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Linear algebra (Osnabrück 2024-2025)/Part I/Lecture 13/refcontrol

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Projections

For a direct sum decompositionMDLD/direct sum decomposition of a -vector spaceMDLD/vector space , the linear mappingMDLD/linear mapping

is called the first projection (or projection onto with respect to the given decomposition or projection onto along ) and, accordingly,

the second projection of this decomposition. Since and are linear subspaces of , it is reasonable to call the composed mapping

a projection as well. Then we have a projection in the sense of the following definition.


Let be a field,MDLD/field a -vector spaceMDLD/vector space and a linear subspace.MDLD/linear subspace A linear mappingMDLD/linear mapping

is called a projection of onto , if and

holds.

== Example Example 13.2

change==

Let be a finite-dimensionalMDLD/finite-dimensional (vs) -vector spaceMDLD/vector space and , , a basisMDLD/basis (vs) of . For a subset , set

the linear subspaceMDLD/linear subspace corresponding to . Moreover, let

the corresponding projection.MDLD/projection (direct sum) The image of this projection is . On , this mapping is the identity, one can also consider this mapping as

The kernelMDLD/kernel (vs) of this mapping is


For , equipped with the standard basis,MDLD/standard basis we consider subsets with two elements and the corresponding projections[1] (in the sense of Example 13.2 ) onto the coordinate planes. The projections are

The images of some object in under these projections carry names like ground view etc.

For a subset with one element, the projections map to an axis.

A more abstract definition is the following that does not refer to a linear subspace.


Let be a fieldMDLD/field and a -vector space.MDLD/vector space A linear mappingMDLD/linear mapping

is called a projection, if

holds.

The identity and the zero mapping are projections.


LemmaLemma 13.5 change

Let be a fieldMDLD/field and a -vector space.MDLD/vector space For a direct sum decompositionMDLD/direct sum decomposition

the projectionMDLD/projection (direct sum) onto is a projection in the sense of Definition.MDLD/Definition Such a projection

gives a decomposition

and is the projection onto .

Let be the projection onto . Write with . Then we have

and hence

Suppose now that

is an endomorphism with

Let . Then there exists some such that

Then

This means that the intersection of these linear subspaces is the zero space. For an arbitrary , we write

Here, the first summand belongs to the image and, because of

the second summand belongs to the kernel. Therefore, we have a direct sum decomposition.



Spaces of homomorphisms

Let be a field,MDLD/field and let and be -vector spaces.MDLD/vector spaces Then

is called the space of homomorphisms. It is endowed with the addition defined by

and the scalar multiplication defined by

Due to Exercise 13.8 , this is indeed a -vector space.


Let be a -vector spaceMDLD/vector space over the fieldMDLD/field . Then the mappingMDLD/mapping

is an isomorphismMDLD/isomorphism (vs) of vector spaces, see Exercise 13.10 .

The space of homomorphisms plays an important role. It is called the dual space of . In the next lectures, we will discuss it in more details.


LemmaLemma 13.8 change

Let be a field,MDLD/field and let and be

-vector spaces.MDLD/vector spaces Then the following hold.
  1. A linear mappingMDLD/linear mapping

    from another vector space induces a linear mapping

  2. A linear mappingMDLD/linear mapping

    to another vector space induces a linear mapping

Proof



LemmaLemma 13.9 change

Let be a -vector spaceMDLD/vector space together with a direct sum decompositionMDLD/direct sum decomposition

Let be another -vector space and let

and

denote linear mappings.MDLD/linear mappings Then we get, by setting

where is the direct decomposition, a linear mapping

The mapping is well-defined, since the representation with and is unique. The linearity follows from



LemmaLemma 13.10 change

Let be a field,MDLD/field and let and be -vector spaces.MDLD/vector spaces Let

and

de direct sum decompositionsMDLD/direct sum decompositions and let

denote the canonical projections.MDLD/canonical projections (direct sum) Then the mapping

is an isomorphism.MDLD/isomorphism (vs) If we consider as linear subspaces of , then we have the direct sum decomposition

It follows directly from Lemma 13.8 that the given mapping is linear. In order to prove injectivity, let with be given. Then there exists some such that

Let with . Then also for some . Therefore, for some . Hence

In order to prove surjectivity, let a family of homomorphisms , be given, which we consider as mappings to . Then the

are linear mappings from to . This yields via Lemma 13.9 a linear mapping from to , which restricts to the given mappings.



TheoremTheorem 13.11 change

Let denote a fieldMDLD/field and let and denote finite-dimensionalMDLD/finite-dimensional -vector spaces.MDLD/vector spaces Let be a basisMDLD/basis (vs) of and be a basis of . Then the assignment

is an isomorphismMDLD/isomorphism (vs)

of -vector spaces.

The bijectivity was shown in Theorem 10.15 . The additivity follows from

where the index denotes the -th component with respect to the basis .


This means that we can consider the direct sum decomposition for the one-dimensional linear subspaces bzw. corresponding to bases and apply Lemma 13.10 .


CorollaryCorollary 13.12 change

Let denote a field,MDLD/field and let and denote finite-dimensionalMDLD/finite-dimensional -vector spacesMDLD/vector spaces with dimensionsMDLD/dimensions (vs) and . Then

This follows immediately from Theorem 13.11 .



Linear subspaces of homomorphism spaces

LemmaLemma 13.13 change

Let and be vector spacesMDLD/vector spaces over a fieldMDLD/field . Then the following subsets are linear subspacesMDLD/linear subspaces

of .
  1. For a linear subspace ,

    is a linear subspace of . If and are finite-dimensional,MDLD/finite-dimensional then

  2. For a linear subspace ,

    is a linear subspace of , which is isomorphicMDLD/isomorphic (linear) to . If and are finite-dimensional,MDLD/finite-dimensional then

  3. For linear subspaces and ,

    is a linear subspace of . If and finite-dimensional,MDLD/finite-dimensional then

  4. For linear subspaces and ,

    is a linear subspace of .

(1). It is clear that we have a linear subspace. In order to prove the statement about the dimension, let be an direct complementMDLD/direct complement of in , so that

Let be a basis of . Every linear mapping from maps to , and on (or on a basis thereof) we have free choice. Therefore

and the statement follows from Corollary 13.12 .

(2). It is clear that we have a linear subspace. The natural mapping

of Lemma 13.8   (2) is injective in this case. Therefore,

(3). It is clear that we have a linear subspace. In the finite-dimensional case, let

be a direct sum decomposition. Due to Lemma 13.10 , we have

and

Therefore, the dimension equals

(4). Setting

we have . Hence, (4) follows from (3).



Let denote a fieldMDLD/field and let and denote finite-dimensionalMDLD/finite-dimensional -vector spaces.MDLD/vector spaces We consider the natural mapping

where we have the product space on the left. This mapping is not linear in general. We have, on one hand,

and, on the other hand,

so, if we fix one component, we have additivity (and also compatibility with the scalar multiplication) in the other component. In the product space, we have

and, therefore,

(only in exceptional cases we have ).



Footnotes
  1. These projections are even orthogonal projections. This term requires that an inner product is defined, a concept we will discuss in the second term. Here, we only deal with linear projections, which depend, different from the orthogonal case, from the direct complement chosen.


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