Metric Spaces Homework: Showing Cauchy Sequences

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In summary, the conversation discusses Cauchy sequences and completeness in different metrics. It is proven that the sequence x_n = n is not Cauchy in the standard metric, but is Cauchy in the other metric. It is also discussed that if a metric space is complete, every Cauchy sequence must converge to a limit in the space, but this is not the case for the given sequence.
  • #1
Ted123
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Homework Statement



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Homework Equations





The Attempt at a Solution



I've done the first 3 parts. I've come to the bit on Cauchy sequences at the end. How do I show [itex]x_n = n[/itex] is/isn't a Cauchy sequence in the 2 metrics?

[itex](x_n)[/itex] is a Cauchy sequence in a metric space [itex](X,d)[/itex] if for any [itex]\varepsilon >0[/itex] there exists [itex]N\in \mathbb{N}[/itex] such that if [itex]m,n > N[/itex] then [itex]d(x_m , x_n ) < \varepsilon[/itex].

The metric space [itex](X,d)[/itex] is complete if every Cauchy sequence in [itex](X,d)[/itex] converges to a limit in [itex]X[/itex].
 
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  • #2
So let's prove that it isn't a Cauchy sequence in the standard metric.

So, we need to find an epsilon (let's take [itex]\epsilon=1[/itex] for a moment), such that for all N, there exists n,m>N such that

[tex]d(x_n,x_m)\geq 1[/tex]

So we must find n,m>N such that

[tex]|n-m|\geq 1[/tex]

Can you find such a n and m??
 
  • #3
Well, let ε be some number in <0, 1>. Does there exist some positive integer N such that for all m, n >= N you have |xm - xn| < ε?

Edit: sorry, micromass seems to have answered first.
 
  • #4
micromass said:
So let's prove that it isn't a Cauchy sequence in the standard metric.

So, we need to find an epsilon (let's take [itex]\epsilon=1[/itex] for a moment), such that for all N, there exists n,m>N such that

[tex]d(x_n,x_m)\geq 1[/tex]

So we must find n,m>N such that

[tex]|n-m|\geq 1[/tex]

Can you find such a n and m??

Setting [itex]m=N+1[/itex] and [itex]n=N+2[/itex] we have that [itex]m,n > N[/itex] and [tex]|m-n|=|N+1-(N+2)|=|1-2|=1 \geqslant 1\;,\;\text{for all}\;N\in \mathbb{N}[/tex]
 
  • #5
Good! So that proves that it isn't a Cauchy sequence.

Now, to prove that it is a Cauchy sequence in the other metric, you must make

[tex]|\tan^{-1}(n)-\tan^{-1}(m)|[/tex]

smaller than [itex]\varepsilon[/itex]
 
  • #6
micromass said:
Good! So that proves that it isn't a Cauchy sequence.

Now, to prove that it is a Cauchy sequence in the other metric, you must make

[tex]|\tan^{-1}(n)-\tan^{-1}(m)|[/tex]

smaller than [itex]\varepsilon[/itex]

How do I make [itex]|\tan^{-1}(m) - \tan^{-1}(n)|<\varepsilon[/itex] ? I'm guessing that the fact given in the question that [itex]d(x,y)< \pi[/itex] might help?

However, for the last part on whether [itex](\mathbb{R} ,d)[/itex] is complete, can I say: if it is complete then every Cauchy sequence in [itex](\mathbb{R} ,d)[/itex] must converge to a limit in [itex]\mathbb{R}[/itex].

Suppose the Cauchy sequence [itex]x_n=n[/itex] converges in [itex](\mathbb{R} ,d)[/itex]. Then by part (c), [itex]x_n[/itex] must converge in the standard metric. Every convergent sequence is Cauchy, but [itex]x_n[/itex] is not Cauchy in the standard metric - contradiction. So [itex]x_n[/itex] does not converge in [itex](\mathbb{R} , d)[/itex]; therefore not every Cacuhy sequence in [itex](\mathbb{R} , d)[/itex] converges so it is not complete.
 
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  • #7
Ted123 said:
How do I make [itex]|\tan^{-1}(m) - \tan^{-1}(n)|<\varepsilon[/itex] ? I'm guessing that the fact given in the question that [itex]d(x,y)< \pi[/itex] might help?

Well, this showing that [itex]x_n=n[/itex] is Cauchy in [itex](\mathbb{R},d)[/itex] is equivalent to showing that [itex]y_n=\tan^{-1}(n)[/itex] is Cauchy in the standard metric.

However, for the last part on whether [itex](\mathbb{R} ,d)[/itex] is complete, can I say: if it is complete then every Cauchy sequence in [itex](\mathbb{R} ,d)[/itex] must converge to a limit in [itex]\mathbb{R}[/itex].

Suppose the Cauchy sequence [itex]x_n=n[/itex] converges in [itex](\mathbb{R} ,d)[/itex]. Then by part (c), [itex]x_n[/itex] must converge in the standard metric. Every convergent sequence is Cauchy, but [itex]x_n[/itex] is not Cauchy in the standard metric - contradiction. So [itex]x_n[/itex] does not converge in [itex](\mathbb{R} , d)[/itex]; therefore not every Cacuhy sequence in [itex](\mathbb{R} , d)[/itex] converges so it is not complete.

