
Let \(G=(V,E)\) be an arbitrary graph, and \(d_ i>0\) be the degree of the vertex \(v_ i\in V\). D(G) denotes the diagonal matrix whose (i,i)-entry is \(d_ i\), and A(G) denotes the adjacency matrix of the graph G. The matrix \(L(G)=D(G)-A(G)\) will be called the Laplacian matrix of the graph G. Brualdi and the author have obtained bounds for PerL(G) where PerL(G) is the permanent of the matrix L(G) and G is a bipartite graph. They have also introduced the notion of the Laplacian ratio \(\pi (G)=PerL(G)/d_ 1d_ 2\cdot \cdot \cdot d_ n\) and obtained a lower bound for \(\pi\) (G) where G is a bipartite graph. In this work upper and lower bounds are obtained for \(\pi\) (T), namely \(\pi (T)\geq \pi (C_ k)\) and \(\pi\) (T)\(\leq 2\) k, where T is a tree, k is the maximal number of independent edges of T, and \(C_ k\) is the tree obtained by adjoining a pendant edge to each vertex of the path \(P_ k\).
adjacency matrix, Graphs and linear algebra (matrices, eigenvalues, etc.), Determinants, permanents, traces, other special matrix functions, permanent, Theoretical Computer Science, upper bounds, lower bounds, Edge subsets with special properties (factorization, matching, partitioning, covering and packing, etc.), bipartite graph, Discrete Mathematics and Combinatorics, Laplacian matrix, Combinatorial aspects of matrices (incidence, Hadamard, etc.)
adjacency matrix, Graphs and linear algebra (matrices, eigenvalues, etc.), Determinants, permanents, traces, other special matrix functions, permanent, Theoretical Computer Science, upper bounds, lower bounds, Edge subsets with special properties (factorization, matching, partitioning, covering and packing, etc.), bipartite graph, Discrete Mathematics and Combinatorics, Laplacian matrix, Combinatorial aspects of matrices (incidence, Hadamard, etc.)
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 13 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
