Uniformly continuous functions

In summary, the conversation discusses the concept of uniformly continuous functions in metric spaces, and how they map Cauchy sequences to Cauchy sequences. It also provides an example of a uniformly continuous function, f(x) = 1/x, that is defined on [1, +infinity) but not on (0, 1) due to a failure in the condition for epsilon. The speaker suggests using more precise definitions and reasoning in order to make a valid argument.
  • #1
Bachelier
376
0
Question

Let (S; d) and (T;D) be metric spaces. A function f : X -> Y is said to be
uniformly continuous if ( for all epsilons > 0)(there exists a sigma > 0) such that d(x; y) < sigma => D(f(x); f(y)) < epsilon
a. Show that a uniformly continuous function maps Cauchy sequences to Cauchy seq.
b. Show that f(x) = 1/x is uniformly continuous on [1 , + infinity) but not on (0 , 1).

Answer:

a. let Sn be Cauchy.
then ( for all epsilons > 0)(there exists a sigma > 0) such that d(Sn; Sn) < sigma => D(f(Sn); f(Sn)) < epsilon
therefore f(Sn) is Cauchy since it is bounded (inside the ball with radius epsilon).

b. reason: D(f(x),f(y)) < epsilon fails on (0, 1) because
let x= 1/10^100 and y= 1/2, both are in (0,1) yet D(10^100,2) >>>>>>> epsilon

what do you guys think?

thanks
 
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  • #2
Bachelier said:
Question

Let (S; d) and (T;D) be metric spaces. A function f : X -> Y is said to be
uniformly continuous if ( for all epsilons > 0)(there exists a sigma > 0) such that d(x; y) < sigma => D(f(x); f(y)) < epsilon
a. Show that a uniformly continuous function maps Cauchy sequences to Cauchy seq.
b. Show that f(x) = 1/x is uniformly continuous on [1 , + infinity) but not on (0 , 1).

Answer:

a. let Sn be Cauchy.
then ( for all epsilons > 0)(there exists a sigma > 0) such that d(Sn; Sn) < sigma => D(f(Sn); f(Sn)) < epsilon
therefore f(Sn) is Cauchy since it is bounded (inside the ball with radius epsilon).

b. reason: D(f(x),f(y)) < epsilon fails on (0, 1) because
let x= 1/10^100 and y= 1/2, both are in (0,1) yet D(10^100,2) >>>>>>> epsilon

what do you guys think?

thanks

What I think is that you need to write your general ideas up much more carefully using the appropriate definitions to make a genuine valid argument.
 

1. What is a uniformly continuous function?

A uniformly continuous function is a type of mathematical function that maintains a consistent rate of change over its entire domain. This means that for any two points on the graph of the function, the vertical distance between them will always be proportional to the horizontal distance between them. In other words, the function does not have any sudden changes or breaks in its behavior.

2. How is uniform continuity different from regular continuity?

Uniform continuity is a stronger form of continuity than regular continuity. A function is considered uniformly continuous if the distance between the output values of any two input values can be made arbitrarily small by choosing the input values close enough together. Regular continuity only requires that the function is continuous at each individual point in its domain.

3. What are some examples of uniformly continuous functions?

Some examples of uniformly continuous functions include linear functions, polynomial functions, and trigonometric functions such as sine and cosine. These functions have a consistent rate of change and do not have any sudden changes or breaks in their behavior.

4. How is uniform continuity related to differentiability?

A function that is uniformly continuous is also differentiable at all points in its domain. This is because the definition of uniform continuity requires that the function does not have any sudden changes or breaks in its behavior, which is a necessary condition for a function to be differentiable.

5. Can a non-uniformly continuous function be continuous?

Yes, a function can be continuous but not uniformly continuous. For example, the function f(x) = 1/x is continuous but not uniformly continuous on the interval (0,1). This is because the function has a vertical asymptote at x = 0, meaning that the distance between the output values of any two input values can become arbitrarily large as the input values get closer to 0.

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