This is an analysis exercise that I have been struggling with for some time now. I am not familiar with metric spaces.
In $\mathbb{R}$, the book that I am using proves this fact by showing that every Cauchy sequence in $\mathbb{R}$ is bounded. Next, they use Bolzano-Weierstrass to choose a convergent subsequence of that Cauchy sequence.
However, the book does not specify an analog to boundedness in $\mathbb{R}^{n}$. Also, the book proved Bolzano-Weierstrass for $\mathbb{R}$, not $\mathbb{R}^{n}$. I was originally planning to outline the $\mathbb{R}$ approach by proving boundedness and choosing a convergent subsequence, but this is not currently possible because of what I said.
I was wondering if there is a good way to do this problem.
Thanks
Best Answer
So, first, we need a distance on $\mathbb{R}^k$. We have a number of choices; the usual Euclidean distance $d_2(x,y)=\sqrt{\sum_j (x_j-y_j)^2}$, the "taxicab" distance $d_1(x,y)=\sum_j |x_j-y_j|$, the sup norm $d_{\infty}(x,y)=\max_j |x_j-y_j|$, and others. (In these definitions, $x_j$ and $y_j$ are the components of $x$ and $y$ respectively.)
Once we have a distance, we can define bounded sets, Cauchy sequences, and convergence in exactly the same way we did for $\mathbb{R}$:
This is all general stuff for the topic of metric spaces - standard definitions.
So, then, what about $\mathbb{R}^k$? As it turns out, our choice of distance doesn't really matter; within a pretty broad class that includes all the example I gave, they're "equivalent". The exact distances between a pair of points may vary, but we can bracket a distance function of a pair of points between two constant multiples of another distance function. For example, $d_{\infty}(x,y) \le d_1(x,y)\le k\cdot d_{\infty}(x,y)$ for any $x,y$.
Because of this property, any of these distance functions induce the same topology - the same bounded sets, Cauchy sequences, convergent sequences, open sets, and closed sets.
And with that, a theorem: Under any of these "nice" distances, a set $S$ is bounded if and only if each of the component sets $S_i=\{x_i: x\in S\}$ is bounded. A sequence $x(n)$ converges to $x$ if and only if each of the component sequences $x_i(n)$ converges to $x_i$. A sequence $x(n)$ is Cauchy if and only if each of the component sequences $x_i(n)$ is Cauchy.
With that, we can prove Bolzano-Weierstrass in $\mathbb{R}^k$ by applying the version from $\mathbb{R}$. Start with a bounded sequence in $\mathbb{R}^k$. The first components are bounded, so we extract a subsequence with convergent first components from that. Then the second components are bounded, so we extract a further subsequence with convergent second components - and its first components still converge. Repeat this process $k$ times to reach a subsequence with each of its components convergent, and we have it.
You'll need to be. Simply defining things like bounded sequences and Cauchy sequences requires that distance function. Convergence gives you a choice - either metric spaces or more general point-set topology. The metric spaces are usually treated earlier, because they're more familiar.
Fortunately, these topics will come up in your course, or possibly a later course in the sequence.