Identifier
Values
([(0,1)],2) => ([],1) => ([],1) => ([],1) => 1
([(1,2)],3) => ([],1) => ([],1) => ([],1) => 1
([(2,3)],4) => ([],1) => ([],1) => ([],1) => 1
([(0,3),(1,2)],4) => ([],2) => ([],1) => ([],1) => 1
([(3,4)],5) => ([],1) => ([],1) => ([],1) => 1
([(1,4),(2,3)],5) => ([],2) => ([],1) => ([],1) => 1
([(0,3),(0,4),(1,2),(1,4),(2,3)],5) => ([(0,3),(0,4),(1,2),(1,4),(2,3)],5) => ([(0,3),(0,4),(1,2),(1,4),(2,3)],5) => ([(0,3),(0,4),(1,2),(1,4),(2,3)],5) => 2
([(4,5)],6) => ([],1) => ([],1) => ([],1) => 1
([(2,5),(3,4)],6) => ([],2) => ([],1) => ([],1) => 1
([(0,5),(1,4),(2,3)],6) => ([],3) => ([],1) => ([],1) => 1
([(1,4),(1,5),(2,3),(2,5),(3,4)],6) => ([(0,3),(0,4),(1,2),(1,4),(2,3)],5) => ([(0,3),(0,4),(1,2),(1,4),(2,3)],5) => ([(0,3),(0,4),(1,2),(1,4),(2,3)],5) => 2
([(5,6)],7) => ([],1) => ([],1) => ([],1) => 1
([(3,6),(4,5)],7) => ([],2) => ([],1) => ([],1) => 1
([(1,6),(2,5),(3,4)],7) => ([],3) => ([],1) => ([],1) => 1
([(2,5),(2,6),(3,4),(3,6),(4,5)],7) => ([(0,3),(0,4),(1,2),(1,4),(2,3)],5) => ([(0,3),(0,4),(1,2),(1,4),(2,3)],5) => ([(0,3),(0,4),(1,2),(1,4),(2,3)],5) => 2
([(0,1),(2,5),(2,6),(3,4),(3,6),(4,5)],7) => ([(1,4),(1,5),(2,3),(2,5),(3,4)],6) => ([(0,3),(0,4),(1,2),(1,4),(2,3)],5) => ([(0,3),(0,4),(1,2),(1,4),(2,3)],5) => 2
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Description
The multiplicity of the largest distance Laplacian eigenvalue in a connected graph.
The distance Laplacian of a graph is the (symmetric) matrix with row and column sums 0, which has the negative distances between two vertices as its off-diagonal entries. This statistic is the largest multiplicity of an eigenvalue.
For example, the cycle on four vertices has distance Laplacian
(4−1−2−1−14−1−2−2−14−1−1−2−14).
Its eigenvalues are 0,4,4,6, so the statistic is 1.
The path on four vertices has eigenvalues 0,4.7…,6,9.2… and therefore also statistic 1.
The graphs with statistic n−1, n−2 and n−3 have been characterised, see [1].
The distance Laplacian of a graph is the (symmetric) matrix with row and column sums 0, which has the negative distances between two vertices as its off-diagonal entries. This statistic is the largest multiplicity of an eigenvalue.
For example, the cycle on four vertices has distance Laplacian
(4−1−2−1−14−1−2−2−14−1−1−2−14).
Its eigenvalues are 0,4,4,6, so the statistic is 1.
The path on four vertices has eigenvalues 0,4.7…,6,9.2… and therefore also statistic 1.
The graphs with statistic n−1, n−2 and n−3 have been characterised, see [1].
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complement
Description
The complement of a graph.
The complement of a graph has the same vertices, but exactly those edges that are not in the original graph.
The complement of a graph has the same vertices, but exactly those edges that are not in the original graph.
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line graph
Description
The line graph of a graph.
Let G be a graph with edge set E. Then its line graph is the graph with vertex set E, such that two vertices e and f are adjacent if and only if they are incident to a common vertex in G.
Let G be a graph with edge set E. Then its line graph is the graph with vertex set E, such that two vertices e and f are adjacent if and only if they are incident to a common vertex in G.
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core
Description
The core of a graph.
The core of a graph G is the smallest graph C such that there is a homomorphism from G to C and a homomorphism from C to G.
Note that the core of a graph is not necessarily connected, see [2].
The core of a graph G is the smallest graph C such that there is a homomorphism from G to C and a homomorphism from C to G.
Note that the core of a graph is not necessarily connected, see [2].
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