Let $F:U\rightarrow W$ be a linear transformation from the vector space $U$ to the vectorspace $W$. Show that the image space to $F$,
$$V(F)=\{w\in W:w=F(u) \ \ \text{for some} \ \ u\in U\},$$
is a subspace of $W$.
Okay, I know that in order for $M$ to be a subspace of a vectorspace $V$ then $M$ has to be
- non-empty
- closed under addition with vectors and multiplication with scalars.
So I have to show that $V(F)$ is non empty and closed under addition with vectors and multiplication with scalars.
Can someone break down to me how this is done? I don't really understand what is being stated in the curly brackets and how to apply that to show 1. and 2.
The curly bracket says that $w$ is an element of the set $V(F)$ if and only if $w$ is the result of applying $F$ to some element $u \in U$.
For instance, if $F: \mathbb{R}^2 \to \mathbb{R}^3$ is given by $F(x,y)=(x,0,0)$, then $(1,0,0)$ is in $V(F)$, since $(1,0,0)=F(1,3)$, for example. But $(3,2,0)$ is not in $V(F)$, since if it were, its second coordinate would have to be $0$.
So, suppose that $w_1$ and $w_2$ are in $V(F)$. Then they are the image of some $u_1$ and $u_2$, respectively (i.e., $F(u_1)=w_1$ and $F(u_2)=w_2$).
We want to prove that $w_1+w_2$ is still in $V(F)$. But since $F$ is linear, you have a pretty good candidate for an element $u$ such that $F(u)=w_1+w_2$. Can you tell who it is?
Repeat this train of thought for the rest.