I need ANY combination of 8 variables which satisfy:
a+b+c+d+e+f+g+h=0
a^2+b^2+c^2+d^2+e^2+f^2+g^2+h^2=1
a*b+b*c+c*d+d*e+e*f+f*g+g*h+a*h>2/3
Ideally these would be numbers having simple closed forms...
If I exchange third restriction with
a*b+b*c+c*d+d*e+e*f+f*g+g*h+a*h=2/3
I get a solution a=b=c=6^(-0.5); e=f=g=-6^(-0.5); d=h=0;
Answer
This is a special kind of problem which succumbs to a standard approach.
Analysis
The question can be solved by maximizing xAx′ and checking that this maximum exceeds 2/3. The restrictions are (1) that x=(a,b,…,h) must have unit square length and (2) be orthogonal to e1=(1,1,…,1), where A is the matrix
(0100000000100000000100000000100000000100000000100000000110000000)
Solution
Because A is obviously a rotation matrix (it represents a cyclic permutation of the eight basis vectors), e1 (by virtue of its constant coefficients) must be an eigenvector. Seven other complex eigenvectors can be found orthogonal to e1. Their eigenvalues fall into three groups of complex conjugates, representing rotations by primitive multiples of 2π/8, and one real eigenvalue of −1, representing a rotation by π. We seek the smallest rotation among these rotations, because that corresponds to the largest cosine of the angle, which geometrically is what xAx′ is computing.
The eigensystem can be obtained and displayed as
MatrixForm /@ ({e, ev} = Eigensystem[a = RotateRight[#, 1] & /@ IdentityMatrix[8]] // Simplify)
The cosines are the real parts of the eigenvalues e
:
Re[e]
{−1√2,−1√2,1√2,1√2,−1,0,0,1}
The two largest real parts, 1/√2≈0.7071>2/3, occur in the third and fourth places. The real parts of either the third or fourth normalized eigenvectors therefore afford values of x where the desired maximum is attained:
x = Normalize @ (Re /@ ev[[3]])
{12√2,0,−12√2,−12,−12√2,0,12√2,12}
If any of this seems too abstract, let's check all the requirements:
Confirm x is orthogonal to e1:
x .ConstantArray[1, 8]
0
Confirm x has unit squared length:
x . x
1
Compute xAx′:
x . a . x
1√2
Comments
Post a Comment