Isometry

From Wikipedia, the free encyclopedia

For the mechanical engineering and architecture usage, see isometric projection. For isometry in differential geometry, seeisometry (Riemannian geometry).

In mathematics, an isometry is a distance-preserving map between metric spaces. Geometric figures which can be related by an isometry are called congruent.

Isometries are often used in constructions where one space is embedded in another space. For instance, the completion of a metric space M involves an isometry from M into M’, a quotient set of the space of Cauchy sequences on M. The original space M is thus isometrically isomorphic to a subspace of a complete metric space, and it is usually identified with this subspace. Other embedding constructions show that every metric space is isometrically isomorphic to a closed subset of some normed vector space and that every complete metric space is isometrically isomorphic to a closed subset of some Banach space.

An isometric surjective linear operator on a Hilbert space is called a unitary operator.

http://en.wikipedia.org/wiki/Isometry

Unitary matrix

From Wikipedia, the free encyclopedia

In mathematics, a unitary matrix is an $ntimes n$ complex matrix U satisfying the condition

$U^{dagger} U = UU^{dagger} = I_n,$

where I_n is the identity matrix in n dimensions and $U^{dagger}$ is the conjugate transpose (also called the Hermitian adjoint) of U. Note this condition says that a matrix U is unitary if and only if it has an inverse which is equal to its conjugate transpose $U^{dagger} ,$

$U^{-1} = U^{dagger} ,;$

A unitary matrix in which all entries are real is an orthogonal matrix. Just as an orthogonal matrix G preserves the (real) inner productof two real vectors,

$langle Gx, Gy rangle = langle x, y rangle$

so also a unitary matrix U satisfies

$langle Ux, Uy rangle = langle x, y rangle$

for all complex vectors x and y, where $langlecdot,cdotrangle$ stands now for the standard inner product on $mathbb{C}^n$ .

If $U ,$ is an n by n matrix then the following are all equivalent conditions:

$U ,$ is unitary
$U^{dagger} ,$ is unitary
the columns of $U ,$ form an orthonormal basis of $mathbb{C}^n$ with respect to this inner product
the rows of $U ,$ form an orthonormal basis of $mathbb{C}^n$ with respect to this inner product
$U ,$ is an isometry with respect to the norm from this inner product
$U ,$ is a normal matrix with eigenvalues lying on the unit circle.

http://en.wikipedia.org/wiki/Unitary_matrix