Processing math: 100%

Identifier
Values
[[1,0],[1]] => [[1]] => ([],1) => ([],1) => 1
[[2,0],[2]] => [[1,1]] => ([],1) => ([],1) => 1
[[1,1],[1]] => [[1],[2]] => ([],1) => ([],1) => 1
[[1,0,0],[1,0],[1]] => [[1]] => ([],1) => ([],1) => 1
[[3,0],[3]] => [[1,1,1]] => ([],1) => ([],1) => 1
[[2,1],[2]] => [[1,1],[2]] => ([],1) => ([],1) => 1
[[2,0,0],[2,0],[2]] => [[1,1]] => ([],1) => ([],1) => 1
[[1,1,0],[1,1],[1]] => [[1],[2]] => ([],1) => ([],1) => 1
[[1,0,0,0],[1,0,0],[1,0],[1]] => [[1]] => ([],1) => ([],1) => 1
[[4,0],[4]] => [[1,1,1,1]] => ([],1) => ([],1) => 1
[[3,1],[3]] => [[1,1,1],[2]] => ([],1) => ([],1) => 1
[[2,2],[2]] => [[1,1],[2,2]] => ([],1) => ([],1) => 1
[[3,0,0],[3,0],[3]] => [[1,1,1]] => ([],1) => ([],1) => 1
[[2,1,0],[2,1],[2]] => [[1,1],[2]] => ([],1) => ([],1) => 1
[[1,1,1],[1,1],[1]] => [[1],[2],[3]] => ([],1) => ([],1) => 1
[[2,0,0,0],[2,0,0],[2,0],[2]] => [[1,1]] => ([],1) => ([],1) => 1
[[1,1,0,0],[1,1,0],[1,1],[1]] => [[1],[2]] => ([],1) => ([],1) => 1
[[1,0,0,0,0],[1,0,0,0],[1,0,0],[1,0],[1]] => [[1]] => ([],1) => ([],1) => 1
[[5,0],[5]] => [[1,1,1,1,1]] => ([],1) => ([],1) => 1
[[4,1],[4]] => [[1,1,1,1],[2]] => ([],1) => ([],1) => 1
[[3,2],[3]] => [[1,1,1],[2,2]] => ([],1) => ([],1) => 1
[[4,0,0],[4,0],[4]] => [[1,1,1,1]] => ([],1) => ([],1) => 1
[[3,1,0],[3,1],[3]] => [[1,1,1],[2]] => ([],1) => ([],1) => 1
[[2,2,0],[2,2],[2]] => [[1,1],[2,2]] => ([],1) => ([],1) => 1
[[2,1,1],[2,1],[2]] => [[1,1],[2],[3]] => ([],1) => ([],1) => 1
[[3,0,0,0],[3,0,0],[3,0],[3]] => [[1,1,1]] => ([],1) => ([],1) => 1
[[2,1,0,0],[2,1,0],[2,1],[2]] => [[1,1],[2]] => ([],1) => ([],1) => 1
[[1,1,1,0],[1,1,1],[1,1],[1]] => [[1],[2],[3]] => ([],1) => ([],1) => 1
[[2,0,0,0,0],[2,0,0,0],[2,0,0],[2,0],[2]] => [[1,1]] => ([],1) => ([],1) => 1
[[1,1,0,0,0],[1,1,0,0],[1,1,0],[1,1],[1]] => [[1],[2]] => ([],1) => ([],1) => 1
[[1,0,0,0,0,0],[1,0,0,0,0],[1,0,0,0],[1,0,0],[1,0],[1]] => [[1]] => ([],1) => ([],1) => 1
[[5,1],[5]] => [[1,1,1,1,1],[2]] => ([],1) => ([],1) => 1
[[4,2],[4]] => [[1,1,1,1],[2,2]] => ([],1) => ([],1) => 1
[[3,3],[3]] => [[1,1,1],[2,2,2]] => ([],1) => ([],1) => 1
[[5,0,0],[5,0],[5]] => [[1,1,1,1,1]] => ([],1) => ([],1) => 1
[[4,1,0],[4,1],[4]] => [[1,1,1,1],[2]] => ([],1) => ([],1) => 1
[[3,2,0],[3,2],[3]] => [[1,1,1],[2,2]] => ([],1) => ([],1) => 1
