Strongly regular graphs #
Main definitions #
G.IsSRGWith n k ℓ μ
(seeSimpleGraph.IsSRGWith
) is a structure for aSimpleGraph
satisfying the following conditions:- The cardinality of the vertex set is
n
G
is a regular graph with degreek
- The number of common neighbors between any two adjacent vertices in
G
isℓ
- The number of common neighbors between any two nonadjacent vertices in
G
isμ
- The cardinality of the vertex set is
Main theorems #
IsSRGWith.compl
: the complement of a strongly regular graph is strongly regular.IsSRGWith.param_eq
:k * (k - ℓ - 1) = (n - k - 1) * μ
when0 < n
.IsSRGWith.matrix_eq
: letA
andC
beG
's andGᶜ
's adjacency matrices respectively andI
be the identity matrix, thenA ^ 2 = k • I + ℓ • A + μ • C
.
A graph is strongly regular with parameters n k ℓ μ
if
- its vertex set has cardinality
n
- it is regular with degree
k
- every pair of adjacent vertices has
ℓ
common neighbors - every pair of nonadjacent vertices has
μ
common neighbors
- card : Fintype.card V = n
- regular : SimpleGraph.IsRegularOfDegree G k
- of_adj : ∀ (v w : V), G.Adj v w → Fintype.card ↑(SimpleGraph.commonNeighbors G v w) = ℓ
- of_not_adj : Pairwise fun (v w : V) => ¬G.Adj v w → Fintype.card ↑(SimpleGraph.commonNeighbors G v w) = μ
Instances For
Empty graphs are strongly regular. Note that ℓ
can take any value
for empty graphs, since there are no pairs of adjacent vertices.
Complete graphs are strongly regular. Note that μ
can take any value
for complete graphs, since there are no distinct pairs of non-adjacent vertices.
Assuming G
is strongly regular, 2*(k + 1) - m
in G
is the number of vertices that are
adjacent to either v
or w
when ¬G.Adj v w
. So it's the cardinality of
G.neighborSet v ∪ G.neighborSet w
.
The complement of a strongly regular graph is strongly regular.
The parameters of a strongly regular graph with at least one vertex satisfy
k * (k - ℓ - 1) = (n - k - 1) * μ
.
Let A
and C
be the adjacency matrices of a strongly regular graph with parameters n k ℓ μ
and its complement respectively and I
be the identity matrix,
then A ^ 2 = k • I + ℓ • A + μ • C
. C
is equivalent to the expression J - I - A
more often found in the literature, where J
is the all-ones matrix.