ATLAS Bridging Application: Di-Higgs Processes as a Window to the Standard Model and Beyond

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The Large Hadron Collider (LHC) collides protons at the highest energy conditions of any facility in the world, recreating conditions a fraction of a second after the Big Bang. We record the outcomes of these collisions with the ATLAS detector, and we use this data to understand the fundamental building blocks of the universe and the forces which bind them together. In 2012 ATLAS (and another experiment, CMS) discovered a new particle, the Higgs boson. This particle is thought to play a critical role in our understanding of the universe by providing other particles their masses. While this discovery of the Higgs Boson resolved one set of questions, a whole host of new ones has emerged. The most pressing is about the nature of the Higgs mechanism, the process which provides the other particles their masses. My research program addresses this question by searching for collisions producing not just one Higgs boson, but two. These events are extremely rare: only roughly one in a trillion collisions produces two Higgs bosons at once. We use advanced data analysis techniques to pick out this delicate needle from the haystack, but the challenge is worthwhile: these events can hold clues to the shape of the Higgs energy potential and the fundamental mechanism that provides particles their masses. Additionally, the conditions just moments after the Big Bang could be imprinted onto this same Higgs energy potential: if we are able to measure this, we could see a relic of the universe's birth. Discovering these double Higgs events could revolutionize our understanding of the universe, allowing us to see not just how the universe works but how it evolved to its current state, explaining the why we are made of only matter and not anti-matter. I intend to place Canadian scientists at the forefront of the global effort to discover these processes and understand their consequences. A second key component of my research program is the full utilization of information that our detectors provide. Since the Higgs boson is not stable, observing pairs of Higgs bosons requires that we accurately measure particles they decay into. The most common decay is into b-quarks, which themselves form complicated sprays of particles called jets which we can measure with ATLAS's inner detector and calorimeter systems. I intend to use deep learning techniques, inspired by developments in image recognition technology, to revolutionize how we measure the energy of the particles that make up jets. In the same way that machine learning has revolutionized photography through the combination of several images at once, we can combine low level information from the detector and algorithms designed and tuned by physicists to significantly sharpen our understanding of the collisions we are observing. By improving the quality of the data we are taking, we can make the most of the significant Canadian investment in ATLAS's upgrades and accelerate our road to discoveries.