PhD project: Parton Distribution Functions

Project description

This is an exciting time to be a particle theorist. There is an immense amount of new data from LHC, with the possibility that discoveries of new physics are just around the corner. Since there are no entirely convincing models of how this new physics might look, particle theory is now, for the first time for many decades, essentially data-driven.

The analysis of LHC data is complicated by the fact that it is a proton-proton collider. The underlying hard processes which may produce new physics involve instead parton-parton collisions, where a ‘parton’ is a quark, antiquark or gluon. These hard processes may be computed using perturbative QCD. However to turn these QCD calculations into physical cross-sections, which can be compared to actual data, we need to know the probability of finding a given parton in the proton. This information is encoded in so-called ‘parton distribution functions’ (or PDFs for short). Since PDFs cannot be computed in perturbation theory, they must in turn be inferred from experimental data. PDF determinations are thus the key to understanding LHC physics: without them we would have no way of comparing theory with data, and thus no way of reliably exploring possible new physics.

There are a number of international collaborations around the world working on PDF determination. In Edinburgh we belong to one of the largest and most successful of these, the NNPDF Collaboration. NNPDF use neural networks to extract the PDFs, and Monte Carlo methods to determine their statistical distribution. As a PhD student working in Edinburgh on PDFs, you would have the opportunity to work on a wide range of possible projects – from development of new software tools, to making new predictions to be compared directly to LHC data, to discovering new ways of increasing the precision of the PDFs in regions where new physics might be discovered. You would also be able to experience working in an international collaboration, with members in Edinburgh, Cambridge, CERN, Amsterdam, Milan and Torino, with plenty of opportunities for travel.

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