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math121b:01-22

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2020-01-22, Wednesday

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

  • it is an arrow with a starting point and ending point (ha, you are thinking of a displacement vector)
  • it is an ordered set (a.k.a tuple) of numbers, like (2,3,1)(2,3,-1) a 3-dim vector, or (2,3)(2,3) a 2-dim vector. You represent it by an arrow from the origin to the point with that coordinate.
  • (and the most boring yet correct answer) it is an element in the vector space. (well, great, it is like asking, what is 2 + 3? and the answer is 3 + 2.) but this is correct, since, after we learned so many examples of various general vector spaces (the space of degree 2 polynomials, the solution space to differential equations, etc), you cannot simply say that vector is just a tuple of numbers.

The notion of vector space is the following.

Let VV be a set, we say VV is a vector space VV over a field kk (say, k=Rk=\R or k=Ck=\C) if the following is true * we can add two vectors together and get a vector * we can multiply a number (in kk) to a vector and get a vector * these two operations needs to satisfy some obvious relations, i.e., if a,bka, b \in k and v,wVv,w \in V, then (ab)v=a(bv),a(v+w)=av+aw,a0,v0av0 (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 :

  1. Fix a positive number NN, then the set of real coefficient polynomials f(x)f(x), where deg(f)Ndeg(f) \leq N forms a vector space over R\R. A basis of this vector space is {1,x,,xN}\{1, x, \cdots, x^N\}, hence the dimension is N+1N+1.
  2. The space of solution to f(x)+xf(x)=0f''(x) + x f(x) = 0 forms a 2 dimension vector space.
  3. In general, a degree kk homogeneous ordinary differential equation has solution space kk-dimensional. That is why when we write down the general solution, we write f(x)=c1f1(x)++ckfk(x) f(x) = c_1 f_1(x) + \cdots + c_k f_k(x) where the set {fi(x)}\{f_i(x)\} are linearly independent solutions, and cic_i are constants.

OK, now that we see many 'weird' vector spaces, we may think twice when we say, “the length of a vector is just x2+y2+z2\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 …

Basis

A basis of a vector space VV is a maximal collection of linearly independent vectors VV. The number of vectors in a basis is called the dimension.

Q: is it possible that, for a vector space VV, I can find a basis with 33 elements, but someone else can find a basis with 44 elements? Why not?

Coordinates

Given a basis e1,,ene_1, \cdots, e_n of an n-dimensional vector space VV, any element vv can be identified with a tuple of numbers (v1,,vn)(v_1, …, v_n) by the following relation v=v1e1++vnen v = v_1 e_1 + \cdots + v_n e_n These (v1,,vn)(v_1, \cdots, v_n), or viv_is, are coordinates of vv with respect of the basis {ei}\{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.

math121b/01-22.txt · Last modified: 2020/01/22 21:53 (external edit)