Mathematics Without Calculations – It’s a Beautiful Thing!

All students should have the opportunity to do mathematics in a meaningful way for the sheer fun of it. Such experiences, if well designed, improve students’ effective thinking skills, increase their appreciation of the beauty and utility of mathematics, and prepare them to be mathematically-literate members of society. This session invites talks on how we can engage the liberal arts student through courses specifically designed for them. We welcome presentations on innovative course design, pedagogy, projects, or activities, as well as talks on tools used to assess such courses. Presentations should include a research basis for the design or pedagogical choices, a report on outcomes in student learning or attitude, or other evidence of success. Papers about programs demonstrating success engaging students who enter the course reluctant to engage in mathematics are especially encouraged. We also welcome talks on first year seminars or other experiences that engage first year students in doing mathematics as well as Honors courses in mathematics that incorporate the liberal arts

Is Mathematics Created by Humans or is it Discovered by Humans? A Catholic Intellectual Perspective

In this essay, Dr. Molitierno intends to show that not only is it appropriate to discuss the Catholic Intellectual Tradition in light of mathematics, the CIT can actually be exemplified in mathematics

Tight Bounds on the Algebraic Connectivity of a Balanced Binary Tree

In this paper, quite tight lower and upper bounds are obtained on the algebraic connectivity, namely, the second-smallest eigenvalue of the Laplacian matrix, of an unweighted balanced binary tree with k levels and hence n = 2k - 1 vertices. This is accomplished by considering the inverse of a matrix of order k - 1 readily obtained from the Laplacian matrix. It is shown that the algebraic connectivity is 1/(2k - 2k + 3) + 0(1/22k)

On some properties of the Laplacian matrix revealed by the RCM algorithm

In this paper we present some theoretical results about the irreducibility of the Laplacian matrix ordered by the Reverse Cuthill-McKee (RCM) algorithm. We consider undirected graphs with no loops consisting of some connected components. RCM is a well-known scheme for numbering the nodes of a network in such a way that the corresponding adjacency matrix has a narrow bandwidth. Inspired by some properties of the eigenvectors of a Laplacian matrix, we derive some properties based on row sums of a Laplacian matrix that was reordered by the RCM algorithm. One of the theoretical results serves as a basis for writing an easy MATLAB code to detect connected components, by using the function “symrcm” of MATLAB. Some examples illustrate the theoretical results.The research has been supported by Spanish DGI grant MTM2010-18674, Consolider Ingenio CSD2007-00022, PROMETEO 2008/051, OVAMAH TIN2009-13839-C03-01, and PAID-06-11-2084.Pedroche Sánchez, F.; Rebollo Pedruelo, M.; Carrascosa Casamayor, C.; Palomares Chust, A. (2016). On some properties of the Laplacian matrix revealed by the RCM algorithm. Czechoslovak Mathematical Journal. 66(3):603-620. doi:10.1007/s10587-016-0281-yS60362066

A Tight Upper Bound on the Spectral Radius of Bottleneck Matrices for Graphs

In this paper, we find a tight upper bound on the spectral radius of bottleneck matrices for graphs. We use this upper bound to find a tight lower bound on the algebraic connectivity of graphs in terms of the radius of the graph. We show that these lower bounds are an improvement on those found in[9]

The Spectral Radius of Submatrices of Laplacian Matrices for Trees and Its Comparison to the Fiedler Vector

We consider the effects on the spectral radius of submatrices of the Laplacian matrix for graphs by deleting the row and column corresponding to various vertices of the graph. We focus most of our attention on trees and determine which vertices v will yield the maximum and minimum spectral radius of the Laplacian when row v and column v are deleted. At this point, comparisons are made between these results and results concerning the Fiedler vector of the tree

The Spectral Radius of Submatrices of Laplacian Matrices for Trees and Its Comparison to the Fiedler Vector

We consider the effects on the spectral radius of submatrices of the Laplacian matrix for graphs by deleting the row and column corresponding to various vertices of the graph. We focus most of our attention on trees and determine which vertices v will yield the maximum and minimum spectral radius of the Laplacian when row v and column v are deleted. At this point, comparisons are made between these results and results concerning the Fiedler vector of the tree

Applications of Combinatorial Matrix Theory to Laplacian Matrices of Graphs

On the surface, matrix theory and graph theory are seemingly very different branches of mathematics. However, these two branches of mathematics interact since it is often convenient to represent a graph as a matrix. Adjacency, Laplacian, and incidence matrices are commonly used to represent graphs. In 1973, Fiedler published his first paper on Laplacian matrices of graphs and showed how many properties of the Laplacian matrix, especially the eigenvalues, can give us useful information about the structure of the graph. Since then, many papers have been published on Laplacian matrices. This book is a compilation of many of the exciting results concerning Laplacian matrices that have been developed since the mid 1970\u27s. Papers written by well-known mathematicians such as (alphabetically) Fallat, Fiedler, Grone, Kirkland, Merris, Mohar, Neumann, Shader, Sunder, and several others are consolidated here. Each theorem is referenced to its appropriate paper so that the reader can easily do more in-depth research on any topic of interest. However, the style of presentation in this book is not meant to be that of a journal but rather a reference textbook. Therefore, more examples and more detailed calculations are presented in this book than would be in a journal article. Additionally, most sections are followed by exercises to aid the reader in gaining a deeper understanding of the material. Some exercises are routine calculations that involve applying the theorems presented in the section. Other exercises require a more in-depth analysis of the theorems and require the reader to prove theorems that go beyond what was presented in the section. Many of these exercises are taken from relevant papers and they are referenced accordingly

Entries of the Group Inverse of the Laplacian Matrix for Generalized Johnson Graphs

In this paper, we use graph theoretic properties of generalized Johnson graphs to compute the entries of the group inverse of Laplacian matrices for generalized Johnson graphs. We then use these entries to compute the Zenger function for the group inverse of Laplacian matrices of generalized Johnson graphs

The Spectral Radius of Submatrices of Laplacian Matrices for Graphs with Cut Vertices

We observed the effects on the spectral radius of submatrices of the Laplacian matrix L for a tree by deleting a row and column of L corresponding to a vertex of the tree. This enabled us to classify trees as either of Type A or Type B. In this paper, we extend these results to graphs which are not trees and offer a similar classification. Additionally, we show counterexamples to theorems that are true for trees, but not so for general graphs