (HEP) & Jason McEwen (MSSL)

Direct Dark Matter search experiments operate highly sensitive detectors in deep underground laboratories, seeking to detect rare and low-energy scatters from Dark Matter particles in our galaxy. The world-leading LUX experiment, based at the Sanford Underground Research Facility, S. Dakota, operates a xenon target that is the most radio-quiet environment on Earth in the hunt for Weakly Interacting Massive Particles (WIMPs). WIMPs are expected to produce characteristic single vertex elastic scattering signatures. The rate of candidate events that satisfy this requirement is low, about 2 per day, and this is consistent with background expectation. However, there are many WIMP and non-WIMP models of Dark Matter that may produce significantly different signatures. LUX triggers about 1 million times per day to record data from completely uncharted electroweak parameter space, potentially containing new physics and non-standard WIMP or non-WIMP Dark Matter signals. The techniques of Machine Learning and Deep Learning present opportunities to analyse this data efficiently, particularly where faint signals with unknown characteristics may be hidden amongst large backgrounds. Developing these techniques could prove to be the key for discovery in the next generation of leading Dark Matter experiment, LZ, presently under construction and set to begin taking data within the lifetime of this project. LZ will examine the bulk of the favoured theoretical parameter space for Dark Matter, uncovering unknown backgrounds never previously encountered and potential signals. This project will develop the routines to analyse the existing rich LUX data for any galactic signals or new backgrounds, and prepare the framework for a robust and rapid interpretation of the data from LZ, be it for the first discovery of WIMPs or any hints of physics Beyond the Standard Model.

The LUX dark matter detector

The LUX dark matter detector (Matthew Kapust/Sanford Underground Research Facility)

Understanding the effect of neutrinos on large scale structure

Supervisors: Andreu Font-Ribera (Astronomy) & Tom Kitching (MSSL)

Neutrinos are some of the most abundant particles in the universe, but they have a very weak interaction with the other particles. The standard model of particle physics assumes that neutrinos are massless, but recently several experiments have shown that neutrinos must have a small but non-zero mass. This exciting discovery was awarded the 2015 Nobel prize in Physics, and it has motivated several attempts to measure the mass of the different neutrino species. One of the most promising approaches is to look at the effect that neutrinos have in the growth of structure in the Universe, as measured from the distribution of galaxies and gas (from redshift surveys like DESI), or from the distribution of dark matter as seen in the lensing of background sources (in lensing surveys like DES, Euclid or LSST). The goal of this project is to accurately model the effect of massive neutrinos in the different cosmological probes, and use data from existing and near future surveys to constrain or measure the mass of neutrinos.

Density Distribution in the Universe

Comparison of density distribution in the Universe with (left) and without (right) massive neutrinos. Illustration from Shankar Agarwal and Hume Feldman (2010).

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