HELP real analysis question: continuity and compactness

In summary: Proposition 1.126?In summary, Fredrik has found that if K is compact, then there is a point q0 ∈ K, such that dist(p, K) = d(p, q0). This implies that f is continuous on K. This is useful because it allows Fredrik to prove that if f is continuous on K, then it is also continuous on X.
  • #1
amanda_ou812
48
1
HELP! real analysis question: continuity and compactness

Homework Statement


Let (X,d) be a metric space, fix p ∈ X and define f : X → R by f (x) = d(p, x). Prove that f is continuous. Use this fact to give another proof of Proposition 1.126.

Proposition 1.126. Let (X, d) be a metric space, let K ⊆ X and let p ∈ X. If K is compact, then there is a point q0 ∈ K, such that dist(p, K) = d(p, q0).


Homework Equations





The Attempt at a Solution


I think I know how to do the first part of the question but I don't know how to do the second part.

part 1
given ε>0 let delta = ε, then when d(p, x)< delta we have abs( f(p) - f(x)) = abs( d(p, p) - d(p, x)) = abs (0 - d(p, x)) = d(p, x) < delta = ε.

part 2
I am not sure how to do this. Suppose K is compact and that f: K-> R is defined by f(q0) = d(p, q0). Well f continuous implies...I am not sure where to go from here...
 
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  • #2


Define f:X→ℝ by f(x)=d(x,p) for all x. f is continuous and K is compact. What does that tell you about the range f(K)?
 
  • #3


Hi amanda, about the first part, you only show that f is continuous on p. If you want to show that f is continuous on X, then you have to show that for any [itex]x_0\in X,[/itex] for every [itex]\epsilon>0,[/itex] there exists [itex]\delta>0[/itex] such that [itex]d(x,x_0)<\delta[/itex] implies [itex]|f(x)-f(x_0)|<\epsilon[/itex]. Or maybe you only want to show that f is continuous on p?
 
  • #4


Good point canis89. I didn't even notice that. We need f to be continuous everywhere (or at least on all of K) for my approach to part 2 to work.
 
  • #5


Ah, I see your point. Given e>0 let delta = e the for x-0 contained in X we have d(x, x-0)< delta implies abs (f(x) - f(x-0)) = abs ( d(p, x) - d(p, x-0)) <= abs (d(x, x-0)) [reverse triangle inequality] < delta = e.

Fredrik - f(K) is compact
 
  • #6


amanda_ou812 said:
Ah, I see your point. Given e>0 let delta = e the for x-0 contained in X we have d(x, x-0)< delta implies abs (f(x) - f(x-0)) = abs ( d(p, x) - d(p, x-0)) <= abs (d(x, x-0)) [reverse triangle inequality] < delta = e.
You seem to have the right idea, but I don't know what you mean by x-0 (or - or 0). The proof should go like this:

We're going to prove that f is continuous. This is equivalent to proving that f is continuous at x for all x in X. Let x be an arbitrary member of X. Let ε>0 be arbitrary. Choose δ=ε. For all y in X such that d(x,y)<δ, we have |f(y)-f(x)|= ... <ε.


amanda_ou812 said:
Fredrik - f(K) is compact
That's what I had in mind. Now that you just need to figure out how to use that.
 
  • #7


I used x-0 to mean x-nought as an arbitrary point in X. If I use x and y's doesn't that prove its uniformly continuous? (of course, that would mean continuous as well)

f(K) compact implies f(K) is a closed and bounded subset of R which implies f(K) has a sup and inf. When p-nought is contained in R, the abs((p-nought - f(K)) = inf { abs(p-nought - q-nought) : q-nought is contained in f(K)} [remember f(K) = d(p, K)] so there exists a q-nought contained in f(K) and p-nought contained in R s.t. dist(p-nought, f(K)) = dist (p-nought, q-nought). That seems to be what 1.126 says except its for the images of K but would it be ok to take f(K) = A where A is an arbitrary subset of a metric space (X, d)? Then would that statement prove 1.126?
 
