Quantitative quasirandomness

20 October 2015
Benny Sudakov

A graph is quasirandom if its edge distribution is similar (in a well defined quantitative way) to that of a random graph with the same edge density. Classical results of Thomason and Chung-Graham-Wilson show that a variety of graph properties are equivalent to quasirandomness. On the other hand, in some known proofs the error terms which measure quasirandomness can change quite dramatically when going from one property to another which might be problematic in some applications.

Simonovits and Sós proved that the property that all induced subgraphs have about the expected number of copies of a fixed graph $H$ is quasirandom. However, their proof relies on the regularity lemma and gives a very weak estimate. They asked to find a new proof for this result with a better estimate. The purpose of this talk is to accomplish this.

Joint work with D. Conlon and J. Fox

  • Combinatorial Theory Seminar