Tag - Extremal combinatorics
This talk will review two different results regarding the existence of Ramanujan graphs. While both methods employ the method of interlacing polynomials, they are thematically quite different. The goal will be to highlight some of the commonalities and differences.
The breakthrough work of Marcus, Spielman, and Srivastava showed that every bipartite Ramanujan graph has a bipartite Ramanujan double cover. Chris Hall, Doron Puder, and I generalized this to covers of arbitrary degree. I will explain the proof, with emphasis on how group theory and representation theory are useful for this problem.
Randomness is widely used in various areas of computer science, and many of the applications require uniform, uncorrelated bit. However, most sources of randomness in nature are defective and at best, only contain some amount of entropy. This leads to the area of randomness extraction, where an extractor is a deterministic procedure to produce pure random bits from a weak source. A central open problem (from the 80s) in this area is to extract from 2 independent weak sources (it is known that it is impossible to extract from just 1 weak source). In joint work with David Zuckerman, we resolve this problem. I will discuss the main ideas we use to solve this problem.
As a corollary of our 2-source extractor, we obtain exponential improvements in explicit constructions of Ramsey graphs, a central object in extremal combinatorics. This is in a line of work spanning the last 70 years in an attempt to meet Erdős's challenge of matching the probabilistic method.
We explain what Ramanujan graphs are, and prove that there exist infinite families of bipartite Ramanujan graphs of every degree. Our proof follows a plan suggested by Bilu and Linial, and exploits a proof of a conjecture of theirs about lifts of graphs. Our proof of their conjecture applies the method of interlacing families of polynomials to Mixed Characteristic Polynomials. A bound on the roots of these polynomials will follow from a bound of Heilmann and Lieb on the roots of the matching polynomials of graphs. We also prove that there exist infinite families of irregular bipartite Ramanujan graphs.
Random graphs and expander graphs can be viewed as sparse approximations of complete graphs, with Ramanujan expanders providing the best possible approximations. We formalize this notion of approximation and ask how well an arbitrary graph can be approximated by a sparse graph. We prove that every graph can be approximated by a sparse graph almost as well as the complete graphs are approximated by the Ramanujan expanders: our approximations employ at most twice as many edges to achieve the same approximation factor. Our algorithms follow from the solution of a problem in linear algebra. Given an expression for a rank-n symmetric matrix A as a sum of rank-1 symmetric matrices, we show that A can be well approximated by a weighted sum of only O(n) of those rank-1 matrices.
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