Discrete metric and continuity equivalence

In summary: Thanks for the advice. I've come up with this idea but I want to check if it is ok:Suppose X is not discrete. Take (Y,d') to be the Y={0,1} and d'=δ distance. By definition of discrete space, if X is not discrete then there exists some x for which for all ε>0, the ball B(x,ε) contains other point y different from x. Define f to be f(x)=0 and f(y)=1 for all y in X with y≠x. If f is continuousYou don't need to derive a contradiction; you can show directly that f as defined is not continuous at x:If \epsilon < d'(0,1)
  • #1
mahler1
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Homework Statement .

Prove that a metric space X is discrete if and only if every function from X to an arbitrary metric space is continuous.

The attempt at a solution.

I didn't have problems to prove the implication discrete metric implies continuity. Let f:(X,δ)→(Y,d) where (Y,d) is an arbitrary metric space. Let V be an open set in (Y,d). Every set in X is open so, in particular, f^-1(V) is an open set. This proves f is continuous.
I don't know how to prove the other statement: if every function from the metric space X to some arbitrary metric space Y is a continuous function, then X is discrete.
 
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  • #2
mahler1 said:
Homework Statement .

Prove that a metric space X is discrete if and only if every function from X to an arbitrary metric space is continuous.

The attempt at a solution.

I didn't have problems to prove the implication discrete metric implies continuity. Let f:(X,δ)→(Y,d) where (Y,d) is an arbitrary metric space. Let V be an open set in (Y,d). Every set in X is open so, in particular, f^-1(V) is an open set. This proves f is continuous.
I don't know how to prove the other statement: if every function from the metric space X to some arbitrary metric space Y is a continuous function, then X is discrete.

Proof by contrapositive: Suppose X is not discrete. Then there exists a function from X to {0,1} which is not continuous.
 
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  • #3
pasmith said:
Proof by contrapositive: Suppose X is not discrete. Then there exists a function from X to {0,1} which is not continuous.

Thanks for the advice. I've come up with this idea but I want to check if it is ok:
Suppose X is not discrete. Take (Y,d') to be the Y={0,1} and d'=δ distance. By definition of discrete space, if X is not discrete then there exists some x for which for all ε>0, the ball B(x,ε) contains other point y different from x. Define f to be f(x)=0 and f(y)=1 for all y in X with y≠x. If f is continuous, in particular, is continuous at the point x. Take ε'=1/2. Then, for all ε, there is some y such that d(x,y)<ε but δ(f(x),f(y))=δ(1,0)=1>1/2=ε'. But this is absurd since f was continuous. Then X must be discrete.

I have a question regarding the concept of discrete space. If the derived set of some metric space is empty, is this equivalent to say that X is discrete? I think it is but I'm not 100% sure. If this equivalence holds, I have a similar proof to the original problem:
Suppose X is not discrete, then there exists x in X'. Take (Y,d')=({0,1},δ) and define f(x)=0 and f(y)=1 for all y in X-{x}. By definition of derived set, there exists a sequence {x_n} in X such that x_n→x when n→∞. The function f is continuous, so f(x_n)→f(x) when n→∞. But f(x_n)=1≠0=f(x), which is absurd. It follows that X must be discrete.
 
  • #4
mahler1 said:
Thanks for the advice. I've come up with this idea but I want to check if it is ok:
Suppose X is not discrete. Take (Y,d') to be the Y={0,1} and d'=δ distance. By definition of discrete space, if X is not discrete then there exists some x for which for all ε>0, the ball B(x,ε) contains other point y different from x. Define f to be f(x)=0 and f(y)=1 for all y in X with y≠x. If f is continuous, in particular, is continuous at the point x. Take ε'=1/2. Then, for all ε, there is some y such that d(x,y)<ε but δ(f(x),f(y))=δ(1,0)=1>1/2=ε'. But this is absurd since f was continuous. Then X must be discrete.

I have a question regarding the concept of discrete space. If the derived set of some metric space is empty, is this equivalent to say that X is discrete? I think it is but I'm not 100% sure. If this equivalence holds, I have a similar proof to the original problem:
Suppose X is not discrete, then there exists x in X'. Take (Y,d')=({0,1},δ) and define f(x)=0 and f(y)=1 for all y in X-{x}. By definition of derived set, there exists a sequence {x_n} in X such that x_n→x when n→∞. The function f is continuous, so f(x_n)→f(x) when n→∞. But f(x_n)=1≠0=f(x), which is absurd. It follows that X must be discrete.

That sounds fine. Both of those proofs are really the same. Why are you not 100% sure that the set of all limit points of a metric space is empty if and only if the space is discrete? You should be able to prove that. And for your first proof, since you have 'if and only if' you still have to prove any function on a discrete space is continuous. But that should be pretty easy. Actually, I see you've already gotten that part. Nevermind.
 
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  • #5
mahler1 said:
Thanks for the advice. I've come up with this idea but I want to check if it is ok:
Suppose X is not discrete. Take (Y,d') to be the Y={0,1} and d'=δ distance. By definition of discrete space, if X is not discrete then there exists some x for which for all ε>0, the ball B(x,ε) contains other point y different from x. Define f to be f(x)=0 and f(y)=1 for all y in X with y≠x. If f is continuous

You don't need to derive a contradiction; you can show directly that f as defined is not continuous at x:

If [itex]\epsilon < d'(0,1)[/itex] then for every [itex]\delta > 0[/itex] there exists [itex]y \in B(x,\delta)[/itex] with [itex]d'(f(x),d(y)) > \epsilon[/itex] and thus [itex]f[/itex] is not continuous at [itex]x[/itex].

That's sufficient to complete the proof: the object is to show that if X is not discrete then there exists a metric space Y such that there exists a function from X to Y which is not continuous, which is equivalent to showing that if every function from X to an arbitrary metric space is continuous then X is discrete.

A direct proof would probably start with the observations that if every function from X to an arbitrary metric space is continuous then every function from X to {0,1} is continuous, and that every such function can be written as
[tex]
f : x \mapsto \left\{\begin{array}{rc}
0 & \mbox{ if } x \in U \\
1 & \mbox{ otherwise}
\end{array}
\right.[/tex]
for some [itex]U \subset X[/itex].
 
  • #6
You're right. I've messed up with logic. We've shown that the contrapositive is true, so the statement is true.
 

1. What is the discrete metric?

The discrete metric is a mathematical concept used to measure the distance between two points in a discrete set. It assigns a value of 1 to any two distinct points in the set, indicating that they are completely separated from each other.

2. How is the discrete metric different from other metrics?

The discrete metric is different from other metrics, such as the Euclidean metric, because it only considers the distance between two points as either 0 or 1, depending on whether they are the same point or different points. Other metrics may assign fractional values to represent the distance between points.

3. What is the significance of the discrete metric in mathematics?

The discrete metric is important in mathematics because it allows us to define and study discrete spaces, which are sets with a finite or countably infinite number of elements. It also has applications in fields such as computer science and topology.

4. What is the relationship between discrete metric and continuity?

The discrete metric and continuity are equivalent concepts. This means that a function is continuous if and only if the distance between the function's output for any two points in the domain is always less than or equal to the distance between the two points in the discrete metric. In other words, a function is continuous if and only if it preserves the discrete structure of its domain.

5. How can the discrete metric be used in real-world applications?

The discrete metric has various real-world applications, such as in computer science for measuring the similarity between two discrete objects or in data analysis for clustering discrete data. It can also be used in analyzing networks and social structures, as well as in the study of fractals and chaos theory.

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