Proving a Fixed Point Theorem for Shrinking Maps on Compact Spaces

In summary: The sequence does not live in ##A##.Yes, I clearly oversped on this one. Let me read more carefully.Let ##(X,d)## be a metric space and let ##f:X\to X## be such that$$d(f(x),f(y))<d(x,y),\quad x\ne y.$$Theorem. Assume that for some ##x_0## a sequence ##x_{n+1}=f(x_n)## contains a convergent subsequence: ##x_{n_k}\to x_*##. Then$$f(x_*)=
  • #1
facenian
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TL;DR Summary
A problem in Munkres' topology book ##\S##-7(b) Page 183
Show that if ##f## is a shrinking map ##d(f(x),f(y)) < d(x,y)## and ##X## is compact, then ##f## has a unique fixed point.
Hint. Let ##A_n=f^n(X)## and ##A=\cap A_n##. Given ##x\in A##, choose ##x_n## so that ##x=f^{n+1}(x_n)##. If ##a## is the limit of some subsequence of the sequence ##y_n=f^n(x_n)##, show that ##a\in A## and ##f(a)=x##. Conlude that ##A=f(A)##, so that ##diam\,A=0##.

Solution: I can prove all except that ##a\in A##, i.e., I had to assume it to prove that ##A=f(A)## and ##diam\,A=0##.
Any help will be welcome.
 
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  • #2
I will not bother working with a subsequence, and I'll take the full sequence. The easy modification to the general case is left to you.

You should show that ##a \in A_m## for all ##m \geq 1##. Note that we have a descending chain ##A_1 \supseteq A_2 \supseteq \dots##. Fix ##m \geq 1##.

Observe that ##y_n \in A_n \subseteq A_m## for ##n \geq m##. Thus

$$a = \lim_{n \to \infty, n \geq m} y_n \in A_m$$ because ##A_m## is closed (limits of sequences in a set remain in the closure of the set).

Since ##m \geq 1## is arbitrary, ##a \in \bigcap_{m=1}^\infty A_m=A##.
 
  • #3
Math_QED said:
I will not bother working with a subsequence, and I'll take the full sequence. The easy modification to the general case is left to you.

You should show that ##a \in A_m## for all ##m \geq 1##. Note that we have a descending chain ##A_1 \supseteq A_2 \supseteq \dots##. Fix ##m \geq 1##.

Observe that ##y_n \in A_n \subseteq A_m## for ##n \geq m##. Thus

$$a = \lim_{n \to \infty, n \geq m} y_n \in A_m$$ because ##A_m## is closed (limits of sequences in a set remain in the closure of the set).

Since ##m \geq 1## is arbitrary, ##a \in \bigcap_{m=1}^\infty A_m=A##.
Many thanks for your response, however, I believe that it is not correct. Let us just work with the sequence as you said. Your answer would be correct if ##y_n\in A## then ##a## would be in ##\overline{A}=A##. The problem is that ##y_n\not\in A## in general because we cannot assume that ##y_n\in A_m## for ##m>n##, so ##a## is a limit point for the elements ##\{y_k:k\in Z^+\}## but not for elements in ##A##.
 
  • #4
facenian said:
Many thanks for your response, however, I believe that it is not correct. Let us just work with the sequence as you said. Your answer would be correct if ##y_n\in A## then ##a## would be in ##\overline{A}=A##. The problem is that ##y_n\not\in A## in general because we cannot assume that ##y_n\in A_m## for ##m>n##, so ##a## is a limit point for the elements ##\{y_k:k\in Z^+\}## but not for elements in ##A##.

I never claim that ##y_n\in A##. Reread my answer more carefully please.

I don't show directly that ##a\in A##, I rather show that ##a \in A_m## for every ##m## and this follows because the sequence lives in ##A_m## for sufficiently large indices. Hence the limit lives in ##\overline{A_m}=A_m##.

You can do this for every ##m## and then you can conclude that ##a \in A##.

Could you let me know if this helped?
 
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  • #5
Math_QED said:
I never claim that ##y_n\in A##. Reread my answer more carefully please.

I don't show directly that ##a\in A##, I rather show that ##a \in A_m## for every ##m## and this follows because the sequence lives in ##A_m## for sufficiently large indices. Hence the limit lives in ##\overline{A_m}=A_m##.

You can do this for every ##m## and then you can conclude that ##a \in A##.
You are right! I read it and interpreted it as I tried to solve it before. Thank you.
 
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  • #6
Each An is compact and therefore closed ( in a metric space) and thus so is A as the intersection, and complete ( compact subset/subspace of metric is complete).A Cauchy sequence in A must therefore converge to a point in A.
 
  • #7
WWGD said:
Each An is compact and therefore closed ( in a metric space) and thus so is A as the intersection, and complete ( compact subset/subspace of metric is complete).A Cauchy sequence in A must therefore converge to a point in A.

The sequence does not live in ##A##.
 
  • #8
Yes, I clearly oversped on this one. Let me read more carefully.
 
  • #9
Let ##(X,d)## be a metric space and let ##f:X\to X## be such that
$$d(f(x),f(y))<d(x,y),\quad x\ne y.$$

Theorem. Assume that for some ##x_0## a sequence ##x_{n+1}=f(x_n)## contains a convergent subsequence: ##x_{n_k}\to x_*##. Then ##f(x_*)=x_*##
 
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FAQ: Proving a Fixed Point Theorem for Shrinking Maps on Compact Spaces

What is a fixed point theorem?

A fixed point theorem is a mathematical theorem that states the existence of a point in a given space that remains unchanged when a certain transformation is applied to it.

What are shrinking maps?

Shrinking maps are a type of transformation that decrease the distance between points in a given space. In other words, they "shrink" the space.

What is a compact space?

A compact space is a mathematical term used to describe a topological space that is both closed and bounded. This means that every sequence within the space has a convergent subsequence.

How is a fixed point theorem proven for shrinking maps on compact spaces?

To prove a fixed point theorem for shrinking maps on compact spaces, one must show that the shrinking map satisfies certain conditions, such as being continuous and having a unique fixed point. This can be done using mathematical methods such as the Brouwer fixed point theorem or the Kakutani fixed point theorem.

What is the significance of proving a fixed point theorem for shrinking maps on compact spaces?

Proving a fixed point theorem for shrinking maps on compact spaces has important implications in various fields of mathematics, such as dynamical systems and optimization. It also has practical applications in areas such as economics, physics, and computer science.

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