2.6 KiB
Linear transformations
Definition
Definition: let
V
andW
be vector spaces, a mappingL: V \to W
is a linear transformation or linear map if
L(\lambda \mathbf{v}_1 + \mu \mathbf{v}_2) = \lambda L(\mathbf{v}_1) + \mu L(\mathbf{v}_2),
for all
\mathbf{v}_{1,2} \in V
and\lambda, \mu \in \mathbb{K}
.
In the case that the vector spaces V
and W
are the same; V=W
, a linear transformation L: V \to V
will be reffered to as a linear operator on V
.
The image and kernel
Let L: V \to W
be a linear transformation from a vector space V
to a vector space W
. In this section the effect is considered that L
has on subspaces of V
. Of particular importance is the set of vectors in V
that get mapped into the zero vector of W
.
Definition: let
L: V \to W
be a linear transformation. The kernel ofL
, denoted by\ker(L)
, is defined by
\ker(L) = {\mathbf{v} \in V ;|; L(\mathbf{v}) = \mathbf{0}}.
The kernel is therefore a set consisting of vectors in V
that get mapped into the zero vector of W
.
Definition: let
L: V \to W
be a linear transformation and letS
be a subspace ofV
. The image ofS
, denoted byL(S)
, is defined by
L(S) = {\mathbf{w} \in W ;|; \mathbf{w} = L(\mathbf{v}) \text{ for } \mathbf{v} \in S }.
The image of the entire vector space
L(V)
, is called the range ofL
.
With these definitions the following theorem may be posed.
Theorem: if
L: V \to W
is a linear transformation andS
is a subspace ofV
, then
\ker(L)
is a subspace ofV
.L(S)
is a subspace ofW
.
??? note "Proof:"
Let $L: V \to W$ be a linear transformation and $S$ is a subspace of $V$.
To prove 1, let $\mathbf{v}_{1,2} \in \ker(L)$ and let $\lambda, \mu \in \mathbb{K}$. Then
$$
L(\lambda \mathbf{v}_1 + \mu \mathbf{v}_2) = \lambda L(\mathbf{v}_1) + \mu L(\mathbf{v}_2) = \lambda \mathbf{0} + \mu \mathbf{0} = \mathbf{0},
$$
therefore $\lambda \mathbf{v}_1 + \mu \mathbf{v}_2 \in \ker(L)$ and hence $\ker(L)$ is a subspace of $V$.
To prove 2, let $\mathbf{w}_{1,2} \in L(S)$ then there exist $\mathbf{v}_{1,2} \in S$ such that $\mathbf{w}_{1,2} = L(\mathbf{v}_{1,2})$ For any $\lambda, \mu \in \mathbb{K}$ we have
$$
\lambda \mathbf{w}_1 + \mu \mathbf{w}_2 = \lambda L(\mathbf{v}_1) + \mu L(\mathbf{v}_2) = L(\lambda \mathbf{v}_1 + \mu \mathbf{v}_2),
$$
since $\lambda \mathbf{v}_1 + \mu \mathbf{v}_2 \in S$ it follows that $\lambda \mathbf{w}_1 + \mu \mathbf{w}_2 \in L(S)$ and hence $L(S)$ is a subspace of $W$.