Show R^2 is locally compact with non-standard metric

In summary, the distance between points \left( x_1 , y_1\right) and \left( x_2 , y_2\right) in the plane is defined to be \left| y_1 -y_2\right| if x_1 = x_2 and 1+ \left| y_1 -y_2\right| if x_1 \neq x_2. This is indeed a metric on the plane, as it satisfies the properties of being positive definite, symmetric, and satisfying the triangle inequality. The resulting metric space is also locally compact, meaning that every point has a neighborhood with compact closure. To prove this, we can consider the open and closed k
  • #1
benorin
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The Q: Define the distance between points [itex]\left( x_1 , y_1\right) [/itex] and [itex]\left( x_2 , y_2\right) [/itex] in the plane to be

[tex]\left| y_1 -y_2\right| \mbox{ if }x_1 = x_2 \mbox{ and } 1+ \left| y_1 -y_2\right| \mbox{ if }x_1 \neq x_2 .[/tex]

Show that this is indeed a metric, and that the resulting metric space is locally compact. I need help with the second part.

My A: Write

[tex]d\left( \left( x_1 , y_1\right) , \left( x_2 , y_2\right) \right) = \delta_{x_1}^{x_2} + \left| y_1 -y_2\right| ,[/tex]

where

[tex]\delta_{x_1}^{x_2}=\left\{\begin{array}{cc}0,&\mbox{ if }
x_{1} = x_{2}\\1, & \mbox{ if } x_{1} \neq x_{2}\end{array}\right.[/tex]

is the Kronecker delta function. Then [itex]d:\mathbb{R} ^2 \times \mathbb{R} ^2 \rightarrow \mathbb{R}[/itex] is a metiric on [itex]\mathbb{R} ^2[/itex] since the following hold:

i. d is positive definite since d is obviously positive and

[tex]\delta_{x_1}^{x_2}=0 \Leftrightarrow x_{1} = x_{2} \mbox{ and } \left| y_1 -y_2\right| = 0 \Leftrightarrow y_{1} = y_{2}[/tex]

ii. d is symmetric in its variables, that is

[tex]d\left( \left( x_1 , y_1\right) , \left( x_2 , y_2\right) \right) = \delta_{x_1}^{x_2} + \left| y_1 -y_2\right| = \delta_{x_2}^{x_1} + \left| y_2 -y_1\right| = d\left( \left( x_2 , y_2\right) , \left( x_1 , y_1\right) \right)[/tex]

iii. d the triangle inequality, that is: if [itex]\left( x_j , y_j\right) \in \mathbb{R} ^2, \mbox{ for } j=1,2,3,[/itex] then

[tex]d\left( \left( x_1 , y_1\right) , \left( x_2 , y_2\right) \right) \leq d\left( \left( x_1 , y_1\right) , \left( x_3 , y_3\right) \right) + d\left( \left( x_3 , y_3\right) , \left( x_2 , y_2\right) \right) ,[/tex]

which can be reasoned thus: the triangle inequality in R^2 with the Euclidian metric gives

[tex]\left| y_1 -y_2\right| \leq \left| y_1 -y_3\right| + \left| y_3 -y_2\right| , \forall y_{1},y_{2},y_{3}\in\mathbb{R}[/tex]

and

[tex]\delta_{x_1}^{x_2} \leq \delta_{x_1}^{x_3} + \delta_{x_3}^{x_2} \mbox{ holds } \forall x_{1},x_{2},x_{3}\in\mathbb{R}[/tex]

for suppose not: then

[tex]\exists x_{1},x_{2},x_{3}\in\mathbb{R} \mbox{ such that }\delta_{x_1}^{x_2} > \delta_{x_1}^{x_3} + \delta_{x_3}^{x_2} \Leftrightarrow x_1 \neq x_2 \mbox{ and } x_1 = x_3 = x_2 ,[/tex]

which is a contradiction; adding these inequalities yields the required result, viz. the triangle inequality.

By i,ii, and iii, d is a metric on [itex]\mathbb{R} ^2[/itex].

The locally compact part I don't get: a metric space is locally compact iff every point of has a neighborhood with compact closure.

An open neighborhood of a point, say [itex]\left( x_0 , y_0\right) [/itex], is given by: for some k>0, put

[tex]\left\{ \left( x , y\right) : d\left( \left( x , y\right) , \left( x_0 , y_0\right) \right) < k \right\}[/tex]

but what does that look like? How do I grasp what compact means in this metric?

The delta function above is the discrete metric on R^1 and the absolute value is the Euclidian metric on R^1, and their sum is indeed a metric on the product space R^2. Do I get to keep Heine-Borel? Does Heine-Borel even hold for R^1 with the discrete metric? I don't get the idea of compact sets with H-B, I can tell you "A set is compact if every open cover has a finite subcover," but that topology stuff is so abstract. What does it mean for a set to be compact in terms of a given metric? Is that given by sequential compactness?