[[3,1,1],[3,1],[3]] => [[1,1,1],[2],[3]] => ([],1) => ([],1) => 1
[[2,2,1],[2,2],[2]] => [[1,1],[2,2],[3]] => ([],1) => ([],1) => 1
[[4,0,0,0],[4,0,0],[4,0],[4]] => [[1,1,1,1]] => ([],1) => ([],1) => 1
[[3,1,0,0],[3,1,0],[3,1],[3]] => [[1,1,1],[2]] => ([],1) => ([],1) => 1
[[2,2,0,0],[2,2,0],[2,2],[2]] => [[1,1],[2,2]] => ([],1) => ([],1) => 1
[[2,1,1,0],[2,1,1],[2,1],[2]] => [[1,1],[2],[3]] => ([],1) => ([],1) => 1
[[1,1,1,1],[1,1,1],[1,1],[1]] => [[1],[2],[3],[4]] => ([],1) => ([],1) => 1
[[3,0,0,0,0],[3,0,0,0],[3,0,0],[3,0],[3]] => [[1,1,1]] => ([],1) => ([],1) => 1
[[2,1,0,0,0],[2,1,0,0],[2,1,0],[2,1],[2]] => [[1,1],[2]] => ([],1) => ([],1) => 1
[[1,1,1,0,0],[1,1,1,0],[1,1,1],[1,1],[1]] => [[1],[2],[3]] => ([],1) => ([],1) => 1
[[2,0,0,0,0,0],[2,0,0,0,0],[2,0,0,0],[2,0,0],[2,0],[2]] => [[1,1]] => ([],1) => ([],1) => 1
[[1,1,0,0,0,0],[1,1,0,0,0],[1,1,0,0],[1,1,0],[1,1],[1]] => [[1],[2]] => ([],1) => ([],1) => 1
[[1,0,0,0,0,0,0],[1,0,0,0,0,0],[1,0,0,0,0],[1,0,0,0],[1,0,0],[1,0],[1]] => [[1]] => ([],1) => ([],1) => 1
[[6,1],[6]] => [[1,1,1,1,1,1],[2]] => ([],1) => ([],1) => 1
[[5,2],[5]] => [[1,1,1,1,1],[2,2]] => ([],1) => ([],1) => 1
[[4,3],[4]] => [[1,1,1,1],[2,2,2]] => ([],1) => ([],1) => 1
[[5,1,0],[5,1],[5]] => [[1,1,1,1,1],[2]] => ([],1) => ([],1) => 1
[[4,2,0],[4,2],[4]] => [[1,1,1,1],[2,2]] => ([],1) => ([],1) => 1
[[4,1,1],[4,1],[4]] => [[1,1,1,1],[2],[3]] => ([],1) => ([],1) => 1
[[3,3,0],[3,3],[3]] => [[1,1,1],[2,2,2]] => ([],1) => ([],1) => 1
[[3,2,1],[3,2],[3]] => [[1,1,1],[2,2],[3]] => ([],1) => ([],1) => 1
[[2,2,2],[2,2],[2]] => [[1,1],[2,2],[3,3]] => ([],1) => ([],1) => 1
[[5,0,0,0],[5,0,0],[5,0],[5]] => [[1,1,1,1,1]] => ([],1) => ([],1) => 1
[[4,1,0,0],[4,1,0],[4,1],[4]] => [[1,1,1,1],[2]] => ([],1) => ([],1) => 1
[[3,2,0,0],[3,2,0],[3,2],[3]] => [[1,1,1],[2,2]] => ([],1) => ([],1) => 1
[[3,1,1,0],[3,1,1],[3,1],[3]] => [[1,1,1],[2],[3]] => ([],1) => ([],1) => 1
[[2,2,1,0],[2,2,1],[2,2],[2]] => [[1,1],[2,2],[3]] => ([],1) => ([],1) => 1
[[2,1,1,1],[2,1,1],[2,1],[2]] => [[1,1],[2],[3],[4]] => ([],1) => ([],1) => 1
[[4,0,0,0,0],[4,0,0,0],[4,0,0],[4,0],[4]] => [[1,1,1,1]] => ([],1) => ([],1) => 1
[[3,1,0,0,0],[3,1,0,0],[3,1,0],[3,1],[3]] => [[1,1,1],[2]] => ([],1) => ([],1) => 1
[[2,2,0,0,0],[2,2,0,0],[2,2,0],[2,2],[2]] => [[1,1],[2,2]] => ([],1) => ([],1) => 1
