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248 Communicating without errors<br />
⎛<br />
A =<br />
⎜<br />
⎝<br />
0 1 0 0 1<br />
1 0 1 0 0<br />
0 1 0 1 0<br />
0 0 1 0 1<br />
1 0 0 1 0<br />
⎞<br />
⎟<br />
⎠<br />
The adjacency matrix for the 5-cycle C 5<br />
Let us carry our discussion a little further. We see from (8) that the larger σ T<br />
is for a representation of G, the better a bound for Θ(G) we will get. Here<br />
is a method that gives us an orthonormal representation for any graph G.<br />
To G = (V, E) we associate the adjacency matrix A = (a ij ), which is<br />
defined as follows: Let V = {v 1 , . . .,v m }, then we set<br />
{ 1 if vi v<br />
a ij :=<br />
j ∈ E<br />
0 otherwise.<br />
A is a real symmetric matrix with 0’s in the main diagonal.<br />
Now we need two facts from linear algebra. First, as a symmetric matrix,<br />
A has m real eigenvalues λ 1 ≥ λ 2 ≥ . . . ≥ λ m (some of which may<br />
be equal), and the sum of the eigenvalues equals the sum of the diagonal<br />
entries of A, that is, 0. Hence the smallest eigenvalue must be negative<br />
(except in the trivial case when G has no edges). Let p = |λ m | = −λ m be<br />
the absolute value of the smallest eigenvalue, and consider the matrix<br />
M := I + 1 p A,<br />
where I denotes the (m × m)-identity matrix. This M has the eigenvalues<br />
1+ λ1 λ2<br />
p<br />
≥ 1+<br />
p ≥ . . . ≥ 1+ λm p<br />
= 0. Now we quote the second result (the<br />
principal axis theorem of linear algebra): If M = (m ij ) is a real symmetric<br />
matrix with all eigenvalues ≥ 0, then there are vectors v (1) , . . .,v (m) ∈ R s<br />
for s = rank(M), such that<br />
m ij = 〈v (i) , v (j) 〉<br />
In particular, for M = I + 1 pA we obtain<br />
(1 ≤ i, j ≤ m).<br />
〈v (i) , v (i) 〉 = m ii = 1 for all i<br />
and<br />
〈v (i) , v (j) 〉 = 1 p a ij for i ≠ j.<br />
Since a ij = 0 whenever v i v j ∉ E, we see that the vectors v (1) , . . .,v (m)<br />
form indeed an orthonormal representation of G.<br />
Let us, finally, apply this construction to the m-cycles C m for odd m ≥ 5.<br />
Here one easily computes p = |λ min | = 2 cos π m<br />
(see the box). Every<br />
row of the adjacency matrix contains two 1’s, implying that every row of<br />
the matrix M sums to 1 + 2 p . For the representation {v(1) , . . . ,v (m) } this<br />
means<br />
〈v (i) , v (1) + . . . + v (m) 〉 = 1 + 2 p = 1 + 1<br />
cos π m<br />
and hence<br />
〈v (i) , u〉 = 1 m (1 + (cos π m )−1 ) = σ<br />
for all i. We can therefore apply our main result (8) and conclude<br />
Θ(C m ) ≤<br />
m<br />
1 + (cos π m )−1 (for m ≥ 5 odd). (9)