scholarly journals SPN Graphs

2019 ◽  
Vol 35 ◽  
pp. 376-386
Author(s):  
Leslie Hogben ◽  
Naomi Shaked-Monderer
Keyword(s):  
Linear Algebra ◽  
Nonnegative Matrix ◽  
Positive Semidefinite ◽  
Simple Graph ◽  
Subdivision Graph ◽  
Copositive Matrix

A simple graph G is an SPN graph if every copositive matrix having graph G is the sum of a positive semidefinite and nonnegative matrix. SPN graphs were introduced in [N. Shaked-Monderer. SPN graphs: When copositive = SPN. Linear Algebra Appl., 509:82{113, 2016.], where it was conjectured that the complete subdivision graph of K4 is an SPN graph. This conjecture is disproved, which in conjunction with results in the Shaked-Monderer paper show that a subdivision of K_4 is a SPN graph if and only if at most one edge is subdivided. It is conjectured that a graph is an SPN graph if and only if it does not have an F_5 minor, where F_5 is the fan on five vertices. To establish that the complete subdivision graph of K_4 is not an SPN graph, rank-1 completions are introduced and graphs that are rank-1 completable are characterized.

scholarly journals The triangle graph $T_6$ is not SPN

2020 ◽  
Vol 36 (36) ◽  
pp. 90-93
Author(s):  
Stephen Drury
Keyword(s):  
Symmetric Matrix ◽  
Nonnegative Matrix ◽  
Positive Semidefinite ◽  
Positive Semidefinite Matrix ◽  
Real Symmetric Matrix ◽  
Triangle Graph ◽  
Nonnegative Vector ◽  
Copositive Matrix ◽  
Semidefinite Matrix

A real symmetric matrix $A$ is copositive if $x'Ax \geq 0$ for every nonnegative vector $x$. A matrix is SPN if it is a sum of a real positive semidefinite matrix and a nonnegative matrix. Every SPN matrix is copositive, but the converse does not hold for matrices of order greater than $4$. A graph $G$ is an SPN graph if every copositive matrix whose graph is $G$ is SPN. We show that the triangle graph $T_6$ is not SPN.

scholarly journals Power graphs and exchange property for resolving sets

2019 ◽  
Vol 17 (1) ◽  
pp. 1303-1309 ◽  
Author(s):  
Ghulam Abbas ◽  
Usman Ali ◽  
Mobeen Munir ◽  
Syed Ahtsham Ul Haq Bokhary ◽  
Shin Min Kang
Keyword(s):  
Present Article ◽  
Linear Algebra ◽  
Finite Groups ◽  
Robot Navigation ◽  
Simple Graph ◽  
Exchange Property ◽  
Metric Dimension ◽  
Sufficient Condition ◽  
Resolving Set ◽  
Dihedral Groups

Abstract Classical applications of resolving sets and metric dimension can be observed in robot navigation, networking and pharmacy. In the present article, a formula for computing the metric dimension of a simple graph wihtout singleton twins is given. A sufficient condition for the graph to have the exchange property for resolving sets is found. Consequently, every minimal resolving set in the graph forms a basis for a matriod in the context of independence defined by Boutin [Determining sets, resolving set and the exchange property, Graphs Combin., 2009, 25, 789-806]. Also, a new way to define a matroid on finite ground is deduced. It is proved that the matroid is strongly base orderable and hence satisfies the conjecture of White [An unique exchange property for bases, Linear Algebra Appl., 1980, 31, 81-91]. As an application, it is shown that the power graphs of some finite groups can define a matroid. Moreover, we also compute the metric dimension of the power graphs of dihedral groups.

scholarly journals Some algorithms for maximum volume and cross approximation of symmetric semidefinite matrices

2021 ◽  
Author(s):  
Stefano Massei
Keyword(s):  
Computer Science ◽  
Recent Work ◽  
Linear Algebra ◽  
Optimization Problems ◽  
Approximation Error ◽  
Positive Semidefinite ◽  
Numerical Linear Algebra ◽  
Maximum Volume ◽  
Deterministic Algorithms ◽  
Principal Submatrix

AbstractVarious applications in numerical linear algebra and computer science are related to selecting the $$r\times r$$ r × r submatrix of maximum volume contained in a given matrix $$A\in \mathbb R^{n\times n}$$ A ∈ R n × n . We propose a new greedy algorithm of cost $$\mathcal O(n)$$ O ( n ) , for the case A symmetric positive semidefinite (SPSD) and we discuss its extension to related optimization problems such as the maximum ratio of volumes. In the second part of the paper we prove that any SPSD matrix admits a cross approximation built on a principal submatrix whose approximation error is bounded by $$(r+1)$$ ( r + 1 ) times the error of the best rank r approximation in the nuclear norm. In the spirit of recent work by Cortinovis and Kressner we derive some deterministic algorithms, which are capable to retrieve a quasi optimal cross approximation with cost $$\mathcal O(n^3)$$ O ( n 3 ) .

scholarly journals An elementary proof of Chollet’s permanent conjecture for 4 × 4 real matrices

2021 ◽  
Vol 9 (1) ◽  
pp. 83-102
Author(s):  
George Hutchinson
Keyword(s):  
Linear Algebra ◽  
Elementary Proof ◽  
Positive Semidefinite ◽  
Real Matrices

Abstract A proof of the statement per(A ∘ B) ≤ per(A)per(B) is given for 4 × 4 positive semidefinite real matrices. The proof uses only elementary linear algebra and a rather lengthy series of simple inequalities.

scholarly journals Solution to a Conjecture on the Maximum Skew-Spectral Radius of Odd-Cycle Graphs

