Last time we discussed two versions of compactness: the sequential compactness and the open cover compactness.
Theorem: let be a metric space. Then, is sequentially compact, if and only if is open cover compact.
Last time we have shown open cover compactness implies sequential compactness, today we show the converse.
Suppose a metric space is sequentially compact, namely, any sequence in has a convergent subsequence. How to show that any open cover of has a finite sub-cover? We first introduce
Definition (A Lebesgue number of a cover ) we say is a Lebesgue number of the covering , if for any , there is some , such that .
Lemma Every open cover of a sequentially compact space has a Lebesgue number .
Proof: suppose not, then for every , there exists a point , such that is not contained in any . Let take values for , and we get a sequence for . By sequential compactness, this sequence has a convergent subsequence, say converge to . However, is contained in some open set , thus there is that . Thus, let , and large enough such that , since sub-converge to , there exists with . Thus, we have
which contradict with is not contained in any . This proves the lemma.
Lemma If is a sequentially compact space, then for any , can be covered by finitely many open balls of radius . Proof: We claim that can only contain finitely many disjoint open balls with radius . Then, take such a maximal -radius ball packing, and replace the radius balls by radius balls, claim the bigger balls cover . (Discussion: prove the two claims)
Given the above two lemma, one can prove that any open cover of a sequentially compact space admits a finite subcover. (Discussion: prove it)
1. Compactness is an absolute (or intrinsic) property of a metric space. If is a metric space, and is a subset, when we say is compact, we mean as a 'stand-alone' metric space (totally forgetting about , but only using the distance function inherited from ) is compact.
2. We proved last time: If is (open cover) compact, then is closed and bounded. (Discussion: if you replace open cover compact by sequential compactness, can you prove the two conclusions directly (without using the equivalence of the two definitions)?)
3. We know that is sequentially compact (by Heine-Borel theorem), can you show that is sequentially compact? (Hint: given a sequence in , first show that you can pass to subsequence to make the sequence of the first coordinate converge, then …)
There are two notions of compactness, they turn out to be equivalent for metric spaces.
Let be a metric space, a subset.
The two notions turns out are equivalent, see https://courses.wikinana.org/math104-f21/compactness
We will follow Pugh to give a proof. See also Rudin Thm 2.41
We will finish discussion about compactness. In particular, in , we have Heine-Borel theorem, namely, compact subsets are exactly those subsets which are closed and bounded. Note that, this is false for general metric space, e.g. closed and bounded subset in are not compact.
Last time we had some basic notion of metric space (a set with the notion of distances), and topological space (which is a set with some notion of which subsets are open).
Today, we will define continuous functions (or rather continuous maps) between metric spaces and between topological spaces.
Def 1 : Let and be two metric spaces, a map is continuous, if for every convergent sequence in , we have convergent sequence .
Def 2 : (: Let and be two metric spaces, a map is continuous, if for every , and every , we have , such that .
Def 3 : Let be two topological spaces, we say a map is continuous, if for every open sets , we have is open in .
We can discuss later, why the three definitions are equivalent.
Homeomorphism: if is continuous and a bijection, and if is also continuous, then we say is a homeomorphism.
Topologically, we cannot distinguish spaces that are homeomorphic.
We plan to discuss topological space. Read Ross section 13 to see the axioms of 'topology'.
Exam solution given in lecture.
We begin discussing metric space and topological space. The note from last year might be useful.
Can you think of other example of metric spaces?