CAREER: Physics Implications of the String Landscape via Formal Theory and Data Science

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This CAREER award funds the research and education/outreach activities of Professor James Halverson at Northeastern University. String theory is the leading candidate for a theory of physics at the smallest length scales. It describes the fundamental building blocks of the universe, including the elementary particles whose interactions are measured at the Large Hadron Collider, and it also describes the sources of energy that drive the evolution of the cosmos. In this way string theory is capable of connecting particle physics and cosmology. The research funded by this award focuses on the implications of string theory for these two disciplines. There are two central challenges. First, certain aspects of string theory proper still remain to be understood. In particular, in collaboration with mathematicians, Halverson will study the regime in which strings interact strongly. An improved understanding of this regime is necessary for a complete understanding of string interactions. Second, string theory predicts a vast array of possible laws of physics --- an array known as the string landscape --- prompting the question of how the laws we observe are realized in nature and whether their realization leads to new predictions for experiments. From a practical point of view, however, the landscape can be viewed as an enormous dataset. As part of this project, Halverson, in collaboration with computer scientists, will therefore utilize techniques from data science and machine learning to study the landscape. Research in this area advances the national interest by promoting the progress of science in one of its most fundamental directions: the discovery and understanding of physical law. Halverson's research will also have significant broader impacts by enabling and engaging new communities of researchers. These include professionals in industry, high-school students, and the internet data-science community. Among Halverson's activities, a lecture series will be developed for and delivered to members of these communities in order to give them the essential background information for carrying out research at the interface of data science and string theory. More technically, Halverson will carry out formal work at strong coupling in string theory. He will study string junctions in F-theory on singular spaces, aspects of non-Higgsable clusters, and G2 compactifications of M-theory. He will also study physical problems in the string landscape using techniques from data science, including supervised learning, reinforcement learning, and generative adversarial networks. The interplay between computational complexity and the use of these techniques in physical problems will be addressed. Halverson will also study the particle physics and cosmological implications of the low-energy degrees of freedom that arise regularly in the landscape, including those associated with large dark gauge sectors and the string axiverse.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.