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Math4201Topology I (Lecture 12)

Math4201 Topology I (Lecture 12)

Metric spaces

Basic properties and definitions

Definition of metric space

A metric space is a set XX with a function d:X×XRd:X\times X\to \mathbb{R} that satisfies the following properties:

  1. x,yX,d(x,y)0\forall x,y\in X, d(x,y)\geq 0 and d(x,y)=0d(x,y)=0 if and only if x=yx=y. (positivity)
  2. x,yX,d(x,y)=d(y,x)\forall x,y\in X, d(x,y)=d(y,x). (symmetry)
  3. x,y,zX,d(x,z)d(x,y)+d(y,z)\forall x,y,z\in X, d(x,z)\leq d(x,y)+d(y,z). (triangle inequality)

Example of metric space

Let X=RX=\mathbb{R} and d(x,y)=xyd(x,y)=|x-y|.

Check definition of metric space:

  1. Positivity: d(x,y)=xy0d(x,y)=|x-y|\geq 0 and d(x,y)=0d(x,y)=0 if and only if x=yx=y.
  2. Symmetry: d(x,y)=xy=yx=d(y,x)d(x,y)=|x-y|=|y-x|=d(y,x).
  3. Triangle inequality: d(x,z)=xzxy+yz=d(x,y)+d(y,z)d(x,z)=|x-z|\leq |x-y|+|y-z|=d(x,y)+d(y,z) since a+ba+b|a+b|\leq |a|+|b| for all a,bRa,b\in \mathbb{R}.

Let XX be arbitrary. The trivial metric is d(x,y)={0if x=y1if xyd(x,y)=\begin{cases} 0 & \text{if } x=y \\ 1 & \text{if } x\neq y \end{cases}

Check definition of metric space:

  1. Positivity: d(x,y)={0if x=y1if xy0d(x,y)=\begin{cases} 0 & \text{if } x=y \\ 1 & \text{if } x\neq y \end{cases}\geq 0 and d(x,y)=0d(x,y)=0 if and only if x=yx=y.
  2. Symmetry: d(x,y)={0if x=y1if xy=d(y,x)d(x,y)=\begin{cases} 0 & \text{if } x=y \\ 1 & \text{if } x\neq y \end{cases}=d(y,x).
  3. Triangle inequality use case by case analysis.

Balls of a metric space forms a basis for a topology

Let (X,d)(X,d) be a metric space. xXx\in X and r>0,rRr>0, r\in \mathbb{R}. We define the ball of radius rr centered at xx as Br(x)={yX:d(x,y)<r}B_r(x)=\{y\in X:d(x,y)<r\}.

Goal: Show that the balls of a metric space forms a basis for a topology.

{Br(x)xX,r>0,rR} is a basis for a topology on X\{B_r(x)|x\in X,r>0,r\in \mathbb{R}\}\text{ is a basis for a topology on }X

Example of balls of a metric space

Let X=RX=\mathbb{R} and d(x,y)={0if x=y1if xyd(x,y)=\begin{cases} 0 & \text{if } x=y \\ 1 & \text{if } x\neq y \end{cases}

The balls of this metric space are:

Br(x)={{x}if r<1Xif r1B_r(x)=\begin{cases} \{x\} & \text{if } r<1 \\ X & \text{if } r\geq 1 \end{cases}
Note

This basis generate the discrete topology of XX.


Let X=RX=\mathbb{R} and d(x,y)=xyd(x,y)=|x-y|.

The balls of this metric space are:

Br(x)={(xr,x+r)}B_r(x)=\{(x-r,x+r)\}

This basis is the set of all open sets in R\mathbb{R}, which generates the standard topology of R\mathbb{R}.

Proof

Let’s check the two properties of basis:

  1. xX\forall x\in X, Br(x){Br(x)xX,r>0,rR}\exists B_r(x)\in \{B_r(x)|x\in X,r>0,r\in \mathbb{R}\} such that xBr(x)x\in B_r(x). (Trivial by definition of non-zero radius ball)
  2. Br(x),Br(y){Br(x)xX,r>0,rR}\forall B_r(x),B_r(y)\in \{B_r(x)|x\in X,r>0,r\in \mathbb{R}\}, zBr(x)Br(y)\forall z\in B_r(x)\cap B_r(y), Br(z){Br(x)xX,r>0,rR}\exists B_r(z)\in \{B_r(x)|x\in X,r>0,r\in \mathbb{R}\} such that zBr(z)Br(x)Br(y)z\in B_r(z)\subseteq B_r(x)\cap B_r(y).

