Let (xn) and (yn) be Cauchy sequences in (X,d). Show that (xn) and (yn) converge to the same limit iff d(xn,yn)→0
Proof →
Suppose (xn)→a and (yn)→a, then
∀ϵ>0∃N1s.t.∀n>N1⟹d(xn,a)<ϵ2∀ϵ>0∃N2s.t.∀n>N2⟹d(yn,a)<ϵ2
Given ϵ>0 take N=max then \forall_{n>N} we have:
\begin{align} d(x_n, y_n) &\leq d(x_n, a) + d(a, y_n) \\ & < \dfrac{\epsilon}{2} + \dfrac{\epsilon}{2} = \epsilon \end{align}
What is the cleanest way to finish this piece of the proof? Technically I feel like I could do the following:
Consider d(d(x_n, y_n), 0):
\begin{align} d(d(x_n, y_n), 0) &< d(\epsilon, 0) < \epsilon \implies d(x_n, y_n) \to 0 \end{align}
What can I do to make this direction of the proof cleaner? Note that I only used the fact that the sequences converged and nothing special about Cauchy sequences. Additionally, what is the formal definition of d(x_n, yn) \to 0?
ADDED
\leftarrow Suppose d(x_n, y_n) \to 0 that is \forall_{\epsilon > 0} \exists_{N_1} s.t \forall_{n > N_1} \implies |d(x_n, y_n) - 0| < \epsilon. Given \epsilon > 0 take N > N_1 then by the triangle inequality we have:
\begin{align} 0 < d(x_n, y_n) \leq d(x_n, a) + d(a, y_n) < \epsilon \end{align}
We know this a exists as (X, d) is a complete metric space and (x_n) and (y_n) are Cauchy. Thus we have that d(x_n, a) < \epsilon \land d(y_n, a) < \epsilon.
Therefore, (x_n)\to a \land (y_n)\to a
How does the other direction look?
Answer
Remember that your metric d is real valued, and the real numbers are a metric space. Thus, the formal definition of d(x_n, y_n) \rightarrow 0 is the same as for convergence of a sequence in a metric space, i.e., for every \epsilon > 0 there exists an N \in \mathbb{N} such that for all n \geq N we have d_{\mathbb{R}}(d(x_n,y_n), 0) < \epsilon.
Note the d_{\mathbb{R}}! This is the metric on the real numbers (where d(x_n,y_n) and 0 live). It is defined by d_{\mathbb{R}}(x,y) = |x -y|. So a much less obfuscated way to write the definition above is the following:
d(x_n, y_n) \rightarrow 0 if for every \epsilon > 0 there exists an N \in \mathbb{N} such that for all n \geq N we have |d(x_n,y_n) - 0| < \epsilon. But this is exactly what you have shown in the part before your proposed finish! You can actually stop right there with the \epsilon. You could also add a note about how you know d(x_n,y_n) \geq 0.
The error in what you go on to write is that d(d(x_n,y_n), 0) may not be defined since d is a metric on X while d(x_n, y_n) and 0 are in \mathbb{R}.
As for the Cauchy assumption, you need that to do the converse (along with completeness of X).
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