Metric Spaces - Fixed Point Theorem (Apostol, Theorem 4.48)

In summary, Apostol's proof of the Fixed Point Theorem invokes the triangle inequality and proves that for any metric space (S,d) the relationd(p_m, p_n) \le \sum_{k=n}^{m-1} d(p_{k+1}, p_k ) holds.
  • #1
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I need help with the proof of the Fixed Point Theorem for a metric space (S,d) (Apostol Theorem 4.48)

The Fixed Point Theorem and its proof read as follows:View attachment 3901
View attachment 3902
In the above proof Apostol writes:

" ... ... Using the triangle inequality we find for \(\displaystyle m \gt n\),

\(\displaystyle d(p_m, p_n) \le \sum_{k=n}^{m-1} d(p_{k+1}, p_k ) \) ... ... "I am unsure of how (exactly!) Apostol uses the triangle inequality to derive the relation

\(\displaystyle d(p_m, p_n) \le \sum_{k=n}^{m-1} d(p_{k+1}, p_k ) \)

Can someone please help by showing how (formally and rigorously) this is derived?

I presume that Apostol is using the generalised form of the triangle inequality which he describes as the following (see page 13):

\(\displaystyle | x_1 + x_2 + \ ... \ ... \ + x_n | \le |x_1| + |x_2| + \ ... \ ... \ + |x_n|\)

... ... but ... ... I cannot see how he derives a situation where:

\(\displaystyle d(p_m, p_n) = d(p_{n+1}, p_n) + d(p_{n+2}, p_{n+1}) + \ ... \ ... \ + d( p_m, p_{m-1} )\)

so that the triangle inequality can be applied ... ...

Hope that someone can help,

Peter
 
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  • #2
Hi Peter,

The triangle inequality is valid for any metric, not only the absolute value, this is, if $(X,d)$ is a metric space, then $d(x,z)\leq d(x,y)+d(y,z)$ for all $x,y,z\in X$.

Now he applies this as many times as needed.

$d(p_{m},p_{n})\leq d(p_{n},p_{n+1})+d(p_{n+1},p_{m})$
$d(p_{n+1},p_{m})\leq d(p_{n+1},p_{n+2})+d(p_{n+2},p_{m})$

and so he can conclude $d(p_{m},p_{n})\leq \displaystyle\sum_{k=n}^{m-1}d(p_{k+1},p_{k})$
 
  • #3
Fallen Angel said:
Hi Peter,

The triangle inequality is valid for any metric, not only the absolute value, this is, if $(X,d)$ is a metric space, then $d(x,z)\leq d(x,y)+d(y,z)$ for all $x,y,z\in X$.

Now he applies this as many times as needed.

$d(p_{m},p_{n})\leq d(p_{n},p_{n+1})+d(p_{n+1},p_{m})$
$d(p_{n+1},p_{m})\leq d(p_{n+1},p_{n+2})+d(p_{n+2},p_{m})$

and so he can conclude $d(p_{m},p_{n})\leq \displaystyle\sum_{k=n}^{m-1}d(p_{k+1},p_{k})$
Thanks Fallen Angel ...

Appreciate your help ... ...

Peter
 
  • #4
I just want to add that the triangle inequality is an axiom for a metric. Sorry Peter if this sounds redundant.
 
  • #5
Euge said:
I just want to add that the triangle inequality is an axiom for a metric. Sorry Peter if this sounds redundant.

Hi Euge,

No ... that does not sound redundant at all ...

Your post is relevant and most helpful,

Thanks,

Peter
 

1. What is the Metric Spaces - Fixed Point Theorem?

The Metric Spaces - Fixed Point Theorem is a mathematical theorem that states that every nonempty complete metric space with a contraction mapping has a unique fixed point. This means that if there is a function from the metric space to itself that shrinks the distance between any two points, there will always be a specific point that does not move when the function is applied.

2. How is this theorem useful in scientific research?

This theorem is often used in various branches of science, such as physics, engineering, and biology. It provides a powerful tool for proving the existence and uniqueness of solutions to various problems involving dynamical systems and optimization.

3. Can you provide an example of a real-world application of this theorem?

One example is the use of the Metric Spaces - Fixed Point Theorem in the study of population dynamics. In this context, the fixed point represents the equilibrium point of a population, where the birth and death rates are equal. This theorem can be used to prove the existence and stability of this equilibrium point.

4. What are the key assumptions of the Metric Spaces - Fixed Point Theorem?

The key assumptions are that the metric space is complete (meaning that every Cauchy sequence converges to a point in the space) and that there exists a contraction mapping (a function that decreases the distance between any two points in the space).

5. Are there any limitations to this theorem?

Yes, there are some limitations to this theorem. It only applies to complete metric spaces and contraction mappings, so it cannot be used in all mathematical situations. Additionally, the uniqueness of the fixed point is dependent on the choice of the contraction mapping, so different contraction mappings may yield different fixed points.

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