Lecture 4 - (Online) Subspaces and Constructions

Subspaces

Let's just start with the definition:

Subspace

A subspace U of a vector space V if U is also a vector space (under the same operations of U)

The question here is what properties of a subspace are guaranteed given that V itself is a vector space? We expect many properties to carry over to U. There are some things to consider:

  1. The 0 may not be in U. Being a subspace doesn't guarantee it.
  2. We need to be careful that u+vU for any u,vU. It's possible that we leave U and enter the uncovered part of U in V.
  3. Similarly, we may "leave" U when doing scalar multiplication of u.
Theorem

A subset U of a vector space V iff:

  1. Additive Identity: 0U.
  2. Closed under vector addition: x,yU,x+yU
  3. Closed under scalar multiplication: xU,αF,αxU.

Before we prove this, let's go through some examples:

Example

Let W={(x1,x2,0):x1,x2R}. Clearly WR3. We claim that this subset is a subspace of R3.

\begin{proof}

  1. Notice 0=(0,0,0)U.
  2. Let x,yU be arbitrary, so then we can say that x=(x1,x2,0),y=(y1,y2,0), for x1,x2,y1,y2R. Notice that:
x+y=(x1+y1,x2+y2,0)U
  1. Let xU be arbitrary, and likewise for αR. We define x the same as in (2). Notice that:
αx=(αx1,αx2,0)U

Therefore, U is a subspace of R3.
\end{proof}

Example

Recall: Mn×n(F) is the vector space of n×n matrices, with entries from F. Recall that a matrix is symmetric if it is equal to it's transpose (A=AT); the entries are symmetrical about the diagonal. For example:

[012115257]

We claim that the set of n×n symmetric matrices are a subspace of Mn×nF.

\begin{proof}
Let's just prove it for n=3, as the process is largely the same for any n.

  1. Notice 0 is the zero matrix in our subspace:
[000000000]S
  1. Let A,BS. Consider A+BS:
A=[abcbdecef],B=[ghihjkikl],A+B=[a+gb+hc+ib+hd+je+kc+ie+kf+l]S
  1. Let αF. Then:
αA=[αaαbαcαbαdαeαcαeαf]S

\end{proof}

RR

This is the vector space of functions from RR.

\begin{proof}

  1. The zero function is in RR.
  2. ... (you can show the rest pretty easily).
    \end{proof}

Constructions of New Subspaces from Old Ones

Let V be a vector space. Let U,W be subspaces of V. A couple questions we should answer are:

  1. Is UW a subspace of V?
  2. Is UW a subspace of V?

Notice that clearly if (1) is true then (2) must be true, but let's take it one step at a time:

1: Is UW a subspace of V?

Let's look at an example to see what's going on here:

Example

Let U={(x1,x2,0):x1,x2R} and W={(0,x1,x2):x1,x2R}. These both are subspaces of R3, which itself is a vector space.

But notice that UW isn't closed under vector addition. If we take uU and wW, then:

u+w=(u1,u2,0)+(0,w1,w2)=(u1,u2+w1,w2)UW

So UW is not closed under vector addition, so UW is not a subspace of W.

2: Is UW a subspace of V?

It turns out that UW is indeed a vector space. The proof is in HW 1 - Vector Spaces#1.C TODO (read first).

A new question (Smallest Subspace)

What is the smallest subspace of V that contains both UW? We know that it's possible that UW to not be a subspace, but what are the conditions that make it not so?

Define a set S={u+w:uU,wW}. This is essentially saying the set of vectors that are spanned by anything from u and w. You may note that the smallest subspace of V that contains both U and W must also contain S (by definition)

Is S a subspace? Yes! Why? Let's prove it:

\begin{proof}

  1. 0S,0=0+0
  2. Let s1=u1+w1, s2=u2+w2. then s1+s2=(u1+w1)+(u2+w2)=(u1+u2)+(w1+w2). But look! u1+u2U and likewise w1+w2W so then since S is defined as it is, by definition s1+s2S.
  3. Let αF be arbitrary, and sS. Notice that αs=α(u+w)=αu+αw. The former vector αuU and αwW so then by definition then αsS.
    \end{proof}
    Note that S is the smallest subspace containing both u,w. We give S some notation, namely as the sum of two subspaces U,W:
The Sum of Vector Spaces

Suppose U1,...,Um are subspaces of vector space V. The sum of U1,U2,...,Um, denoted by U1+U2+...+Um, is the set of all possible sums of elements from U1,...,Um:

U1+...+Um={u1+...+um|u1U1,...,umUm}

And U1+...+Um is the smallest subspace containing U1,...,Um.

We use the words "smallest" to mean that there exists no strict subset F from U1,...,Um such that F is a vector space while containing all of U1,...,Um.