Applications of graphs to Boolean functions

Let f be a Boolean function on $GF(2)^n$ . The Cayley graph of f is defined to be the graph

$\Gamma_f = (GF(2)^n, E_f )$ ,

whose vertex set is $GF(2)^n$ and the set of edges is defined by

$E_f =\{ (u,v) \in GF(2)^n \times GF(2)^n \ |\ f(u+v)=1\}$ .

The adjacency matrix $A_f$ is the matrix whose entries are

$A_{i,j} = f(b(i) + b(j))$ ,

where b(k) is the binary representation of the integer k.
Note $\Gamma_f$ is a regular graph of degree wt(f), where wt denotes the Hamming weight of f when regarded as a vector of values (of length $2^n$ ).

Recall that, given a graph $\Gamma$ and its adjacency matrix A, the spectrum Spec( $\Gamma$ ) is the multi-set of eigenvalues of A.

The Walsh transform of a Boolean function f is an integer-valued function over $GF(2)^n$ that can be defined as

$W_f(u) = \sum_{x in GF(2)^n} (-1)^{f(x)+ \langle u,x\rangle}.$
A Boolean function f is bent if $|W_f(a)| = 2^{n/2}$ (this only makes sense if n is even). The Hadamard transform of a integer-valued function f is an integer-valued function over $GF(2)^n$ that can be defined as

$H_f(u) = \sum_{x in GF(2)^n} f(x)(-1)^{\langle u,x\rangle}.$
It turns out that the spectrum of $\Gamma_f$ is equal to the Hadamard transform of f when regarded as a vector of (integer) 0,1-values. (This nice fact seems to have first appeared in [2], [3].)

A graph is regular of degree r (or r-regular) if every vertex has degree r (number of edges incident to it).   We say that an r-regular graph $\Gamma$ is a strongly regular graph with parameters (v, r, d, e) (for nonnegative integers e, d) provided, for all vertices u, v the number of vertices adjacent to both u, v is equal to

          e, if u, v are adjacent,
          d, if u, v are nonadjacent.

It turns out tht f is bent iff $\Gamma_f$ is strongly regular and e = d (see [3] and [4]).

The following Sage computations illustrate these and other theorems in [1], [2], [3], [4].

Consider the Boolean function $f: GF(2)^4 \to GF(2)$ given by $f(x_0,x_1,x_2) = x_0x_1+x_2x_3$ .

sage: V = GF(2)^4
sage: f = lambda x: x[0]*x[1]+x[2]*x[3]
sage: CartesianProduct(range(16), range(16))
Cartesian product of [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], 
                     [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
sage: C = CartesianProduct(range(16), range(16))
sage: Vlist = V.list()                  
sage: E = [(x[0],x[1]) for x in C if f(Vlist[x[0]]+Vlist[x[1]])==1]
sage: len(E)
96
sage: E = Set([Set(s) for s in E])
sage: E = [tuple(s) for s in E] 
sage: Gamma = Graph(E)
sage: Gamma
Graph on 16 vertices
sage: VG = Gamma.vertices()
sage: L1 = []
sage: L2 = []
sage: for v1 in VG:
....:         for v2 in VG:
....:             N1 = Gamma.neighbors(v1)
....:         N2 = Gamma.neighbors(v2)
....:         if v1 in N2:
....:                 L1 = L1+[len([x for x in N1 if x in N2])]
....:         if not(v1 in N2) and v1!=v2:
....:                 L2 = L2+[len([x for x in N1 if x in N2])]
....: 
....: 
sage: L1; L2
[2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]
[2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
 2, 2, 2, 2]

This implies the graph is strongly regular with d=e=2.

sage: Gamma.spectrum()
[6, 2, 2, 2, 2, 2, 2, -2, -2, -2, -2, -2, -2, -2, -2, -2]
sage: [walsh_transform(f, a) for a in V]
[4, 4, 4, -4, 4, 4, 4, -4, 4, 4, 4, -4, -4, -4, -4, 4]
sage: Omega_f = [v for v in V if f(v)==1] 
sage: len(Omega_f)
6
sage: Gamma.is_bipartite()
False
sage: Gamma.is_hamiltonian()
True
sage: Gamma.is_planar()     
False
sage: Gamma.is_regular()
True
sage: Gamma.is_eulerian()
True
sage: Gamma.is_connected()
True
sage: Gamma.is_triangle_free()
False
sage: Gamma.diameter()
2
sage: Gamma.degree_sequence()
[6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6]
sage: show(Gamma)
# bent-fcns-cayley-graphs1.png