That is good.
 
  • #8
micromass said:
Well, this showing that [itex]x_n=n[/itex] is Cauchy in [itex](\mathbb{R},d)[/itex] is equivalent to showing that [itex]y_n=\tan^{-1}(n)[/itex] is Cauchy in the standard metric.

In examples I've seen on showing a sequence is Cauchy they often involve getting [itex]d(x_m , x_n) \leqslant X \to 0[/itex] where [itex]X[/itex] is some upper bound. Why does this show the sequence is Cauchy?

For my sequence [itex]x_n = n[/itex] I could use the triangle inequality [itex]d(x_m , x_n) \leqslant d(x_m , \frac{\pi}{2} ) + d(\frac{\pi}{2} , x_n)[/itex]: [tex]d(x_m ,x_n) = | \tan^{-1} (x_m) - \tan^{-1}(x_n) |[/tex]
[itex]\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\; \leqslant | \tan^{-1}(m) - \frac{\pi}{2} | + | \tan^{-1}(n) - \frac{\pi}{2} | \to 0 + 0=0[/itex] as [itex]m,n \to \infty[/itex]

since [itex]\displaystyle \lim_{r\to\infty} \tan^{-1}(r) = \frac{\pi}{2}[/itex]
 
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  • #9
Ted123 said:
In examples I've seen on showing a sequence is Cauchy they often involve getting [itex]d(x_m , x_n) \leqslant X \to 0[/itex] where [itex]X[/itex] is some upper bound. Why does this show the sequence is Cauchy?

Well, write out what it means that [itex]d(x_m,x_n)\rightarrow 0[/itex]...

For my sequence [itex]x_n = n[/itex] I could use the triangle inequality [itex]d(x_m , x_n) \leqslant d(x_m , \frac{\pi}{2} ) + d(\frac{\pi}{2} , x_n)[/itex]: [tex]d(x_m ,x_n) = | \tan^{-1} (x_m) - \tan^{-1}(x_n) |[/tex]
[itex]\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\; \leqslant | \tan^{-1}(m) - \frac{\pi}{2} | + | \tan^{-1}(n) - \frac{\pi}{2} | \to 0 + 0=0[/itex] as [itex]m,n \to \infty[/itex]

since [itex]\displaystyle \lim_{r\to\infty} \tan^{-1}(r) = \frac{\pi}{2}[/itex]

That's good.
 
  • #10
Ted123 said:
For my sequence [itex]x_n = n[/itex] I could use the triangle inequality [itex]d(x_m , x_n) \leqslant d(x_m , \frac{\pi}{2} ) + d(\frac{\pi}{2} , x_n)[/itex]: [tex]d(x_m ,x_n) = | \tan^{-1} (x_m) - \tan^{-1}(x_n) |[/tex]
[itex]\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\; \leqslant | \tan^{-1}(m) - \frac{\pi}{2} | + | \tan^{-1}(n) - \frac{\pi}{2} | \to 0 + 0=0[/itex] as [itex]m,n \to \infty[/itex]

Be careful when you're writing this up! You're using the triangle inequality for absolute value here, but you're not using the triangle inequality for the metric d here - if you were actually using d(xn,pi/2) you would end up with |arctan(n)-arctan(pi/2)|+|arctan(m)-arctan(pi/2)| which doesn't go to zero as n and m go to infinity
 
  • #11
Office_Shredder said:
Be careful when you're writing this up! You're using the triangle inequality for absolute value here, but you're not using the triangle inequality for the metric d here - if you were actually using d(xn,pi/2) you would end up with |arctan(n)-arctan(pi/2)|+|arctan(m)-arctan(pi/2)| which doesn't go to zero as n and m go to infinity

I'm not getting any credit for this; it's all past exam paper stuff.

But, yes - it's the scalar triangle inequality I should be using!
 

1. What is a metric space?

A metric space is a mathematical concept that describes a set of objects or points along with a distance function that assigns a non-negative real number to each pair of points. This distance function defines the metric space by determining the distance between any two points in the set.

2. What is a Cauchy sequence?

A Cauchy sequence is a sequence of elements in a metric space that becomes arbitrarily close to each other as the sequence progresses. In other words, for any positive distance, there exists a point in the sequence after which all points are within that distance of each other.

3. How do you show that a sequence is Cauchy?

To show that a sequence is Cauchy, you need to prove that for any positive distance, there exists a point in the sequence after which all points are within that distance of each other. This can be done by using the definition of a Cauchy sequence and applying it to the given sequence.

4. What is the importance of Cauchy sequences in metric spaces?

Cauchy sequences are important in metric spaces because they help us understand the behavior and convergence of sequences in these spaces. They also play a crucial role in the definition of completeness, which is an important property of metric spaces.

5. How are Cauchy sequences different from convergent sequences?

A Cauchy sequence is a sequence where the elements become arbitrarily close to each other as the sequence progresses. In contrast, a convergent sequence is a sequence that has a limit, meaning that the elements become arbitrarily close to a specific value as the sequence progresses. While all convergent sequences are Cauchy, not all Cauchy sequences are convergent.

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