Convergence of {fn} wrt to C(X) metric

In summary, the theorem states that if {fn} converges to f wrt to the metric of C(X), then the uniform convergence is implied.
  • #1
camillio
74
2
Let C(X) be the set of continuous complex-valued bounded functions with domain X. Let {fn} be a sequence of functions on C. We say, that fn converges to f wrt to the metric of C(X) iff fn converges to f uniformly.

By definition of the uniform convergence, for any ε>0 there exists integer N s.t. n ≥ N implies |fn(x) - f(x)| ≤ ε for every x in X. Hence by the definition of supremum norm, the inequality is equivalent to sup(fn(x) - f(x)) ≤ ε.

I conclude, that:
1) the uniform convergence imposes that for every ε>0, there exists N from which on the functions fn and f are within this ε on whole X. Hence it always implies convergence wrt the metric of C(X), since exactly this ε can be used as the supremum of the distance fn and f.
2) What about the converse? I think, that if {fn} converges to f wrt to the metric of C(X), then the existence of such ε>0, being the supremum of the distance on whole X, implies the uniform convergence, as this ε can be used in its definition and the existence of N is guaranteed.

Am I right or not?
 
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  • #2
Is the question if it's true that ##f_n\to f## uniformly if and only if ##f_n\to f## with respect to the metric defined from the norm defined by ##\|f\|=\sup_{x\in X}|f(x)|## for all f in C(X)? If that's what you're asking, the answer is yes. This is how I would start a proof of that theorem:

Let ##\varepsilon>0## be arbitrary.

Suppose that ##f_n\to f## with respect to the norm (metric). Choose N such that for all n≥N,
$$\|f_n-f\|<\varepsilon.$$ This choice ensures that for all n≥N and all x in X,
$$|f_n(x)-f(x)| \dots $$
So ##f_n\to f## uniformly.

Can you fill in the details (at the dots)? The proof of the converse is very similar.
 
  • #3
Thank you, Frederic. This was exactly what I was thinking about, and, roughly said, your answer follows the idea provided by me in (2). The goal was to ensure that I'm not missing something.
 

FAQ: Convergence of {fn} wrt to C(X) metric

1. What is the definition of "Convergence of {fn} wrt to C(X) metric"?

The convergence of {fn} wrt to C(X) metric refers to a type of convergence in functional analysis, where a sequence of functions {fn} converges to a limit function f in the space of continuous functions on a metric space X. This is known as the C(X) metric because it is defined using the supremum norm on X.

2. How is the C(X) metric used in analyzing convergence of functions?

The C(X) metric is used to measure the distance between a sequence of functions {fn} and a limit function f. It is defined as the supremum of the absolute difference between f and fn over the entire space X. This metric allows us to determine if a sequence of functions is converging to a limit function and how quickly it is converging.

3. What is the significance of studying convergence of {fn} wrt to C(X) metric?

Studying the convergence of {fn} wrt to C(X) metric is important in functional analysis and other areas of mathematics because it allows us to understand the behavior of functions as they approach a limit. This can help us make predictions about the behavior of real-world systems or make approximations in complex calculations.

4. How does the C(X) metric differ from other metrics used in functional analysis?

The C(X) metric is just one of many metrics used in functional analysis to measure the convergence of functions. However, it is unique in that it is defined using the supremum norm, which captures the maximum difference between two functions. Other metrics, such as the Lp norm, measure the average difference between functions over a specific region.

5. Can the C(X) metric be used to analyze the convergence of all types of functions?

Yes, the C(X) metric can be used to analyze the convergence of all types of functions, as long as they are continuous on the metric space X. This includes both real-valued and complex-valued functions. However, it may not be the most suitable metric for every type of function, as some may converge more quickly under a different metric.

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