Observe that for any zBr(x)z\in B_r(x), then there exists δ>0\delta>0 such that Bδ(z)Br(x)B_\delta(z)\subseteq B_r(x).

Let δ=rd(x,z)\delta=r-d(x,z), then Bδ(z)Br(x)B_\delta(z)\subseteq B_r(x) (by triangle inequality)

Similarly, there exists δ>0\delta'>0 such that Bδ(z)Br(y)B_\delta'(z)\subseteq B_r(y).

Take λ=min{δ,δ}\lambda=min\{\delta,\delta'\}, then Bλ(z)Br(x)Br(y)B_\lambda(z)\subseteq B_r(x)\cap B_r(y).

Definition of Metric topology

For any metric space (X,d)(X,d), the topology generated by the balls of the metric space is called metric topology.

Definition of metrizable

A topological space (X,T)(X,\mathcal{T}) is metrizable if it is the metric topology for some metric dd on XX.

Q: When is a topological space metrizable?

Lemma: Every metric topology is Hausdorff

If a topology isn’t Hausdorff, then it isn’t metrizable.

Example of non-metrizable space

Trivial topology with at least two points is not Hausdorff, so it isn’t metrizable.


Finite complement topology on infinite set is not Hausdorff.

Suppose there exists x,yXx,y\in X such that xyx\neq y and xUXx\in U\subseteq X and yVXy\in V\subseteq X such that XUX-U and XVX-V are finite.

Since UV=U\cap V=\emptyset, we have VXUV\subseteq X-U, which is finite. So XVX-V is infinite. (contradiction that XVX-V is finite)

So XX with finite complement topology is not Hausdorff, so it isn’t metrizable.

Proof

Let x,y(X,d)x,y\in (X,d) and xyx\neq y. To show that XX is Hausdorff, it is suffices to show that there exists r,r>0r,r'>0 such that Br(x)Br(y)=B_r(x)\cap B_r'(y)=\emptyset.

Take r=r=12d(x,y)r=r'=\frac{1}{2}d(x,y), then Br(x)Br(y)=B_r(x)\cap B_r'(y)=\emptyset. (by triangle inequality)

We prove this by contradiction.

Suppose zBr(x)Br(y)\exists z\in B_r(x)\cap B_r'(y), then d(x,z)<rd(x,z)<r and d(y,z)<rd(y,z)<r'.

Then d(x,y)d(x,z)+d(z,y)<r+r=12d(x,y)+12d(x,y)=d(x,y)d(x,y)\leq d(x,z)+d(z,y)<r+r'=\frac{1}{2}d(x,y)+\frac{1}{2}d(x,y)=d(x,y). (contradiction d(x,y)<d(x,y)d(x,y)<d(x,y))

Therefore, XX is Hausdorff.

Other metrics on Rn\mathbb{R}^n

Let Rn\mathbb{R}^n be the set of all nn-tuples of real numbers with standard topology.

Let d:Rn×RnRd: \mathbb{R}^n\times \mathbb{R}^n\to \mathbb{R} be defined by (the Euclidean distance)

d(u,v)=i=1n(uivi)2d(u,v)=\sqrt{\sum_{i=1}^n (u_i-v_i)^2}

In R2\mathbb{R}^2 the ball is a circle.

Let ρ(u,v)=maxi=1nuivi\rho(u,v)=\max_{i=1}^n |u_i-v_i|. (Square metric)

In R2\mathbb{R}^2 the ball is a square.

Let m(u,v)=i=1nuivim(u,v)=\sum_{i=1}^n |u_i-v_i|. (Manhattan metric)

In R2\mathbb{R}^2 the ball is a diamond.

Lemma: Square metric, Manhattan metric, and Euclidean metric are well defined metrics on Rn\mathbb{R}^n

Proof ignored. Hard part is to show the triangle inequality. May use Cauchy-Schwarz inequality.

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