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We saw earlier how the ideas of convergence could be interpreted in a topological rather than a metric space:
A sequence (ai) converges to if every open set containing contains all but a finite number of the {ai}.
Unfortunately, this definition does not give some of thr "nice" properties we get in a metric space.
For example, if a sequence in a metric space converges, it has a unique limit, but in a topological space this need not happen. For example, in R with the trivial topology every sequence converges to every point.
To recove the nice properties of convergence we need to have "enough" open sets in the topology. Topologists have devised various separation axioms to classify how this happens.
Definition
A topological space X is called Hausdorff if every pair of points can be separated by open sets.
That is, if x1 x2 X then there are disjoint open sets U1 and U2 with x1 U1 and x2 U2 .
Remarks
Proof
Theorem
In any Hausdorff space sequences have at most one limit.
Proof
Theorem
In a Hausdorff space every point is a closed set.
Proof
Remark
It follows that every finite set is closed in a Hausdorff space and the topology is therefore stronger than the cofinite topology.
The other separation axiom we will consider is:
Definition
A topological space X is called normal if every disjoint pair of closed sets can be separated by open sets.
That is, if A1 and A2 are disjoint closed subsets of X then there are disjoint open sets U1 and U2 with A1 U1 and A2 U2 .
Remark
If every point is a closed set (that is T1) then such a normal space is Hausdorff. [normal + T1 = T4]
Theorem
Every metric space is normal.
Proof
Remark
Note that the distance between disjoint closed sets may be 0 (but they can still be separated by open sets).
Examples
Remarks
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