Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Kristin Heysse"'
Publikováno v:
Linear Algebra and Its Applications, 650, 1-25. Elsevier
We introduce the concept of codeterminantal graphs, which generalize the concepts of cospectral and coinvariant graphs. To do this, we investigate the relationship of the spectrum and the Smith normal form (SNF) with the determinantal ideals. We esta
Autor:
Brent Moran, Paul Horn, Steve Butler, Jay Cummings, Zhanar Berikkyzy, Kristin Heysse, Ruth Luo
Publikováno v:
Discrete Mathematics. 341:497-507
Consider the following process on a simple graph without isolated vertices: order the edges randomly and keep an edge if and only if it contains a vertex which is not contained in some preceding edge. The resulting set of edges forms a spanning fores
Publikováno v:
Discrete Mathematics. 341:492-496
For two graphs G and H , the Turan number ex ( G , H ) is the maximum number of edges in a subgraph of G that contains no copy of H . Chen, Li, and Tu determined the Turan numbers ex ( K m , n , k K 2 ) for all k ≥ 1 Chen et al. (2009). In this pap
Autor:
Kristin Heysse
Publikováno v:
Linear Algebra and its Applications. 535:195-212
The distance matrix of a connected graph is the symmetric matrix with columns and rows indexed by the vertices and entries that are the pairwise distances between the corresponding vertices. We give a construction for graphs which differ in their edg
The order ideal $B_{n,2}$ of the Boolean lattice $B_n$ consists of all subsets of size at most $2$. Let $F_{n,2}$ denote the poset refinement of $B_{n,2}$ induced by the rules: $i < j$ implies $\{i \} \prec \{ j \}$ and $\{i,k \} \prec \{j,k\}$. We g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11bf189370f8544c8462aa1ac25c4db3
Autor:
Leslie Hogben, Michael Tait, Jephian C.-H. Lin, Jessica De Silva, Aida Abiad, Kristin Heysse, Ghodratollah Aalipour, Jay Cummings, Franklin H. J. Kenter, Zhanar Berikkyzy, Wei Gao
Publikováno v:
Linear Algebra and Its Applications, 497, 66-87. Elsevier Science
The distance matrix of a graph $G$ is the matrix containing the pairwise distances between vertices. The distance eigenvalues of $G$ are the eigenvalues of its distance matrix and they form the distance spectrum of $G$. We determine the distance spec
Autor:
Kristin Heysse, Steve Butler
We give a construction of a family of (weighted) graphs that are pairwise cospectral with respect to the normalized Laplacian matrix, or equivalently probability transition matrix. This construction can be used to form pairs of cospectral graphs with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::80e906b234a0892dec01c417d848fbb9
Publikováno v:
The European Physical Journal Plus. 126
To approximate solutions of a linear differential equation, we project, via trigonometric interpolation, its solution space onto a finite-dimensional space of trigonometric polynomials and construct a matrix representation of the differential operato