What are the properties of distance?

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Discussion Overview

The discussion revolves around the properties of distance in the context of Euclidean space, specifically examining the definitions and implications of distance between points and sets. Participants explore the mathematical definitions of distance, including the Euclidean metric and its properties, as well as potential issues with using minimum values in distance calculations between sets.

Discussion Character

  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant proposes that the distance function $d(u, w) = 0 \iff u = w$ is valid based on the definition of the Euclidean norm.
  • Another participant questions the definition of the distance between sets, suggesting that the minimum distance may not be attained in certain cases, such as with open intervals.
  • Some participants agree that the proofs presented are correct based on the definitions provided, while others express skepticism about the use of "min" instead of "inf" in the context of distance between sets.
  • There is a discussion about the properties of different metrics, including the Euclidean metric and the Minkowski metric, with one participant noting that the latter does not satisfy the standard definition of a metric.
  • Participants discuss the implications of using different types of metrics and the importance of understanding their properties in various contexts.

Areas of Agreement / Disagreement

Participants express differing views on the appropriateness of using minimum values in distance calculations, with some agreeing on the correctness of the proofs while others raise concerns about the definitions used. The discussion remains unresolved regarding the best approach to defining distance between sets.

Contextual Notes

Participants highlight limitations in the definitions provided, particularly regarding the attainment of minimum values in distance calculations. The discussion also touches on the distinction between different types of metrics and their properties, which may affect the conclusions drawn.

mathmari
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Hey!

Let $v, w\in \mathbb{R} ^n$ and let $V, W\subseteq \mathbb{R} ^n$.

I want to show the following properties :
  • $d(u.,w)=0\iff u=v$
  • $d(V, W) =0\iff V\cap W\neq \emptyset$
I have done the following:

  • $d(u, w) =0\iff |u-w|=0\iff u-w=0\iff u=w$

    Or do we have to do more steps?

    $$$$
  • $d(V, W) =0\iff \min \{d(v, w) \} =0$ this means that there exists $v$ and $w$ such that $d(v, w) =0$ and from the previous one it follows that $v=w$ which means that the intersection is non empty.

    Is that correct?

(Wondering)
 
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Hey mathmari!

What is your function $d$ exactly? (Wondering)
 
Klaas van Aarsen said:
What is your function $d$ exactly? (Wondering)

The following definitions are given:

  • $v$ is orthogonal to $w$, if $v\cdot w=0_{\mathbb{R}}$.
  • $|v|:=\sqrt{v\cdot v}$ is the lengthh of the vector $v$.
  • $d(v,w):=|v-w|$ is the distance between the vectors $v$ and $w$.
    $d(V,W):=\min \{d(v,w)\mid v\in V, w\in W\}$ is the distance between $V$ and $W$.
 
mathmari said:
The following definitions are given:

  • $v$ is orthogonal to $w$, if $v\cdot w=0_{\mathbb{R}}$.
  • $|v|:=\sqrt{v\cdot v}$ is the lengthh of the vector $v$.
  • $d(v,w):=|v-w|$ is the distance between the vectors $v$ and $w$.
    $d(V,W):=\min \{d(v,w)\mid v\in V, w\in W\}$ is the distance between $V$ and $W$.
That definition of $d(V,W)$ is very suspicious because the minimum value $\min \{d(v,w)\mid v\in V, w\in W\}$ is not usually attained. For example, if you define $V, W\subset \Bbb{R}$ to be the open intervals $V=(0,1)$ and $W=(1,2)$ then $\inf \{d(v,w)\mid v\in V, w\in W\} = 0$. But $\min \{d(v,w)\mid v\in V, w\in W\}$ does not exist. You can find $v\in V$ and $w\in W$ with $d(v,w)$ arbitrarily close to $0$. But that distance can never be equal to $0$.
 
mathmari said:
The following definitions are given:

  • $v$ is orthogonal to $w$, if $v\cdot w=0_{\mathbb{R}}$.
  • $|v|:=\sqrt{v\cdot v}$ is the lengthh of the vector $v$.
  • $d(v,w):=|v-w|$ is the distance between the vectors $v$ and $w$.
    $d(V,W):=\min \{d(v,w)\mid v\in V, w\in W\}$ is the distance between $V$ and $W$.