Here is the picture of the graph:

sage: H = matrix(QQ, 16, 16, [(-1)^(Vlist[x[0]]).dot_product(Vlist[x[1]]) for x in C])
sage: H
[ 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  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  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  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  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  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  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  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]
[ 1 -1 -1  1 -1  1  1 -1 -1  1  1 -1  1 -1 -1  1]
sage: flist = vector(QQ, [int(f(v)) for v in V])
sage: H*flist  
(6, -2, -2, 2, -2, -2, -2, 2, -2, -2, -2, 2, 2, 2, 2, -2)
sage: A = matrix(QQ, 16, 16, [f(Vlist[x[0]]+Vlist[x[1]]) for x in C])
sage: A.eigenvalues()
[6, 2, 2, 2, 2, 2, 2, -2, -2, -2, -2, -2, -2, -2, -2, -2]

Here is another example: $f: GF(2)^3 \to GF(2)$ given by $f(x_0,x_1,x_2) = x_0x_1+x_2$ .

sage: V = GF(2)^3
sage: f = lambda x: x[0]*x[1]+x[2]
sage: Omega_f = [v for v in V if f(v)==1] 
sage: len(Omega_f)
4
sage: C = CartesianProduct(range(8), range(8))
sage: Vlist = V.list()    
sage: E = [(x[0],x[1]) for x in C if f(Vlist[x[0]]+Vlist[x[1]])==1]
sage: E = Set([Set(s) for s in E])
sage: E = [tuple(s) for s in E] 
sage: Gamma = Graph(E)
sage: Gamma
Graph on 8 vertices
sage: 
sage: VG = Gamma.vertices()
sage: L1 = []
sage: L2 = []
sage: for v1 in VG:
....:         for v2 in VG:
....:             N1 = Gamma.neighbors(v1)
....:         N2 = Gamma.neighbors(v2)
....:         if v1 in N2:
....:                 L1 = L1+[len([x for x in N1 if x in N2])]
....:         if not(v1 in N2) and v1!=v2:
....:                 L2 = L2+[len([x for x in N1 if x in N2])]
....: 
sage: L1; L2
[2, 0, 2, 2, 2, 2, 0, 2, 2, 2, 0, 2, 2, 2, 2, 0, 0, 2, 2, 2, 2, 0, 2, 2, 2, 0, 2, 2, 2, 2, 0, 2]
[2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]

This implies that the graph is not strongly regular, therefore f is not bent.

sage: Gamma.spectrum()
[4, 2, 0, 0, 0, -2, -2, -2]
sage: 
sage: Gamma.is_bipartite()
False
sage: Gamma.is_hamiltonian()
True
sage: Gamma.is_planar()     
False
sage: Gamma.is_regular()
True
sage: Gamma.is_eulerian()
True
sage: Gamma.is_connected()
True
sage: Gamma.is_triangle_free()
False
sage: Gamma.diameter()
2
sage: Gamma.degree_sequence()
[4, 4, 4, 4, 4, 4, 4, 4]
sage: H = matrix(QQ, 8, 8, [(-1)^(Vlist[x[0]]).dot_product(Vlist[x[1]]) for x in C])
sage: H
[ 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 -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 -1  1  1 -1]
sage: flist = vector(QQ, [int(f(v)) for v in V])
sage: H*flist  
(4, 0, 0, 0, -2, -2, -2, 2)
sage: Gamma.spectrum()
[4, 2, 0, 0, 0, -2, -2, -2]
sage: A = matrix(QQ, 8, 8, [f(Vlist[x[0]]+Vlist[x[1]]) for x in C])
sage: A.eigenvalues()
[4, 2, 0, 0, 0, -2, -2, -2]

sage: show(Gamma)
# bent-fcns-cayley-graphs2.png

Here is the picture:

REFERENCES:
[1] Pantelimon Stanica, Graph eigenvalues and Walsh spectrum of Boolean functions, INTEGERS 7(2) (2007), #A32.

[2] Anna Bernasconi, Mathematical techniques for the analysis of Boolean functions, Ph. D. dissertation TD-2/98, Universit di Pisa-Udine, 1998.

[3] Anna Bernasconi and Bruno Codenotti, Spectral Analysis of Boolean Functions as a Graph Eigenvalue Problem, IEEE TRANSACTIONS ON COMPUTERS, VOL. 48, NO. 3, MARCH 1999.

[4] A. Bernasconi, B. Codenotti, J.M. VanderKam. A Characterization of Bent Functions in terms of Strongly Regular Graphs, IEEE Transactions on Computers, 50:9 (2001), 984-985.

[5] Michel Mitton, Minimal polynomial of Cayley graph adjacency matrix for Boolean functions, preprint, 2007.

[6] ——, On the Walsh-Fourier analysis of Boolean functions, preprint, 2006.

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Applications of graphs to Boolean functions

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