Is this a Metric Space in R x R?

In summary, the conversation discusses whether a given function is a metric space in R x R (Cartesian product). The function is defined as D[(x1,y1),(x2,y2)] = min( abs(x1-x2), abs(y1-y2) ), and there are four properties that need to be confirmed for it to be a metric space. The conversation also mentions the importance of the triangle inequality in proving the function to be a metric, and suggests using counterexamples to aid in the proof. However, it is ultimately determined that the given function is not a metric as it does not satisfy the property of positive definiteness.
  • #1
TimNguyen
80
0
Hi.

I was trying to figure out if the following is a metric space in R x R (Cartesian product).

D[(x1,y1),(x2,y2)] = min( abs(x1-x2), abs(y1-y2) )

I know there are four properties to confirm that the following is a metric space but I'm having trouble with the "triangle inequality" for the distance function.

So, I have D[(x1,z1),(x2,z2)] should be less than or equal to D[(x1,y1),(x2,y2)] + D[(y1,z1),(y2,z2)].

D[(x1,z1),(x2,z2)] = min( abs(x1-x2), abs(z1-z2) ) and basically I'm stuck on the next step. How do I configure it such that I could put it in the form of D[(x1,y1),(x2,y2)] + D[(y1,z1),(y2,z2)]?
 
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  • #2
Anybody could help...?
 
  • #3
This isn't my area of expertise, but here's a suggestion: Try to reduce your problem to triangle inequalities involving distances in [itex]\mathbb{R}[/itex]. First let [itex]|x_1-x_2| \leq |y_1-y_2| \leq |z_1-z_2|[/itex]. In that case we have:

[itex]d[(x_1,y_1),(x_2,y_2)]=|x_1-x_2|[/itex]
[itex]d[(x_1,z_1),(x_2,z_2)]=|x_1-x_2|[/itex]
[itex]d[(y_1,z_1),(y_2,z_2)]=|y_1-y_2|[/itex]

At this point you can set up the triangle inequalities for the absolute values from the right hand sides, and then appropriately substitute the metric functions from the left hand sides.
 
  • #4
If you're having trouble proving something, try looking for a counterexample! Even if you can't find one, the search might help you figure out the missing step of your proof.
 
  • #5
One thing the triangle inequality says is that if you have a right-angled triangle, then the "length of the hypoteneuse" (by length I mean D(x,y), where x and y are the endpoints of the hypoteneuse) is less than or equal to the sum of the lengths of the other two sides of the triangle. Is this the case for your D?
 
  • #6
I have an analysis book in which a distance function like the one you gave, only with max instead of min, is a metric, if that helps
.
 
  • #7
It's NOT a metric, it's not positive definite. For if x1=x2 and y1 > y2, then D[(x1,y1),(x2,y2)] = 0 but (x1,y1) does not equal (x2,y2).
 
Last edited:

1. What is a metric space?

A metric space is a mathematical concept that describes a set of objects along with a mathematical function called a metric, which measures the distance between any two objects in the set. This allows for the study of properties such as convergence, continuity, and completeness within the set.

2. How is a metric space different from a topological space?

While a metric space uses a specific function to measure distance, a topological space uses a collection of sets called open sets to define the properties of the space. Open sets allow for the study of concepts such as connectedness, compactness, and separation within the space.

3. What is the importance of the concept of convergence in metric spaces?

Convergence is a key concept in metric spaces as it allows for the study of limits and continuity of functions defined on the space. It also plays a crucial role in the study of sequences and series within the space.

4. Can you give an example of a metric space?

One example of a metric space is the set of real numbers with the standard Euclidean metric. In this space, the metric function is defined as the absolute value of the difference between any two real numbers, which gives the distance between them. This space is commonly used in calculus and analysis.

5. How is the concept of topology used in real-world applications?

Topology has many practical applications, including in fields such as computer science, physics, and engineering. It can be used to analyze networks, study the behavior of physical systems, and even in data analysis and machine learning. In addition, topology also has applications in geometry, with the study of geometric shapes and their properties.

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