Equivalent definitions of Equivalent metrics.

In summary, two metrics 'd' and 'f' are considered equivalent on a metric space X if they have the same set of open sets. This means that every open ball with respect to d contains an open ball with respect to f and vice versa. However, the existence of two positive constants 'a' and 'b' such that a*d(x,y) <= f(x,y) <= b*d(x,y) for all x,y in X is a sufficient but not necessary condition for two metrics to be equivalent. The implication is actually reversed, and there is a notion of "uniformly equivalent" that satisfies this condition.
  • #1
Oster
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Two metrics 'd' and 'f' are said to be equivalent on a metric space X, if they have the same set of open sets. This is equivalent to saying every open ball with respect to d contains an open ball with respect to f (different radius) and vice versa. (As every open set is a union of open balls).

What I don't quite understand is how these definitions imply that there exist 2 positive constants 'a' and 'b' such that a*d(x,y) <= f(x,y) <= b*d(x,y) for all x,y in X

Can someone please shed some light on this or point me in the direction of some related article.

PS can someone show me where the "less than equal to" sign is?

Thanks.
 
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  • #2
If you use LaTeX to make your formulas, you can get [itex]\leq[/itex] with the \leq command.


Are you sure you're not forgetting a hypothesis (compact metric space?) or reversing the implication (the existence of a and b imply equivalence)?

Naively, I would expect there to be a notion of "uniformly equivalent" which is equivalent to your condition.
 
  • #3
The definition of equivalent metric actually doesn't imply that inequality, you have the implication reversed. That inequality is a sufficient, but not necessary condition for two metrics to be equivalent. Two exercises you can try are to prove that it is a sufficient condition, and to verify the following example:

Let [itex]X=\mathbb{R} [/itex] and let [itex]d_1, d_2 [/itex] be the metrics on X defined by [tex] d_1(x,y) = |x-y| [/tex] and [tex] d_2(x,y) = \frac{ |x-y| }{1+ |x-y| } [/tex]. Then [itex] d_1 [/itex] and [itex] d_2[/itex] are equivalent metrics on [itex]\mathbb{R}[/itex] yet do not satisfy the inequality condition.

PS. There is no "less or equal to" sign on your keyboard, but in LaTeX it's code is just \leq .
 
  • #4
oo thanks. I need to study more.
haha, I know it's not on the keyboard. I shall get latex. Thanks.
 

1. What is the definition of equivalent metrics?

Equivalent metrics are two different ways of measuring the same distance or similarity between objects in a mathematical space. They produce the same topology, meaning that they define the same open and closed sets.

2. Can you give an example of equivalent metrics?

One example of equivalent metrics is the Euclidean and Manhattan distances in two-dimensional space. Both measure the distance between two points, but the Euclidean distance takes into account diagonal movements while the Manhattan distance only considers horizontal and vertical movements. Despite this difference, both metrics define the same topology.

3. How can you prove that two metrics are equivalent?

To prove that two metrics are equivalent, we need to show that they satisfy three conditions: they produce the same open and closed sets, they are both continuous, and they are both bounded. These conditions ensure that the two metrics define the same topology and therefore are equivalent.

4. Are all equivalent metrics equal?

No, equivalent metrics are not necessarily equal. They may have different formulas or ways of calculating distance, but they ultimately produce the same topology. This means that while they have the same properties, they may still differ in other aspects.

5. Why are equivalent metrics important?

Equivalent metrics are important because they allow us to define the same mathematical space in different ways. This can be useful in different applications, as some metrics may be more suitable for certain types of data or problems. Additionally, equivalent metrics can help us prove theorems and establish relationships between different mathematical structures.

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