10.37236/4919 ◽  
2015 ◽  
Vol 22 (1) ◽  
Author(s):  
Xiaolin Chen ◽  
Xueliang Li ◽  
Huishu Lian
Keyword(s):  
Spectral Radius ◽  
Linear Algebra ◽  
Upper Bounds ◽  
Simple Graph ◽  
Vertex Degree ◽  
Maximum Matching ◽  
Extremal Graphs ◽  
Odd Cycle ◽  
Cycle Graph

Let $G$ be a simple graph with no even cycle, called an odd-cycle graph. Cavers et al. [Linear Algebra Appl. 436(12):4512-1829, 2012] showed that the spectral radius of $G^\sigma$ is the same for every orientation $\sigma$ of $G$, and equals the maximum matching root of $G$. They proposed a conjecture that the graphs which attain the maximum skew spectral radius among the odd-cycle graphs $G$ of order $n$ are isomorphic to the odd-cycle graph with one vertex degree $n-1$ and size $m=\lfloor 3(n-1)/2\rfloor$. By using the Kelmans transformation, we give a proof to the conjecture. Moreover, sharp upper bounds of the maximum matching roots of the odd-cycle graphs with given order $n$ and size $m$ are given and extremal graphs are characterized.

scholarly journals The maximal angle between 5×5 positive semidefinite and 5×5 nonnegative matrices

2021 ◽  
Vol 37 ◽  
pp. 698-708
Author(s):  
Qinghong Zhang
Keyword(s):  
Optimization Problem ◽  
Nonnegative Matrix ◽  
Positive Semidefinite ◽  
Problem Solver ◽  
Nonnegative Matrices ◽  
Geometric Program ◽  
Maximal Angle ◽  
Method Of Lagrange Multipliers ◽  
Semidefinite Matrix ◽  
Signomial Geometric Programming

The paper is devoted to the study of the maximal angle between the $5\times 5$ semidefinite matrix cone and $5\times 5$ nonnegative matrix cone. A signomial geometric programming problem is formulated in the process to find the maximal angle. Instead of using an optimization problem solver to solve the problem numerically, the method of Lagrange Multipliers is used to solve the signomial geometric program, and therefore, to find the maximal angle between these two cones.

A Singular Value Inequality Related to a Linear Map

2016 ◽  
Vol 31 ◽  
pp. 120-124 ◽  
Author(s):  
Minghua Lin
Keyword(s):  
Linear Algebra ◽  
Positive Semidefinite ◽  
Singular Value ◽  
Linear Map

If $\begin{bmatrix}A & X \\ X^* & B\end{bmatrix}$ is positive semidefinite with each block $n\times n$, we prove that $$2s_j\Big(\Phi(X)\Big)\le s_j\Big(\Phi(A+B)\Big), \qquad j=1, \ldots, n,$$ where $\Phi: X\mapsto X+(\tr X)I$ and $s_j(\cdot)$ means the $j$-th largest singular value. This confirms a conjecture of the author in [Linear Algebra Appl. 459 (2014) 404-410].

scholarly journals Optimal Gersgorin-style estimation of the largest singular value. II

2016 ◽  
Vol 31 ◽  
pp. 679-685
Author(s):  
Charles Johnson ◽  
J. Pena ◽  
Tomasz Szulc
Keyword(s):  
Spectral Radius ◽  
Linear Algebra ◽  
Nonnegative Matrix ◽  
Singular Value ◽  
Nonnegative Matrices ◽  
Electronic Journal ◽  
Complex Matrix ◽  
Class Of Matrices

In estimating the largest singular value in the class of matrices equiradial with a given $n$-by-$n$ complex matrix $A$, it was proved that it is attained at one of $n(n-1)$ sparse nonnegative matrices (see C.R.~Johnson, J.M.~Pe{\~n}a and T.~Szulc, Optimal Gersgorin-style estimation of the largest singular value; {\em Electronic Journal of Linear Algebra Algebra Appl.}, 25:48--59, 2011). Next, some circumstances were identified under which the set of possible optimizers of the largest singular value can be further narrowed (see C.R.~Johnson, T.~Szulc and D.~Wojtera-Tyrakowska, Optimal Gersgorin-style estimation of the largest singular value, {\it Electronic Journal of Linear Algebra Algebra Appl.}, 25:48--59, 2011). Here the cardinality of the mentioned set for $n$-by-$n$ matrices is further reduced. It is shown that the largest singular value, in the class of matrices equiradial with a given $n$-by-$n$ complex matrix, is attained at one of $n(n-1)/2$ sparse nonnegative matrices. Finally, an inequality between the spectral radius of a $3$-by-$3$ nonnegative matrix $X$ and the spectral radius of a modification of $X$ is also proposed.

Core of a matrix in max algebra and in nonnegative algebra: A survey

2019 ◽  
pp. 252-271
Author(s):  
Peter BUTKOVIC ◽  
Hans SCHNEIDER ◽  
Sergei SERGEEV
Keyword(s):  
Linear Algebra ◽  
Ergodic Theory ◽  
Nonnegative Matrix ◽  
Max Algebra ◽  
Similarities And Differences

This paper presents a light introduction to Perron-Frobenius theory in max algebra and in nonnegative linear algebra, and a survey of results on two cores of a nonnegative matrix. The (usual) core of a nonnegative matrix is defined as ∩ k≥1 span+ (A k ) , that is, intersection of the nonnegative column spans of matrix powers. This object is of importance in the (usual) Perron-Frobenius theory, and it has some applications in ergodic theory. We develop the direct max-algebraic analogue and follow the similarities and differences of both theories.

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