# Vector Spaces

September 19, 2011 16 Comments

If you aren’t feeling totally comfortable with fields, don’t fret. While we can talk about vector spaces over any field, you can think about them as over if that helps you geometrically.

We started out pointing out the importance of and other well-known fields. But if the real line is important, then the real plane should be twice as important! And is important too. That’s “3-dimensional” space, where we live. I use quotation marks, because we don’t know what dimension is yet.

These objects aren’t fields in any obvious way. (How do I multiply points in , or take their inverses?). These are what we call vector spaces. A **vector space** over a field is closed under some commutative operation addition, and we can multiply by elements from our field. What the hell? This feels so arbitrary. Let’s look at for an example.

If we have two points and in , we can add them by adding their components. That is

Well, we can also multiply them by elements of our field (in this case, we will use ). If , we can *scale* by , by saying that

.

You should think of the elements of our vector space, called *vectors*, as pointing in some direction, as the image shows. When we multiply by element in our field, we *scale* the vectors.

is sometimes called the *scalar field*. In the image, the dotted vector is scaled by the scalar to get the vector labeled .

Notice that the “starting point” of a vector isn’t really important. What is important is the displacement it represents.

Let’s write out the rules for a vector space once in full generality. If you ever feel lost, just think about and this picture. Pretty much everything works analogously (with the proper analogy).

A vector space over a field has addition and scalar multiplication such that

- satisfies all the rules about for a field (commutativity, associativity, identity, inverses)
- If and , then .
- If , and , .

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