Vector space/K/Inner product/Linear isometry/Introduction/Section


Let be vector spaces over , endowed with inner products, and let

be s linear mapping. Then is called an isometry if

holds for all

.

An isometry is always injective. For , we also talk about an unitary mapping. As there are also affine isometries, we talk about a linear isometry.


Let and be vector spaces over , both endowed with an inner product, and let be a

linear mapping. Then the following statements are equivalent.
  1. is an isometry.
  2. For all , we have .
  3. For all , we have .
  4. For all fulfilling , we have .

The implications , and are restrictions. . For the zero vecto r,the statement is clear; so suppose that . Then, has norm , and, because of

we have

follows from fact.


Therefore, an isometry is just a (linear) mapping that preserves distances. The set of all the vectors with norm in a Euclidean vector space is also called the sphere. Hence, an isometry is characterized by the property that it maps the sphere to the sphere.


Let and be euclidean vector spaces, and let

denote a

linear mapping. Then the following statements are equivalent.
  1. is an isometry.
  2. For every orthonormal basis , , of , , , is part of an orthonormal basis of .
  3. There exists an orthonormal basis , , of such that , , is part of an orthonormal basis of .

Proof



For every euclidean vector space , there exists a bijective isometry

where carries the

standard inner product.

Let be an orthonormal basis of , and let

be the linear mapping given by

Because of fact  (3), this is an isometry.