With that definition I believe that your proofs are all correct. (Happy)

Opalg said:
That definition of $d(V,W)$ is very suspicious because the minimum value $\min \{d(v,w)\mid v\in V, w\in W\}$ is not usually attained. For example, if you define $V, W\subset \Bbb{R}$ to be the open intervals $V=(0,1)$ and $W=(1,2)$ then $\inf \{d(v,w)\mid v\in V, w\in W\} = 0$. But $\min \{d(v,w)\mid v\in V, w\in W\}$ does not exist. You can find $v\in V$ and $w\in W$ with $d(v,w)$ arbitrarily close to $0$. But that distance can never be equal to $0$.

Suspicious or not, it merely means that the distance of such open intervals is not defined, isn't it?
It would probably be 'nicer' if they used $\inf$ instead of $\min$, but for the problem at hand it does not really matter does it?
Those $V$ and $W$ are probably intended to be linear or affine sub spaces or some such, in which case the distinction would not be relevant. (Thinking)
 
Klaas van Aarsen said:
With that definition I believe that your proofs are all correct. (Happy)

Can we just say that $|u-w|=0\iff u-w=0$ ? Or do we have to use some more steps in between? (Wondering)
 
mathmari said:
Can we just say that $|u-w|=0\iff u-w=0$ ? Or do we have to use some more steps in between?

Well, $|\cdot|$ is the Euclidean norm here.
Part of the definition of a norm, is that $|x|=0 \iff x=0$.
So as such we can simply use that. (Nod)
We might mention that it is because $|\cdot|$ is a norm.

To be fair, your $d$ is the Euclidean metric.
Part of the definition of a metric, is that $d(x,y)=0 \iff x=y$ (point separating).
So there was no actual need to prove it. We could have referred to the definition of a metric instead. (Nerd)
 
@mathmari

Just a note to explain why we need to be careful. The metric (distance function, norm, whatever) you are using is Eudlidean and has all the familiar properties, such as [math]x = 0 \implies ||x|| = 0[/math]. That's because the metric that Klaas van Aarsen mentioned (and is also the one you are using) is positive definite, which means the norm is either 0 or real.

But there are other useful metrics. For example, in SR, we have an indefinite metric, which means that [math]x \cdot x[/math] can be negative, zero, or positive. (Setting c = 1 for convenience the Minkowski metric says that the vector <0, 0, 1, 0> has a norm of -1 and that the vector <1, 0, 1, 0> has a norm of 0.)

There are all sorts of fun metrics out there. (Sun)

-Dan
 
For the distance between two sets, it would be better to use "least upper bound" rather than "min". In R1 the distance between U= (0, 1) and V= (2, 3) is "lub(|x- y|, x in U, y in V)= 1" while "min(|x- y|, x in U. y in V)" does not exist.
 
  • #10
topsquark said:
@mathmari

Just a note to explain why we need to be careful. The metric (distance function, norm, whatever) you are using is Eudlidean and has all the familiar properties, such as [math]x = 0 \implies ||x|| = 0[/math]. That's because the metric that Klaas van Aarsen mentioned (and is also the one you are using) is positive definite, which means the norm is either 0 or real.

But there are other useful metrics. For example, in SR, we have an indefinite metric, which means that [math]x \cdot x[/math] can be negative, zero, or positive. (Setting c = 1 for convenience the Minkowski metric says that the vector <0, 0, 1, 0> has a norm of -1 and that the vector <1, 0, 1, 0> has a norm of 0.)

There are all sorts of fun metrics out there. (Sun)

-Dan

This has been a source of confusion to me. ;)

The so called Minkowski metric does not satisfy the generally used definition of a metric.
Interestingly, the wiki article of a metric does not even mention the Minkowski metric. It does mention various other flavors, such as pseudometrics, quasimetrics, and semimetrics, but the Minkowski metric is none of those!

Moreover, the wiki article for the Minkowski metric does not make any mention that it is not a metric according to the usual definition of a metric.
Confusing indeed!

Either way, as I interpret it, the Minkowski metric is formally not a metric. Instead it is a metric tensor. (Nerd)
 
  • #11
Klaas van Aarsen said:
Either way, as I interpret it, the Minkowski metric is formally not a metric. Instead it is a metric tensor. (Nerd)
(Swearing) Jim, I'm a Physicist, not a Mathematician!

Good catch!

-Dan
 

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