Please help with the second part, and let me know if the first is ok.

Thanks,
-Ben

PS: Please don't answer all the questions in the last paragraph, just the ones that help.
 
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  • #2
As is often the case the first hint is: well, just do it. You need to decide what the open sets look like:

Fix u. Suppose d(u,v)<k, take it into two cases, k<1, k>=1

if k<1 then obviously the x coords of u and v must agree, so where must v lie?

if k=>1, split into two subcases, when x_1=x_2 and when it doesn't.

I think drawing things on paper will help here.

And you should have proven by now that in a metric space compactness and sequential compactness are the same, not that you need it. I doubt H-B is any use what so ever here; I suspect you can do the rest simply by thinking about what open sets look like.

For example, take R with the zariski topology: closed sets are sets with a finite number of points. Any set S is compact: let X_r be an open cover of a set, consider X_1, this contains all but a finite number of points of S since X_1 is open and contains all but a finite number of points of R, label the points in S but not in X_1 as s_2, s_3,.., s_r and then pick some X_(r_i) that contains the point s_i and this is a finite refinement of the open cover.
 
Last edited:
  • #3
proof of compactness

The closed k-ball about [itex]\left( x_0 , y_0\right) [/itex] is given by

[tex]\left\{ \left( x , y\right) : d\left( \left( x , y\right) , \left( x_0 , y_0\right) \right) \leq k \right\} = \left\{ \left( x , y\right) : \delta_{x_0}^{x} + \left| y_0 -y\right| \leq k \right\} [/tex]

which for [itex]0<k<1[/itex] is

[tex]\left\{ \left( x , y\right) : x=x_{0}\mbox{ and }\left| y_0 -y\right| \leq k \right\} ,[/tex]

the closed vertical line segment centered about [itex]\left( x_0 , y_0\right) [/itex] of length [itex]2k< 2[/itex].

and for [itex]1 \leq k <\infty[/itex] is

[tex]\left\{ \left( x , y\right) : x=x_{0}\mbox{ and }\left| y_0 -y\right| \leq k \right\}\cup \left\{ \left( x , y\right) : x\neq x_{0}\mbox{ and }\left| y_0 -y\right| \leq k-1 \right\} ,[/tex]

the union of the closed vertical line segment centered about [itex]\left( x_0 , y_0\right) [/itex] of length [itex]2k \geq 2[/itex] and the closed horizontal strip centered about [itex]\left( x_0 , y_0\right) [/itex] of hieght [itex]2(k-1) \geq 0[/itex]extending infinitely in both directions (the degenerate case of k=1 give a horizontal line).

So how do I prove that these are compact? The open k-balls are the same except with "open" in place of "closed", and recall that closed (open) k-balls are closed (open) in any metric space. I know they're compact, so I am guessing proof by contradiction, but I can't get anywhere.
 
  • #4
Duh! I think it's clear now.

The case of 0<k<1 is compact (closed and bounded) with the usual Euclidian metric.

k>1 has a atleast one counter-example.
 
  • #5
You only have to show that each point has some neighbourhood with compact closure. Don't even bother looking at k>1. Looking at 0<k<1, you have to first find out what the closure of the vertical open interval is with respect to this topology, and then whether that closure is compact with respect to this topology. I think you just went straight to talking about the closed ball as the vertical closed interval. This is true, i.e. the closure of the vertical open interval in this topology is the vertical closed interval, but you should prove this. You then have to prove it is compact, and it is pretty simple if you can prove that the closed interval in R is compact under the standard metric, but you can't just say that the set is closed and bounded, thus compact.
 

1. What is a non-standard metric?

A non-standard metric is a way to measure the distance between two points in a space that is different from the traditional Euclidean metric. It can involve different rules or definitions for distance, such as using a different set of units or allowing certain paths to have zero length.

2. How is R^2 locally compact with a non-standard metric?

To show that R^2 is locally compact with a non-standard metric, we need to prove that it satisfies two conditions: every point in R^2 has a compact neighborhood, and R^2 is Hausdorff. This can be done by constructing a new metric that satisfies these conditions and showing that it is equivalent to the non-standard metric.

3. What is the significance of R^2 being locally compact with a non-standard metric?

The fact that R^2 is locally compact with a non-standard metric has important implications in mathematical analysis and topology. It allows us to study the properties of R^2 using a different set of tools and techniques, which can lead to new insights and discoveries.

4. Are there any practical applications of this result?

While the main focus of studying locally compact spaces with non-standard metrics is theoretical, there are some practical applications. For example, non-standard metrics have been used in physics to describe the behavior of particles in non-Euclidean spaces, and in computer science to model the behavior of complex systems.

5. Can this result be extended to higher dimensions?

Yes, the result that R^2 is locally compact with a non-standard metric can be extended to higher dimensions. In fact, it has been proven that any finite-dimensional Euclidean space is locally compact with a non-standard metric. However, the techniques used to prove this result may differ as the dimension increases.

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