Cartesian Product of Metric Spaces

In summary, the conversation discusses forming a metric space (X x Y, τp) for metric spaces (X, ρ) and (Y, σ), where τp is given by a specific equation. The positivity and symmetry of τp are easily verified, but verifying the triangle inequality is more difficult. Suggestions are given, including using the proof for the Euclidean metric on R² as a guide. Eventually, it is discovered that the Minkowski inequality can be applied to solve the problem.
  • #1
MKR
2
0
Hello everyone.

I read in a book that for metric spaces [itex](X, \rho), (Y, \sigma)[/itex] we can form the metric space [itex] (X \times Y, \tau_p) [/itex], for [itex]1 \leq p < \infty[/itex] where [itex]\tau_p[/itex] is given by:

[tex]\tau_p((x_1,y_1), (x_2,y_2)) = (\rho(x_1,x_2)^p + \sigma(y_1,y_2)^p)^\frac{1}{p}[/tex]

I can easily verify the positivity and symmetry of [itex]\tau_p[/itex] but verifying the triangle innequality is a bit tricky. Any suggestions? Here is what I've tried with no luck:

[tex](\rho(x_1,x_2)^p + \sigma(y_1,y_2)^p)^\frac{1}{p} \leq \rho(x_1,x_2) + \sigma(y_1,y_2) [/tex]

since rho and sigma are metrics they each satisfy the triangle innequality in their respective spaces and so we have for any (x3,y3) in X*Y,

RHS [tex] \leq \rho(x_1,x_3) + \rho (x_3,x_2) + \sigma(y_1,y_3) + \sigma(y_3,y_2) [/tex]

and I'm stuck. Thanks in advance for your help.
 
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  • #2
How did you prove the Euclidean metric on R² satisfies the triangle equality? Wouldn't the same proof work here?
 
  • #3
Thanks Hurkyl. It was even easier than that since I had already proved the Minkowski inequality, so I just had to recognize that I could apply that here. However, It was your comment that led me to recognize this. Thank You!
 
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FAQ: Cartesian Product of Metric Spaces

What is the definition of a Cartesian Product of Metric Spaces?

The Cartesian Product of Metric Spaces is a mathematical concept that combines two or more metric spaces to form a new metric space. It is defined as the set of all ordered pairs of elements from each of the individual metric spaces, with a new metric defined on the product space.

How is the Cartesian Product of Metric Spaces different from the Cartesian Product of sets?

While the Cartesian Product of sets simply combines two sets to form a new set, the Cartesian Product of Metric Spaces takes into account the metric structure of each space. This means that the new product space has a defined distance metric, allowing for the measurement of distances between elements from different spaces.

What is the importance of the Cartesian Product of Metric Spaces in mathematics?

The Cartesian Product of Metric Spaces is an important concept in mathematics because it allows for the creation of new metric spaces from existing ones. This is useful in many areas of mathematics, such as topology and analysis, where the properties of the new product space can be studied and used to solve problems.

How is the metric defined on the Cartesian Product of Metric Spaces?

The metric on the Cartesian Product of Metric Spaces is defined as the maximum of the individual metrics from each space. This means that the distance between two points in the product space is equal to the greatest distance between their respective components in each individual space.

Can the Cartesian Product of Metric Spaces be extended to more than two spaces?

Yes, the Cartesian Product of Metric Spaces can be extended to any finite number of spaces. This means that the product space will consist of ordered n-tuples of elements from each space, with a metric defined in a similar manner as for the two-space case.

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