Matches in SemOpenAlex for { <https://semopenalex.org/work/W171239498> ?p ?o ?g. }
- W171239498 abstract "Given a graph we can associate several matrices which record information about vertices and how they are interconnected. The question then arises, given that you know the eigenvalues of some matrix associated with the graph, what can you say about the graph? Spectral graph theory looks at answering questions of this type. In this dissertation we will be focusing on the eigenvalues of the normalized Laplacian of a matrix which is defined as L=D⁻¹ /²(D-A)D⁻¹/²where D is the diagonal matrix of degrees and A is the adjacency matrix of the graph. In addition to some background material on spectral graph theory we will be looking at three main results about how eigenvalues and structures of graphs are interrelated. These are as follows. * For any graph (including directed graphs) the edge discrepancy is a measurement of how randomly the edges are placed. While it has been known for some time that for undirected graphs that a tight clustering of eigenvalues around 1 implies a good measure of discrepancy, only recently has some progress been made in the other direction. We will show that for any graph (including directed graphs) that a small discrepancy implies a tight clustering of singular values of the normalized adjacency matrix. This shows that having small discrepancy and a tight clustering of singular values are in the same quasirandom class of properties for directed graphs. * Graphs which share common local structure tend to share eigenvalues. We will consider one type of covering that preserves local structures, namely 2-edge-coverings which, as the name strongly suggests, is a mapping from a graph G to a graph H so that each edge in H is twice covered. We show how to compute the eigenvalues of G from the eigenvalues of two modified forms of H. As an application we give a construction of two graphs which are not regular but are cospectral with respect to both the adjacency and normalized Laplacian matrix. * Given a graph G, the removal of a small graph will have an effect on the eigenvalues of the graph. We will show that the new eigenvalues will interlace the old eigenvalues (with the size of the interlacing dependent on the number of vertices in the graph which is removed). We will also mention some negative results about interlacing and a normalized Laplacian which has been introduced for directed graphs" @default.
- W171239498 created "2016-06-24" @default.
- W171239498 creator A5016572035 @default.
- W171239498 date "2008-01-01" @default.
- W171239498 modified "2023-09-27" @default.
- W171239498 title "Eigenvalues and structures of graphs" @default.
- W171239498 cites W1511439182 @default.
- W171239498 cites W1512996539 @default.
- W171239498 cites W1527695545 @default.
- W171239498 cites W1578099820 @default.
- W171239498 cites W1965091154 @default.
- W171239498 cites W1974499780 @default.
- W171239498 cites W1979908024 @default.
- W171239498 cites W2022582871 @default.
- W171239498 cites W2022707084 @default.
- W171239498 cites W2056975040 @default.
- W171239498 cites W2057551763 @default.
- W171239498 cites W2069992656 @default.
- W171239498 cites W2092642948 @default.
- W171239498 cites W2104550457 @default.
- W171239498 cites W2130270608 @default.
- W171239498 cites W2144987283 @default.
- W171239498 cites W2148780152 @default.
- W171239498 cites W2171567099 @default.
- W171239498 cites W247697463 @default.
- W171239498 cites W2610857016 @default.
- W171239498 cites W2901284226 @default.
- W171239498 cites W3043432241 @default.
- W171239498 hasPublicationYear "2008" @default.
- W171239498 type Work @default.
- W171239498 sameAs 171239498 @default.
- W171239498 citedByCount "21" @default.
- W171239498 countsByYear W1712394982013 @default.
- W171239498 countsByYear W1712394982014 @default.
- W171239498 countsByYear W1712394982015 @default.
- W171239498 countsByYear W1712394982016 @default.
- W171239498 countsByYear W1712394982017 @default.
- W171239498 countsByYear W1712394982018 @default.
- W171239498 countsByYear W1712394982019 @default.
- W171239498 countsByYear W1712394982020 @default.
- W171239498 crossrefType "journal-article" @default.
- W171239498 hasAuthorship W171239498A5016572035 @default.
- W171239498 hasConcept C105611402 @default.
- W171239498 hasConcept C105795698 @default.
- W171239498 hasConcept C114614502 @default.
- W171239498 hasConcept C115178988 @default.
- W171239498 hasConcept C118615104 @default.
- W171239498 hasConcept C121332964 @default.
- W171239498 hasConcept C132525143 @default.
- W171239498 hasConcept C149530733 @default.
- W171239498 hasConcept C158693339 @default.
- W171239498 hasConcept C160446614 @default.
- W171239498 hasConcept C162199024 @default.
- W171239498 hasConcept C180356752 @default.
- W171239498 hasConcept C187407849 @default.
- W171239498 hasConcept C203776342 @default.
- W171239498 hasConcept C22149727 @default.
- W171239498 hasConcept C33923547 @default.
- W171239498 hasConcept C43517604 @default.
- W171239498 hasConcept C612898 @default.
- W171239498 hasConcept C62520636 @default.
- W171239498 hasConcept C73555534 @default.
- W171239498 hasConcept C74003402 @default.
- W171239498 hasConcept C74133993 @default.
- W171239498 hasConcept C78913703 @default.
- W171239498 hasConceptScore W171239498C105611402 @default.
- W171239498 hasConceptScore W171239498C105795698 @default.
- W171239498 hasConceptScore W171239498C114614502 @default.
- W171239498 hasConceptScore W171239498C115178988 @default.
- W171239498 hasConceptScore W171239498C118615104 @default.
- W171239498 hasConceptScore W171239498C121332964 @default.
- W171239498 hasConceptScore W171239498C132525143 @default.
- W171239498 hasConceptScore W171239498C149530733 @default.
- W171239498 hasConceptScore W171239498C158693339 @default.
- W171239498 hasConceptScore W171239498C160446614 @default.
- W171239498 hasConceptScore W171239498C162199024 @default.
- W171239498 hasConceptScore W171239498C180356752 @default.
- W171239498 hasConceptScore W171239498C187407849 @default.
- W171239498 hasConceptScore W171239498C203776342 @default.
- W171239498 hasConceptScore W171239498C22149727 @default.
- W171239498 hasConceptScore W171239498C33923547 @default.
- W171239498 hasConceptScore W171239498C43517604 @default.
- W171239498 hasConceptScore W171239498C612898 @default.
- W171239498 hasConceptScore W171239498C62520636 @default.
- W171239498 hasConceptScore W171239498C73555534 @default.
- W171239498 hasConceptScore W171239498C74003402 @default.
- W171239498 hasConceptScore W171239498C74133993 @default.
- W171239498 hasConceptScore W171239498C78913703 @default.
- W171239498 hasLocation W1712394981 @default.
- W171239498 hasOpenAccess W171239498 @default.
- W171239498 hasPrimaryLocation W1712394981 @default.
- W171239498 hasRelatedWork W1251771716 @default.
- W171239498 hasRelatedWork W1539300479 @default.
- W171239498 hasRelatedWork W1578099820 @default.
- W171239498 hasRelatedWork W1587744656 @default.
- W171239498 hasRelatedWork W1603500723 @default.
- W171239498 hasRelatedWork W1668045384 @default.
- W171239498 hasRelatedWork W1984878954 @default.
- W171239498 hasRelatedWork W2030683030 @default.
- W171239498 hasRelatedWork W2057731281 @default.