Spectral Techniques in Combinatorics
Eigenvalue methods provide powerful tools for proving combinatorial results that seem purely structural. The interplay between algebraic properties of graph matrices and combinatorial structure is a central theme of modern graph theory.
The Expander Mixing Lemma
For a -regular graph with second eigenvalue : for all vertex sets , where counts edges between and . When (spectral gap is large), edge distribution is close to random: every pair of large sets has approximately the "expected" number of edges.
Using the expander mixing lemma for a -graph (regular, vertices, degree , second eigenvalue ):
- Independence number: (from the Hoffman bound).
- Chromatic number: (since independent sets are small).
- Diameter: (powers of fill in edges).
- Counting subgraphs: the number of copies of small fixed graph is close to the expected count in a random -regular graph.
Interlacing and Graph Minors
If is a principal submatrix of a symmetric matrix (obtained by deleting rows and columns), then the eigenvalues interlace: where is . For graphs: deleting a vertex can decrease each eigenvalue by at most the amount removed. This constrains how the spectrum changes under vertex deletion and is used to prove bounds on clique number, chromatic number, and maximum cut.
For a graph with vertices and edges: where is the most negative eigenvalue. For random graphs, , giving . The Goemans-Williamson SDP relaxation achieves a 0.878-approximation for max-cut, with the SDP matrix related to the Laplacian.
Strongly Regular Graphs
A strongly regular graph is -regular with every pair of adjacent vertices having common neighbors and every pair of non-adjacent vertices having common neighbors. The adjacency matrix satisfies , giving eigenvalues (multiplicity 1), , . Feasibility conditions from integrality of multiplicities severely restrict which parameter sets are realizable.
The Petersen graph has parameters : 3-regular, no triangles (), every non-adjacent pair has exactly 1 common neighbor (). Eigenvalues: (mult. 1), (mult. 5), (mult. 4). The three eigenvalues and their multiplicities encode the full structure: the Petersen graph is determined by its spectrum among strongly regular graphs.