Lecture 5 - Subspaces and Direct Sums

Review

Subspace

A subset U of a vector space V is a subspace of V (which is over field F) if U is a vector space itself (over the same field and using the same operations as those in V).

This is a pretty simple definition. It's just a smaller vector space inside of another one. For example:

Thus we require certain conditions on the subspace:

Subspace conditions

U is a subspace of V iff:

  1. 0→∈U, so U contains the additive identity
  2. u1+u2∈U for any two vectors u1,u2∈U. This is closure under addition.
  3. αu∈U for any α∈F,u∈U. This is closure under scalar multiplication.

Note that (1) says that 0→∈U. But this is really saying that 0→∈V must be the same 0→ as the one from U. But why is this guaranteed?!?!? Suppose that 0→u≠0→v where both are still additive identities from their respective sets. Let u→∈U be arbitrary, and notice that u→+0→u=u→=u→+0→v. Cancel u→ from both sides and see that 0→u=0→v.

Another example:

Example

Let U={p(x)∈P6(R)|p′(1)=0}. Is U a subspace of P6(R)?

Proof
It is because:

  1. p0(x)=0 so p0′(x)=0 and p0′(1)=0 so p0(x)∈U.
  2. Let p,q∈U be arbitrary, so p′(1)=0=q′(1). Then notice that (p+q)′(1)=(p′+q′)(1)=p′(1)+q′(1)=0+0=0 so p+q∈U.
  3. Let α∈R and p∈U be arbitrary, so p′(1)=0. Then notice that (αp)′(1)=(αp′)(1)=αp′(1)=α0=0 so then αp∈U.
    ☐

Direct Sums of Subspaces

Sums of Subspaces

Given subspaces U1,...,Un of V, then sum of U1,...,Un, denoted by:

U1+...+Un={u→1+...+u→n|u→i∈Ui}

Is the smallest subspaces containing each U1,...,Un.

Note that any u→i could be 0→, or even any linear combination of vectors from Ui. Thus, this simple addition allows vector combinations between possibly different subspaces.

A direct sum goes one step further in saying that each vector in this space can be written uniquely in this way. When it's a direct sum we say:

U1⊕⋯⊕Un

Instead of the standard + sign.