The Higgs Boson Talks to Itself! Using Machine Learning to Probe Higgs Boson Self-Interactions at the ATLAS Experiment

The discovery of the Higgs Boson in 2012 was a remarkable achievement for high energy physicists, but many of the details of the Higgs boson remain elusive. One especially interesting feature of the Higgs boson is how it interacts with itself. These self-interactions have significant implications for our universe, including the possibility that it may be fated for a sudden and catastrophic change. In this talk, I will discuss how we study the Higgs' self-interactions through measurements of the production of pairs of Higgs Bosons at the ATLAS experiment at the Large Hadron Collider. I'll focus on examples of how applications of machine learning towards searches for pairs of Higgs bosons has vastly improved our experimental knowledge of the Higgs boson, and how these methods will continue to propel measurements with the ATLAS detector in the future.