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Extreme points of the probability measures are Dirac masses

Statement

For a compact Hausdorff space K, the extreme points of the convex set of regular Borel probability measures on K are exactly the Dirac measures δx with x∈K.

Facts & Assumptions

Given: A compact Hausdorff space K and its convex set P(K) of regular Borel probability measures.

[F1]

Extreme points are exactly points whose strict two-term convex decompositions are trivial (Extreme point and face).

[F2]

Every Dirac set function is a probability measure (A Dirac set function is a probability measure).

[F3]

Restricting a measure to a measurable set produces a measure (The restriction of a measure to a measurable set is a measure).

[F4]

A regular Borel measure is inner regular on every Borel set (Regular Borel measure on an LCH space).

[F5]

A closed family with the finite-intersection property has nonempty intersection in a compact space (A space is compact exactly when every family of closed subsets with the finite intersection property has nonempty intersection).

Proof

technique · direct characterization by measurable restrictions
1.1F4F7given

If K=∅, then P(K)=∅ and there are no Dirac measures, so the equality is empty on both sides. Hence assume K≠∅. By [F7], compactness makes K locally compact, and it is Hausdorff by hypothesis, so the LCH regularity convention [F4] applies.

1.2F3F4given

Let μ∈P(K) and let A be Borel. The restriction μA(E)=μ(E∩A) is a measure by [F3]. It is regular: for Borel E, inner regularity of μ on E∩A gives μA(E)=sup⁡{μ(D):D⊆E∩A, D compact}; every such D is also a compact subset of E with μA(D)=μ(D), while every compact C⊆E satisfies μA(C)≤μA(E). Thus the required supremum over compact C⊆E equals μA(E).

1.3F5given

Suppose that μ(E)∈{0,1} for every Borel E. Let C be all closed C⊆K with μ(C)=1. It contains K. A finite intersection of its members has measure one because the complement is a finite union of null sets, so C has the finite-intersection property. By [F5], choose x∈⋂C.

1.4F1F2given

Conversely, fix any x∈K. By [F2], δx is a probability measure. The Hausdorff hypothesis makes the compact singleton {x} closed and hence Borel. Thus δx is regular: for a Borel set containing x, that singleton realizes mass one, while a set not containing x has mass zero. If δx=tμ+(1−t)ν with μ,ν∈P(K) and 0<t<1, evaluation on K∖{x} gives 0=tμ(K∖{x})+(1−t)ν(K∖{x}), so nonnegativity gives both masses zero. Thus μ({x})=ν({x})=1 and μ=ν=δx; [F1] makes δx extreme.

2.1F1step 1.2

If 0<t:=μ(A)<1, define μ1=t−1μA and μ2=(1−t)−1μK∖A. Step 1.2 makes both regular probabilities, and μ=tμ1+(1−t)μ2. They are distinct because μ1(A)=1 and μ2(A)=0, so [F1] shows that μ is not extreme.

2.2step 1.3

Every open neighborhood U of the point x from step 1.3 has measure one. Otherwise the zero-one hypothesis gives μ(U)=0, so the closed complement K∖U has measure one and belongs to C, contradicting x∈U∩⋂C.

3.1F4F6step 2.2

If D⊆K∖{x} is compact, [F6] gives disjoint open sets U,V with x∈U and D⊆V. Step 2.2 gives μ(U)=1, hence μ(V)=0 and μ(D)=0. Inner regularity [F4] on the Borel set K∖{x} now gives μ(K∖{x})=0, so μ=δx.

4.1step 1.1step 1.3step 1.4step 2.1step 2.2step 3.1∎

Let μ be extreme. Step 2.1 rules out every Borel set of intermediate mass, so μ is zero-one valued; steps 1.3, 2.2, and 3.1 then give μ=δx for some x∈K. Step 1.4 proves the reverse implication, and step 1.1 covers the empty space.

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