Hi, this is my post-lecture note. A short summary of what we did in class today. (Also a chance to correct my mistakes made in class)
So, what is a vector? There are many possible correct answers (in different sense). You may say one of the following
The notion of vector space is the following.
Let $V$ be a set, we say $V$ is a vector space $V$ over a field $k$ (say, $k=\R$ or $k=\C$) if the following is true * we can add two vectors together and get a vector * we can multiply a number (in $k$) to a vector and get a vector * these two operations needs to satisfy some obvious relations, i.e., if $a, b \in k$ and $v,w \in V$, then $$ (ab)v = a(bv), \quad a(v+w) = av+aw, \quad a \neq 0, v \neq 0 \Rightarrow av \neq 0 \cdots$$.
We then give some examples of vector spaces.
Example :
OK, now that we see many 'weird' vector spaces, we may think twice when we say, “the length of a vector is just $\sqrt{x^2+y^2+z^2}$”, and a vector is just a tuple of numbers. But vector can be identified with a tuple of numbers, once we fix a …
A basis of a vector space $V$ is a maximal collection of linearly independent vectors $V$. The number of vectors in a basis is called the dimension.
Q: is it possible that, for a vector space $V$, I can find a basis with $3$ elements, but someone else can find a basis with $4$ elements? Why not?
Given a basis $e_1, \cdots, e_n$ of an n-dimensional vector space $V$, any element $v$ can be identified with a tuple of numbers $(v_1, …, v_n)$ by the following relation $$ v = v_1 e_1 + \cdots + v_n e_n $$ These $(v_1, \cdots, v_n)$, or $v_i$s, are coordinates of $v$ with respect of the basis $\{e_i\}$.
It is no surprise that, if you change the basis, you will also change the coordinates. Just like when you change unit, the number in front of it changes, 2 meter = 6.5 feet (NBA player Michael Jordan's height), even though they both represent the same length.
That's all. Next time, we will see what is a tensor.