Natural examples of metrics that are not Translation invariant.

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SUMMARY

This discussion focuses on non-translation invariant metrics within the context of metric spaces, specifically targeting beginners in the subject. Two notable examples are presented: the metric on the positive real line defined by d(x,y) = |log(x/y)| and the metric in Euclidean space given by d(x,y) = |x| + |y|, with d(x,x) = 0 for identical points. The conversation emphasizes the importance of understanding these metrics, as they may have applications in both pure and applied mathematics, despite the fact that many metrics exist outside of vector space structures where translation invariance is irrelevant.

PREREQUISITES
  • Basic understanding of metric spaces
  • Familiarity with Euclidean geometry
  • Knowledge of logarithmic functions
  • Concept of distance metrics
NEXT STEPS
  • Research the properties of non-translation invariant metrics
  • Explore applications of metrics in applied mathematics
  • Study the concept of metric spaces without vector space structures
  • Learn about other examples of metrics in mathematical literature
USEFUL FOR

This discussion is beneficial for students of mathematics, particularly those studying metric spaces, as well as educators seeking to illustrate complex concepts with relatable examples.

deluks917
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I am trying to explain metric spaces and finding it hard to come up with simple to understand, interesting examples of metrics that are not translation invariant. The audience is people who are just now studying general metric spaces.
 
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I just looked up "metric spaces" on wikipedia and two examples stood out:
1) Give the positive real line the metric d(x,y) = |log(x/y)|
2) In Euclidean space suppose that instead of considering the direct distance from x to y, we want to travel via 0, then the distance is given by:
d(x,y) = |x| + |y|
unless x=y in which case d(x,x) = 0.

I couldn't say where these appear naturally in pure mathematics, but they seem easy enough to understand and it is certainly not unthinkable that such space may at the very least be used in applied mathematics and therefore that our abstract study of metric spaces should include them.

You should of course also keep in mind that lots of metrics are on spaces without a vector space structure so the term "translation invariant" does not even make sense for general metric spaces.
 

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