Applications of Graph Spectra in Computer Science
In graph theory, the spectra of matrices associated with a graph are widely used to characterize its properties and to extract structural information. There are several graph matrix representations such as the adjacency matrix, combinatorial Laplacian, normalized Laplacian and signless Laplacian. Spectral graph theory has also many applications in other scientific fields such as chemistry, theoretical physics, and quantum mechanics. The aim of this workshop is to foster the connections between spectral graph theory and computer science.