Function continuity in metric spaces

In summary, the statements "f is continuous on X" and "\overline{f^{-1}(B)} \subseteq f^{-1}(\overline{B}) for all subsets B \subseteq Y" are equivalent, and can be proven using the theorem that a function between topological spaces is continuous if and only if the inverse image of every closed set is a closed set.
  • #1
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Homework Statement



Let [tex](X,d_X)[/tex] and [tex](Y,d_Y)[/tex] be metric spaces and let [tex]f: X \to Y[/tex].

Homework Equations



Prove that the following statements are equivalent:

1. [tex]f[/tex] is continuous on [tex]X[/tex],
2. [tex]\overline{f^{-1}(B)} \subseteq f^{-1}(\overline{B})[/tex] for all subsets [tex]B \subseteq Y[/tex]

The Attempt at a Solution



I an prove that (1) leads to (2) but don't know how to show (2) leads to (1). Can you give me some hint?
 
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  • #2
A function f: X -> Y between topological spaces is continuous if and only if the inverse image of every closed set in Y is a closed set in X.

Let F be an arbitrary closed set in Y. Then F = cl(F), where cl(F) is the closure of F. Now apply (2) with F in place of B.
 
  • #3
Thanks, I didn't realize I should use this theorem and was trying to prove it using any point x and its neighborhood approach.
 

What is function continuity in metric spaces?

Function continuity in metric spaces is a concept in mathematics that refers to the idea that a function has no sudden jumps or breaks in its values as the input values change. It means that the function's output changes smoothly and gradually as the input changes.

How is function continuity defined in metric spaces?

Function continuity in metric spaces is defined using the epsilon-delta definition. This definition states that a function f is continuous at a point x if for any positive number ε, there exists a positive number δ such that when the distance between x and another point y is less than δ, the distance between f(x) and f(y) is less than ε.

What is the difference between pointwise and uniform continuity?

The main difference between pointwise and uniform continuity is that pointwise continuity is defined at each point individually, while uniform continuity is defined over the entire domain of the function. In other words, pointwise continuity is concerned with the behavior of a function at a specific point, while uniform continuity looks at the overall behavior of the function.

Why is function continuity important?

Function continuity is important because it allows us to make predictions and draw conclusions about the behavior of a function without having to test every single point. It also enables us to use powerful tools such as the Intermediate Value Theorem and the Extreme Value Theorem, which are crucial in many areas of mathematics.

What are some real-life applications of function continuity in metric spaces?

Function continuity in metric spaces has many real-life applications, such as in physics, engineering, and economics. It is used to model and analyze various phenomena, including the flow of fluids, the spread of diseases, and the behavior of financial markets. It is also used in computer science to optimize algorithms and improve data analysis techniques.

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