CAREER: Graph Profiles: Complexity and Computations

Many problems in engineering, science, economics, and social sciences involve complicated systems that can be represented as graphs. For example, road networks, the human brain, social networks, and interactions between proteins can all be represented as graphs. Computing different properties of these graphs yields valuable information about the original problems, but it is difficult to do so because of the size of the graphs. One technique to study such large graphs is to understand them locally by determining how prevalent certain small substructures are, for example through homomorphism densities. The objective of this project is to further our understanding of graph profiles, objects that record all possible relationships between these local patterns. This project also seeks to make higher-level math, in particular discrete mathematics, accessible to a greater segment of the population. The research component of this project will focus on four directions: (1) to compute graph profiles, including some in more than two dimensions; (2) to study the strengths and limitations of different techniques (e.g., (rational) sums of squares, sums of nonnegative circuits) in proving inequalities over graph profiles; (3) to better understand for which classes of inequalities certification over graph profiles is (un)decidable; (4) to build theory and compute tropicalizations of graph profiles, which are simpler and yet capture all valid pure binomial inequalities, and to use these computations to resolve problems in extremal graph theory. 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.