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  • #8


amanda_ou812 said:
I used x-0 to mean x-nought as an arbitrary point in X.
I see. I recommend that you use either vBulletin's sub tags, or the latex code x_0. In other words, you type either [noparse]x0[/noparse] or
Code:
[itex]x_0[/itex]
to get x0 or [itex]x_0[/itex] respectively.

amanda_ou812 said:
If I use x and y's doesn't that prove its uniformly continuous? (of course, that would mean continuous as well)
What symbols we use certainly doesn't matter, but the fact that the delta you found doesn't depend on the point under consideration means that this f is uniformly continuous.

amanda_ou812 said:
f(K) compact implies f(K) is a closed and bounded subset of R which implies f(K) has a sup and inf.
Every bounded subset of ℝ has a supremum and an infimum.

amanda_ou812 said:
When p-nought is contained in R, the d(p-nought, f(K)) = inf {d d(p-nought, q-nought)) : q-nought is contained in f(K)}
You seem to be saying that for all t in ℝ, d(t,f(K))=inf{|t-s| : s is in f(K)}? This correct, but we're not interested in d(t,f(K)). We only care about d(x,K). You also shouldn't have used the variable q0, since it was already being used for something else.

amanda_ou812 said:
[remember f(K) = d(p, K)] ...
f(K) is a set of non-negative real numbers. d(p,K) is a non-negative real number.
 
  • #9


So, since there exists a t contained in R so that d(t, f(K)) = inf { |t-s|: s in contained in f(K)} there is a number km such that for any k contained in K, f(km) = inf{f(K) : k in K} and f(km) <= f(k). But, f(km) = d(t, f(K))...I don't think I am understanding the problem. So, I defined a function f with the based on part 1 and I know that K is compact. I am not understanding what I need to show to prove that there is a point q0 ∈ K, such that dist(p, K) = d(p, q0). I mean, 1,126 just seems intuitive to me. The questions for this class are always so difficult for me to do.
 
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  • #10


amanda_ou812 said:
there exists a t contained in R so that d(t, f(K)) = inf { |t-s|: s in contained in f(K)}
Hm, I suppose you could say that, since every real number t has that property (by definition of d(t,f(K))). But it's a weird thing to say, like saying that there's an integer that's also a real number.

amanda_ou812 said:
there is a number km such that for any k contained in K, f(km) = inf{f(K) : k in K} and f(km) <= f(k).
This statement is flawed in several ways. You're saying that there's a [itex]k_m\in\mathbb R[/itex] such that for all [itex]k\in K[/itex], we have [itex]f(k_m)=\inf\{f(K):k\in K\}[/itex] and [itex]f(k_m)\leq f(k)[/itex]. What is [itex]\{f(K):k\in K\}[/itex] supposed to mean? It should be "the set of all f(K) such that k is a member of K". That would be the set {f(K)}, i.e. the set that has f(K) as its only member. Maybe you meant [itex]\{f(k')|k'\in K\}[/itex]. But this is just [itex]f(K)[/itex]. Either way, the statement is of the form "there's a [itex]k_m\in\mathbb R[/itex] such that for all [itex]k\in K[/itex], we have [itex]f(k_m)=[/itex]<something that that has nothing to do with K>". And I haven't even mentioned the biggest problem with that statement yet: [itex]k_m[/itex] isn't a member of the domain of f.

amanda_ou812 said:
But, f(km) = d(t, f(K))...
All you have said about t so far is that it's a real number that has a property that all real numbers have. Since f(K)≠ℝ, it wouldn't be hard to find a t that's not at distance [itex]f(k_m)[/itex] from f(K)?

What you need to do is to figure out how to use the fact that f(K) is closed and bounded.
 
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1. What is continuity in real analysis?

In real analysis, continuity is a fundamental concept that describes the behavior of a function at a particular point. A function is said to be continuous at a point if its value at that point is equal to the limit of its values as the input approaches that point.

2. How is continuity different from differentiability?

Continuity and differentiability are related but distinct concepts in real analysis. While a continuous function is always differentiable, the converse is not necessarily true. A function is differentiable at a point if it has a well-defined derivative at that point, while continuity only requires the function to have a value at that point.

3. What is the definition of a compact set?

A compact set is a subset of a metric space that is both closed and bounded. In other words, a compact set contains all of its limit points and is finite in size. This definition can be extended to general topological spaces as well.

4. How is compactness related to continuity?

In real analysis, continuity and compactness are closely related. A continuous function on a compact set will attain a maximum and minimum value, while a continuous function on a non-compact set may not. Additionally, the image of a compact set under a continuous function is also a compact set.

5. What are some practical applications of continuity and compactness in real analysis?

Continuity and compactness have many practical applications in various fields of mathematics, such as optimization, differential equations, and functional analysis. In particular, these concepts are used to prove important theorems, such as the extreme value theorem and the Heine-Borel theorem, which have applications in physics, economics, and engineering.

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