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Vector space/Dual space/Linear subspace/Introduction/Section

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For a linear subspace in a -vector space, we call

the orthogonal space

of .

These orthogonal spaces are again linear subspaces, see exercise. Whether a linear form belongs to can be checked on a generating system of , see exercise.


We consider the linear subspace

The orthogonal space of consists of all linear forms

with and . Because a linear form is described by a row matrix with respect to the standard basis, we are dealing with the solution set of the linear system

The solution space is


Let be a finite-dimensional -vector space with a basis , , and the corresponding dual basis , . Let

for a subset . Then


Let be a -vector space and be a linear subspace of the dual space of . Then

is called the orthogonal space

of .


Let a homogeneous linear system

over a field be given. We consider the -th equation as a kernel condition for the linear form

Let

denote the linear subspace of the dual space generated by these linear forms. Then is the solution space of this linear system.

In general, we have the relation

In particular,


Let be a -vector space with dual space

. Then the following statements hold.
  1. For linear subspaces , we have
  2. For linear subspaces , we have
  3. Let be finite-dimensional. Then

    and

  4. Let be finite-dimensional. Then

    and

(1) and (2) are clear. (3). The inclusion

is also clear. Let , . Then we can choose a basis of and extend it to a basis of . The linear form vanishes on , therefore, it belongs to . Because of

we have .

(4). Let be a basis of , and let

denote the mapping where these linear forms are the components. Here, we have

Assume that the mapping is not surjective. Then is a strict linear subspace of and its dimension is at most . Let be a -dimensional linear subspace with

Due to fact, there is a linear form

whose kernel is exactly . Write . Then

contradicting the linear independence of the . Moreover, is surjective and the statement follows from fact.