01-12
Dual Space
Set of all linear homogenous maps from $V \rightarrow F$ is called its dual, or $\tilde V$ with $\langle \alpha a+\beta b;\gamma c + \delta d\rangle = \alpha\gamma\langle a;c\rangle + \beta\gamma\langle b;c\rangle + \alpha\delta\langle a;d\rangle + \beta\delta\langle b;d\rangle$
Hence the dual is also a [01-07#Vector Spaces|Vector Space].
Subspaces
A subset $V’$ of $V$ which is also a Vector space over $F$
Trivially,
- Null Space - $V’ = {|0\rangle}$
- $V$ itself
Other subspaces are called proper subspaces.
- $\mathbb R^2 \subset \mathbb R^3$
- $\mathbb{M}$
- $\text{Symmetric} \subset \mathbb{M}$
- $\text{Anti-Symmetric} \subset \mathbb{M}$
- Hence $\mathbb{M} = S \oplus A$
- Sq Int functions ($L^2$) $\subset$ Functions on $\mathbb R \to \mathbb{R}$
Norm
Map $||w||: V \to \mathbb{R}$ such that:
- $\forall v \in V, ||v||\ge 0$
- $||v|| = 0 \iff |v\rangle= |0\rangle$
- $||\alpha v|| = |\alpha| ||v||$
- Trinagle Inequality: $||u+v|| \le ||u||+||v||$
A space with a norm becomes a [[01-07#Metric space|Metric Space]] with $d(u, v) = ||u-v||$.
Example
- Euclidean norm
- Taxi Cab Norm on $\mathbb R^n = \sum_i^n ||x_i||$
- pNorm = $(\sum_i^n x_i^p)^\frac{1}{p}$
- max Norm = $\max_i(x_i)$ = $\infty$-norm
Exercises
- Prove $||u-v|| \ge ||u||-||v||$
- Prove space with norm is a metric space
- Prove max norm is $\infty$ Norm