Proving Completeness of $(\mathbb{R},d)$

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Shoelace Thm.
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Homework Statement


Prove that [itex](\mathbb{R},d)[/itex], [itex]d = \frac{\mid x - y \mid}{1 + \mid x - y \mid}[/itex] is a complete metric space.

Homework Equations


The Attempt at a Solution


If [itex]d_u = \mid x - y \mid[/itex], then I can prove this for the Cauchy sequences in [itex](\mathbb{R},d)[/itex] that are also Cauchy in [itex](\mathbb{R},d_u)[/itex]. But there may be Cauchy sequences in [itex](\mathbb{R},d)[/itex] that are not Cauchy in [itex](\mathbb{R},d_u)[/itex].
 
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Shoelace Thm. said:

Homework Statement


Prove that [itex](\mathbb{R},d)[/itex], [itex]d = \frac{\mid x - y \mid}{1 + \mid x - y \mid}[/itex] is a complete metric space.


Homework Equations





The Attempt at a Solution


If [itex]d_u = \mid x - y \mid[/itex], then I can prove this for the Cauchy sequences in [itex](\mathbb{R},d)[/itex] that are also Cauchy in [itex](\mathbb{R},d_u)[/itex]. But there may be Cauchy sequences in [itex](\mathbb{R},d)[/itex] that are not Cauchy in [itex](\mathbb{R},d_u)[/itex].

Can you give me an example of one? I don't really think there are any.
 
I couldn't find one either. How can I prove there are none i.e., there is one-to-one correspondence between the Cauchy sequences of each space?
 
Shoelace Thm. said:
I couldn't find one either. How can I prove there are none i.e., there is one-to-one correspondence between the Cauchy sequences of each space?

Suppose you could find constants m and M such that ##md(x,y) \le d_u(x,y) \le Md(x,y)##? You would have trouble with the M part of that, but remember when you are dealing with Cauchy sequences you only have to worry about small values of |x-y|.
 
I don't quite understand what you are getting at, but I have that for n,m sufficiently large and [itex]x_n[/itex] Cauchy in (R,d), [itex]\frac{\mid x_n - x_m \mid}{1 + \mid x_n - x_m \mid} < \epsilon \rightarrow \mid x_n - x_m \mid < \frac{1}{1 - \epsilon}[/itex]. So [itex]x_n[/itex] is Cauchy in (R,d_u).
 
Does this work?
 
Shoelace Thm. said:
I don't quite understand what you are getting at, but I have that for n,m sufficiently large and [itex]x_n[/itex] Cauchy in (R,d), [itex]\frac{\mid x_n - x_m \mid}{1 + \mid x_n - x_m \mid} < \epsilon \rightarrow \mid x_n - x_m \mid < \frac{1}{1 - \epsilon}[/itex]. So [itex]x_n[/itex] is Cauchy in (R,d_u).
I don't see how that works, because ##1/(1-\epsilon)## does not approach 0 as ##\epsilon \rightarrow 0##.

Suppose that
$$\frac{|x-y|}{1 + |x-y|} \leq \frac{1}{2}$$
Then we have
$$\begin{align}
|x-y| &= \frac{|x-y|}{1+|x-y|} \cdot (1 + |x-y|) \\
&= \frac{|x-y|}{1+|x-y|} + \frac{|x-y|}{1+|x-y|} \cdot |x-y| \\
&<= \frac{|x-y|}{1+|x-y|} + \frac{1}{2}|x-y| \\
\end{align}$$
So
$$|x-y| \leq 2\frac{|x-y|}{1 + |x-y|}$$
This should allow you to conclude that Cauchy in ##d## implies Cauchy in ##d_u##.

By the way, did you already prove that ##d## is a metric?
 
Shoelace Thm. said:
Does this work?

junniiii as already done a fine job of pointing out why it doesn't work. My point was that you only have to worry around small values of ε. If |x-y|<1 then d and d_u are almost the same. They differ by a factor of at most 2.
 
Dick: Ok I understand now.

jbunniii: Yes I did prove d is a metric.