proof of Wielandt-Hoffman theorem
Since both A and B are normal, they can be diagonalized by unitary transformations:
A=V†CV |
where and are diagonal, and are unitary, and
denotes the conjugate transpose
. The Frobenius matrix norm is defined by the quadratic form and is invariant
under unitary transformations, hence
where . The matrix is also unitary, let its matrix elements be given by . Unitarity implies that the matrix with elements has its row and column sums equal to , in other words, it is doubly stochastic.
The diagonal elements are eigenvalues of and
are those of . Writing out the Frobenius norm
explicitly,
we get
where the minimum is taken over all doubly stochastic matrices , whose
elements are . By the Birkoff-von Neumann theorem, doubly
stochastic matrices form a closed convex (http://planetmath.org/ConvexSet) polyhedron
with permutation matrices
at the vertices. The expression
is a linear functional
on this polyhedron,
hence its minimum is achieved at one of the vertices, that is when
is a permutation matrix.
If represents the permutation , its action can be written as
. Finally, we can write the last
inequality as
which is exactly the statement of the Wielandt-Hoffman theorem.
Title | proof of Wielandt-Hoffman theorem |
---|---|
Canonical name | ProofOfWielandtHoffmanTheorem |
Date of creation | 2013-03-22 14:58:51 |
Last modified on | 2013-03-22 14:58:51 |
Owner | Andrea Ambrosio (7332) |
Last modified by | Andrea Ambrosio (7332) |
Numerical id | 6 |
Author | Andrea Ambrosio (7332) |
Entry type | Proof |
Classification | msc 15A18 |
Classification | msc 15A42 |