Grant: Discovery Grants Program - Individual
Redeemer University College
$15,000.00
Combinatorial matrix analysis and algebra
EF 2019-20
Résumé
The focus of my work is developing techniques and structures for exploring the interplay of two areas of mathematics: algebra and graph theory.***One of the most fundamental tasks of mathematics is finding the solutions of equations. A particularly curious fact, discovered in the early 19th century, is that relatively simple polynomial equations, of degree 5 or higher, do not allow for algebraic solutions. Consequently, numerical methods have been developed to find roots of polynomial equations. One method finds the eigenvalues of a Frobenius companion matrix, used for example in the roots command in MATLAB software. ****Our recent and surprising discovery of intercyclic companion matrices may provide useful and efficient alternatives to the Frobenius companion matrix, as well as new bounds on the roots of a polynomial. I plan to use the newer intercyclic companion matrices to provide new bounds, and to characterize under which conditions these new bounds are sharper than those from Frobenius, or the more recent Fiedler matrices. ****I plan to explore properties of the non-sparse companion matrices and generalized companion matrices. There is evidence that these too may improve efficiency of algorithms; one particular goal is to find versions that readily succumb to balancing, to provide well-conditioned matrices, while retaining their advantageous structure. I also plan to explore non-sparse patterns to determine which are most amenable to efficient splitting techniques and sharper bounds.****I plan to uncover eigenvalue properties of matrix patterns, determining which matrix patterns (such as sign patterns) have specific useful properties. The study of sign pattern matrices has some origins in the work of Nobel Laureate P. Samuelson in economics, but has growing interest in other modeling contexts. Recently matrix pattern analysis has been applied to machine learning, and also to detect the possibility of periodicity in biological and ecological systems. I do not plan to focus directly on applications, but instead my focus will be on developing theory that may prove useful in future modeling and algorithmic applications. As such my work is pure mathematics. One of my contributions will be to develop constructions, techniques, and properties of refined inertially arbitrary patterns. As one unique approach, I will use zero patterns to gain insight into the combinatorial structure of the sign patterns. ****I also plan to explore algebraic properties of graphs (e.g. network structures): I plan to develop some algebraic techniques for a classic problem of Graham and Pollack on graph addressing. I will also continue to develop properties of graphs related to the edge ideal of a well-covered graph specifically focusing on the vertex-decomposability of a graph and properties of the set of shedding vertices. ***My projects involve parts that are suitable for training of HQP at the graduate and undergraduate level.**
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Other
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RGPIN-2016-03867
Name nom
VanderMeulen, Kevin
Department département
Mathematics
Organization id
1697
Institution établissement
Redeemer University College
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2019
Competition year année de concours
2016
Award amount
15000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1508
Committee name en
Mathematics and Statistics
Committee name fr
Mathématiques et statistique
Area of application code
1200
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Advancement of knowledge
Area of application fr
Avancement des connaissances
Research subject code
2908
Research subject group en
Pure mathematics
Research subject group fr
Mathématiques pures
Research subject en
Algebra
Research subject fr
algèbre
Installment
inst:4 - 5
Partie
4
Nb partie
5
Application title
Combinatorial matrix analysis and algebra
Keyword
NSERC
Application summary
The focus of my work is developing techniques and structures for exploring the interplay of two areas of mathematics: algebra and graph theory.***One of the most fundamental tasks of mathematics is finding the solutions of equations. A particularly curious fact, discovered in the early 19th century, is that relatively simple polynomial equations, of degree 5 or higher, do not allow for algebraic solutions. Consequently, numerical methods have been developed to find roots of polynomial equations. One method finds the eigenvalues of a Frobenius companion matrix, used for example in the roots command in MATLAB software. ****Our recent and surprising discovery of intercyclic companion matrices may provide useful and efficient alternatives to the Frobenius companion matrix, as well as new bounds on the roots of a polynomial. I plan to use the newer intercyclic companion matrices to provide new bounds, and to characterize under which conditions these new bounds are sharper than those from Frobenius, or the more recent Fiedler matrices. ****I plan to explore properties of the non-sparse companion matrices and generalized companion matrices. There is evidence that these too may improve efficiency of algorithms; one particular goal is to find versions that readily succumb to balancing, to provide well-conditioned matrices, while retaining their advantageous structure. I also plan to explore non-sparse patterns to determine which are most amenable to efficient splitting techniques and sharper bounds.****I plan to uncover eigenvalue properties of matrix patterns, determining which matrix patterns (such as sign patterns) have specific useful properties. The study of sign pattern matrices has some origins in the work of Nobel Laureate P. Samuelson in economics, but has growing interest in other modeling contexts. Recently matrix pattern analysis has been applied to machine learning, and also to detect the possibility of periodicity in biological and ecological systems. I do not plan to focus directly on applications, but instead my focus will be on developing theory that may prove useful in future modeling and algorithmic applications. As such my work is pure mathematics. One of my contributions will be to develop constructions, techniques, and properties of refined inertially arbitrary patterns. As one unique approach, I will use zero patterns to gain insight into the combinatorial structure of the sign patterns. ****I also plan to explore algebraic properties of graphs (e.g. network structures): I plan to develop some algebraic techniques for a classic problem of Graham and Pollack on graph addressing. I will also continue to develop properties of graphs related to the edge ideal of a well-covered graph specifically focusing on the vertex-decomposability of a graph and properties of the set of shedding vertices. ***My projects involve parts that are suitable for training of HQP at the graduate and undergraduate level.**