Elliot T. J. Reynolds

Particles are the fundamental building blocks of reality. The universe is made entirely of them, and everything that happens is due to their interactions. A complete theory of particle physics is, therefore, the Theory of Everything. The Standard Model of particle physics (SM) explains most of our day-to-day world with just a handful of particles, however, it leaves many open questions… How do gravity and the SM fit together? What is dark matter? What is dark energy? Why is there more matter than anti-matter? Why is the Higgs boson so light? Why is the SM the way it is? For this reason, we know the SM is incomplete. The million-dollar question is then: What lies beyond the Standard Model? Answering this question would transform our understanding of nature, and is the overarching theme of my research interests.

The Higgs boson discovery in 2012 completed the SM, enabled the study of the Higgs sector, and led to a Nobel Prize in Physics. The Higgs boson is highly unique, since it is the only spin-0 particle and it is associated with an ever-present field that causes electroweak symmetry breaking and generates mass. It may also be the key to answering many of the most important questions in particle physics and cosmology, including many of those above, as well as to predicting the fate of the universe. Since it has only recently been possible to study the Higgs sector, and because it is highly challenging, there is still much to be learnt about it and a very good chance that beyond the SM (BSM) physics is there waiting to be found. Given these factors, the Higgs boson is a subject of global intrigue and a promising probe of BSM physics, and using it as such a probe is the main goal of my career.

To discover and characterize BSM physics, new techniques will likely be required. In recent years the third wave of deep learning has been changing the world, and particle physics with its enormous datasets is well-placed to ride this wave. I have developed and implemented novel artificial intelligence (AI) techniques in a particle physics context, and I am interested in further exploration of new AI methods in the pursuit of BSM physics, including modern deep learning techniques.

To study the Higgs boson the world’s largest machine, the Large Hadron Collider (LHC), and its general purpose detectors, ATLAS and CMS, are used. I am a member of the CMS collaboration, and plan for much of my coming research to use the CMS detector. Before this, I spent ~9 years of my career working in the ATLAS collaboration. The LHC has had a fruitul physics program, though many searches and measurements are still limited by the dataset sizes. This issue will be addressed by the High Luminosity LHC (HL-LHC), an upgrade to the LHC that will increase the dataset sizes ~10x. However, this will also increases the activities in the detectors ~7x, necessitating major detector upgrades. I contributed to these upgrade efforts for the ATLAS detector, and am interested in working towards the HL-LHC upgrade of the CMS detector.