In an earlier post I discussed bent functions . In this post, I’d like to give some more examples, based on a recent paper with Caroline Melles, Charles Celerier, David Phillips, and Steven Walsh, based on computations using Sage/pythpn programs I wrote with Charles Celerier.
We start with any function . The Cayley graph of
is defined to be the edge-weighted digraph
whose vertex set is and the set of edges is defined by
where the edge has weight
. However, if
is even then we can (and do) regard
as an edge-weighted (undirected) graph.
We assume, unless stated otherwise, that is even.
For each , define
to be the set of all neighbors of
in
,
to be the set of all neighbors
of
in
for which the edge
has weight
(for each
),
to be the set of all non-neighbors
of
in
(i.e., we have
),
- the support of
is
Let be a connected edge-weighted graph which is regular as a simple (unweighted) graph. The graph
is called strongly regular with parameters
,
,
,
, denoted
, if it consists of
vertices such that, for each
where ,
,
are as above. Here,
is the set of weights, including
(recall an “edge” has weight
if the vertices are not neighbors).
This example is intended to illustrate the bent function listed in the table below
Consider the finite field
The set of non-zero quadratic residues is given by
Let be the graph whose vertices are
and whose edges
are those pairs for which
.
The graph looks like the Cayley graph for in the Figure below
except
This is a strongly regular graph with parameters .
The axioms of an edge-weighted strongly regular graph can be directly verified using this table.
Let be a finite set and let
denote binary relations on
(subsets of
). The dual of a relation
is the set
Assume . We say
is an
-class association scheme on
if the following properties hold.
- We have a disjoint union
withfor all $i\not= j$.
- For each
there is a
such that
(and if
for all
then we say the association scheme is symmetric).
- For all
and all
, define
For each, and for all
, the integer
is a constant, denoted
.
These constants are called the intersection numbers of the association scheme.
For this example of , we compute the adjacency matrix associated to the members
and
of the association scheme
, where
,
and .
Consider the following Sage computation:
sage: attach "/home/wdj/sagefiles/hadamard_transform2b.sage" sage: FF = GF(3) sage: V = FF^2 sage: Vlist = V.list() sage: flist = [0,2,2,0,0,1,0,1,0] sage: f = lambda x: GF(3)(flist[Vlist.index(x)]) sage: F = matrix(ZZ, [[f(x-y) for x in V] for y in V]) sage: F ## weighted adjacency matrix [0 2 2 0 0 1 0 1 0] [2 0 2 1 0 0 0 0 1] [2 2 0 0 1 0 1 0 0] [0 1 0 0 2 2 0 0 1] [0 0 1 2 0 2 1 0 0] [1 0 0 2 2 0 0 1 0] [0 0 1 0 1 0 0 2 2] [1 0 0 0 0 1 2 0 2] [0 1 0 1 0 0 2 2 0] sage: eval1 = lambda x: int((x==1)) sage: eval2 = lambda x: int((x==2)) sage: F1 = matrix(ZZ, [[eval1(f(x-y)) for x in V] for y in V]) sage: F1 [0 0 0 0 0 1 0 1 0] [0 0 0 1 0 0 0 0 1] [0 0 0 0 1 0 1 0 0] [0 1 0 0 0 0 0 0 1] [0 0 1 0 0 0 1 0 0] [1 0 0 0 0 0 0 1 0] [0 0 1 0 1 0 0 0 0] [1 0 0 0 0 1 0 0 0] [0 1 0 1 0 0 0 0 0] sage: F2 = matrix(ZZ, [[eval2(f(x-y)) for x in V] for y in V]) sage: F2 [0 1 1 0 0 0 0 0 0] [1 0 1 0 0 0 0 0 0] [1 1 0 0 0 0 0 0 0] [0 0 0 0 1 1 0 0 0] [0 0 0 1 0 1 0 0 0] [0 0 0 1 1 0 0 0 0] [0 0 0 0 0 0 0 1 1] [0 0 0 0 0 0 1 0 1] [0 0 0 0 0 0 1 1 0] sage: F1*F2-F2*F1 == 0 True sage: delta = lambda x: int((x[0]==x[1])) sage: F3 = matrix(ZZ, [[(eval0(f(x-y))+delta([x,y]))%2 for x in V] for y in V]) sage: F3 [0 0 0 1 1 0 1 0 1] [0 0 0 0 1 1 1 1 0] [0 0 0 1 0 1 0 1 1] [1 0 1 0 0 0 1 1 0] [1 1 0 0 0 0 0 1 1] [0 1 1 0 0 0 1 0 1] [1 1 0 1 0 1 0 0 0] [0 1 1 1 1 0 0 0 0] [1 0 1 0 1 1 0 0 0] sage: F3*F2-F2*F3==0 True sage: F3*F1-F1*F3==0 True sage: F0 = matrix(ZZ, [[delta([x,y]) for x in V] for y in V]) sage: F0 [1 0 0 0 0 0 0 0 0] [0 1 0 0 0 0 0 0 0] [0 0 1 0 0 0 0 0 0] [0 0 0 1 0 0 0 0 0] [0 0 0 0 1 0 0 0 0] [0 0 0 0 0 1 0 0 0] [0 0 0 0 0 0 1 0 0] [0 0 0 0 0 0 0 1 0] [0 0 0 0 0 0 0 0 1] sage: F1*F3 == 2*F2 + F3 True
The Sage computation above tells us that the adjacency matrix of is
the adjacency matrix of is
and the adjacency matrix of is
Of course, the adjacency matrix of is the identity matrix. In the above computation, Sage has also verified that they commute and satisfy
in the adjacency ring of the association scheme.
Conjecture:
Letbe a bent function, with
. If the level curves of
give rise to a weighted partial difference set then
is weakly regular, and the corresponding (unweighted) partial difference set is of (positive or negative) Latin square type.
For more details, see the paper [CJMPW] with Caroline Melles, Charles Celerier, David Phillips, and Steven Walsh.