[[2,1,1,0,0],[2,1,1,0],[2,1,1],[2,1],[2]] => [[1,1],[2],[3]] => ([],1) => ([],1) => 1
[[1,1,1,1,0],[1,1,1,1],[1,1,1],[1,1],[1]] => [[1],[2],[3],[4]] => ([],1) => ([],1) => 1
[[3,0,0,0,0,0],[3,0,0,0,0],[3,0,0,0],[3,0,0],[3,0],[3]] => [[1,1,1]] => ([],1) => ([],1) => 1
[[2,1,0,0,0,0],[2,1,0,0,0],[2,1,0,0],[2,1,0],[2,1],[2]] => [[1,1],[2]] => ([],1) => ([],1) => 1
[[1,1,1,0,0,0],[1,1,1,0,0],[1,1,1,0],[1,1,1],[1,1],[1]] => [[1],[2],[3]] => ([],1) => ([],1) => 1
[[2,0,0,0,0,0,0],[2,0,0,0,0,0],[2,0,0,0,0],[2,0,0,0],[2,0,0],[2,0],[2]] => [[1,1]] => ([],1) => ([],1) => 1
[[1,1,0,0,0,0,0],[1,1,0,0,0,0],[1,1,0,0,0],[1,1,0,0],[1,1,0],[1,1],[1]] => [[1],[2]] => ([],1) => ([],1) => 1
[[1,0,0,0,0,0,0,0],[1,0,0,0,0,0,0],[1,0,0,0,0,0],[1,0,0,0,0],[1,0,0,0],[1,0,0],[1,0],[1]] => [[1]] => ([],1) => ([],1) => 1
[[1,1,1,1,1],[1,1,1,1],[1,1,1],[1,1],[1]] => [[1],[2],[3],[4],[5]] => ([],1) => ([],1) => 1
[[1]] => [[1]] => ([],1) => ([],1) => 1
[[1,1,1,1,1,1],[1,1,1,1,1],[1,1,1,1],[1,1,1],[1,1],[1]] => [[1],[2],[3],[4],[5],[6]] => ([],1) => ([],1) => 1
[[2]] => [[1,1]] => ([],1) => ([],1) => 1
[[3]] => [[1,1,1]] => ([],1) => ([],1) => 1
[[4]] => [[1,1,1,1]] => ([],1) => ([],1) => 1
[[5]] => [[1,1,1,1,1]] => ([],1) => ([],1) => 1
[[4,3,2,1],[4,3,2],[4,3],[4]] => [[1,1,1,1],[2,2,2],[3,3],[4]] => ([],1) => ([],1) => 1
search for individual values
searching the database for the individual values of this statistic
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
(4121141221411214).
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 n1, n2 and n3 have been characterised, see [1].
Map
incomparability graph
Description
The incomparability graph of a poset.
Map
to semistandard tableau
Description
Return the Gelfand-Tsetlin pattern as a semistandard Young tableau.
Let G be a Gelfand-Tsetlin pattern and let λ(k) be its (nk+1)-st row. The defining inequalities of a Gelfand-Tsetlin pattern imply, regarding each row as a partition,
λ(0)λ(1)λ(n),
where λ(0) is the empty partition.
Each skew shape λ(k)/λ(k1) is moreover a horizontal strip.
We now define a semistandard tableau T(G) by inserting k into the cells of the skew shape λ(k)/λ(k1), for k=1,,n.
Map
subcrystal
Description
The underlying poset of the subcrystal obtained by applying the raising operators to a semistandard tableau.