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Sharp Upper Bounds on the Signless Laplacian Spectral Radius of Strongly Connected Digraphs

Weige Xi, Ligong Wang (2016)

Discussiones Mathematicae Graph Theory

Let G = (V (G),E(G)) be a simple strongly connected digraph and q(G) be the signless Laplacian spectral radius of G. For any vertex vi ∈ V (G), let d+i denote the outdegree of vi, m+i denote the average 2-outdegree of vi, and N+i denote the set of out-neighbors of vi. In this paper, we prove that: (1) (1) q(G) = d+1 +d+2 , (d+1 ≠ d+2) if and only if G is a star digraph [...] ,where d+1, d+2 are the maximum and the second maximum outdegree, respectively [...] is the digraph on n vertices obtained...

Sign patterns that allow eventual positivity.

Berman, Abraham, Catral, Minerva, Dealba, Luz Maria, Elhashash, Abed, Hall, Frank J., Hogben, Leslie, Kim, In-Jae, Olesky, Dale D., Tarazaga, Pablo, Tsatsomeros, Michael J., van den Driessche, Pauline (2009)

ELA. The Electronic Journal of Linear Algebra [electronic only]

Signatura of magic and Latin integer squares: isentropic clans and indexing

Ian Cameron, Adam Rogers, Peter D. Loly (2013)

Discussiones Mathematicae Probability and Statistics

The 2010 study of the Shannon entropy of order nine Sudoku and Latin square matrices by Newton and DeSalvo [Proc. Roy. Soc. A 2010] is extended to natural magic and Latin squares up to order nine. We demonstrate that decimal and integer measures of the Singular Value sets, here named SV clans, are a powerful way of comparing different integer squares. Several complete sets of magic and Latin squares are included, including the order eight Franklin subset which is of direct relevance...

Solvability classes for core problems in matrix total least squares minimization

Iveta Hnětynková, Martin Plešinger, Jana Žáková (2019)

Applications of Mathematics

Linear matrix approximation problems A X B are often solved by the total least squares minimization (TLS). Unfortunately, the TLS solution may not exist in general. The so-called core problem theory brought an insight into this effect. Moreover, it simplified the solvability analysis if B is of column rank one by extracting a core problem having always a unique TLS solution. However, if the rank of B is larger, the core problem may stay unsolvable in the TLS sense, as shown for the first time by Hnětynková,...

Some graphs determined by their (signless) Laplacian spectra

Muhuo Liu (2012)

Czechoslovak Mathematical Journal

Let W n = K 1 C n - 1 be the wheel graph on n vertices, and let S ( n , c , k ) be the graph on n vertices obtained by attaching n - 2 c - 2 k - 1 pendant edges together with k hanging paths of length two at vertex v 0 , where v 0 is the unique common vertex of c triangles. In this paper we show that S ( n , c , k ) ( c 1 , k 1 ) and W n are determined by their signless Laplacian spectra, respectively. Moreover, we also prove that S ( n , c , k ) and its complement graph are determined by their Laplacian spectra, respectively, for c 0 and k 1 .

Some properties of generalized distance eigenvalues of graphs

Yuzheng Ma, Yan Ling Shao (2024)

Czechoslovak Mathematical Journal

Let G be a simple connected graph with vertex set V ( G ) = { v 1 , v 2 , , v n } and edge set E ( G ) , and let d v i be the degree of the vertex v i . Let D ( G ) be the distance matrix and let T r ( G ) be the diagonal matrix of the vertex transmissions of G . The generalized distance matrix of G is defined as D α ( G ) = α T r ( G ) + ( 1 - α ) D ( G ) , where 0 α 1 . Let λ 1 ( D α ( G ) ) λ 2 ( D α ( G ) ) ... λ n ( D α ( G ) ) be the generalized distance eigenvalues of G , and let k be an integer with 1 k n . We denote by S k ( D α ( G ) ) = λ 1 ( D α ( G ) ) + λ 2 ( D α ( G ) ) + ... + λ k ( D α ( G ) ) the sum of the k largest generalized distance eigenvalues. The generalized distance spread of a graph G is defined as D α S ( G ) = λ 1 ( D α ( G ) ) - λ n ( D α ( G ) ) . We obtain some...

Some properties of the spectral radius of a set of matrices

Adam Czornik, Piotr Jurgas (2006)

International Journal of Applied Mathematics and Computer Science

In this paper we show new formulas for the spectral radius and the spectral subradius of a set of matrices. The advantage of our results is that we express the spectral radius of any set of matrices by the spectral radius of a set of symmetric positive definite matrices. In particular, in one of our formulas the spectral radius is expressed by singular eigenvalues of matrices, whereas in the existing results it is expressed by eigenvalues.

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