Convergence of sparse graphs as a problem at the intersection of graph theory, statistical physics and probability

Series
ACO Seminar
Time
Tuesday, November 26, 2013 - 2:05pm for 1 hour (actually 50 minutes)
Location
Skiles 005
Speaker
Christian Borgs – Microsoft Research (New England), Cambridge, MA – borgs@microsoft.com
Organizer
Prasad Tetali
Many real-world graphs are large and growing. This naturally raises the question of a suitable concept of graph convergence. For graphs with average degree proportional to the number of vertices (dense graphs), this question is by now quite well-studied. But real world graphs tend to be sparse, in the sense that the average or even the maximal degree is bounded by some reasonably small constant. In this talk, I study several notions of convergence for graphs of bounded degree and show that, in contrast to dense graphs, where various a priori different notions of convergence are equivalent, the corresponding notions are not equivalent for sparse graphs. I then describe a notion of convergence formulated in terms of a large deviation principle which implies all previous notions of convergence.