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Cantor Groups, Haar Measure andLebesgue Measure on [0, 1]
Michael Mislove
Tulane University
Domains XIParis
Tuesday, 9 September 2014
Joint work with Will Brian
Work Supported by US NSF & US AFOSR
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Lebesgue Measure and Unit Interval
I [0, 1] ⊆ R inherits Lebesgue measure: λ([a, b]) = b − a.
I Translation invariance: λ(A + x) = λ(A) for all (Borel)measurable A ⊆ R and all x ∈ R.
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Lebesgue Measure and Unit Interval
I [0, 1] ⊆ R inherits Lebesgue measure: λ([a, b]) = b − a.
I Translation invariance: λ(A + x) = λ(A) for all (Borel)measurable A ⊆ R and all x ∈ R.
I Theorem (Haar, 1933) Every locally compact group G has aunique (up to scalar constant) left-translation invariantregular Borel measure µG called Haar measure.
If G is compact, then µG (G ) = 1.
Example: T ' R/Z with quotient measure from λ.
If G is finite, then µG is normalized counting measure.
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The Cantor Set
C0C1C2C3C4
C =⋂
n Cn ⊆ [0, 1] compact 0-dimensional, λ(C) = 0.
Theorem: C is the unique compact Hausdorff 0-dimensionalsecond countable perfect space.
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Cantor Groups
I Canonical Cantor group:C ' Z2
N is a compact group in the product topology.
µC is the product measure (µZ2(Z2) = 1)
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Cantor Groups
I Canonical Cantor group:C ' Z2
N is a compact group in the product topology.
µC is the product measure (µZ2(Z2) = 1)
Theorem: (Schmidt) The Cantor map C → [0, 1] sends Haarmeasure on C = Z2
N to Lebesgue measure.
Goal: Generalize this to all group structures on C.
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Cantor Groups
I Canonical Cantor group:C ' Z2
N is a compact group in the product topology.
µC is the product measure (µZ2(Z2) = 1)
Definition: A Cantor group is a compact 0-dimensional secondcountable perfect space endowed with a topological groupstructure.
I G =∏
n>1 Zn is also a Cantor group.
µG is the product measure (µZn(Zn) = 1)
I Zp∞ = lim←−nZpn – p-adic integers.
I H =∏
n S(n), where each S(n) is the symmetric group on nletters.
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Two Theorems and a Corollary
I Theorem: If G is a compact 0-dimensional group,then G has a neighborhood basis at the identity ofclopen normal subgroups.
I Proof:
1. G is a Stone space, so there is a basis O of clopenneighborhoods of e.If O ∈ O, then e · O = O ⇒ (∃U ∈ O) U · O ⊆ O
U ⊆ O ⇒ U2 ⊆ U · O ⊆ O. So Un ⊆ O.
Assuming U = U−1, the subgroup H =⋃
n Un ⊆ O.
2. Given H < G clopen, H = {xHx−1 | x ∈ G} is compact.
G ×H → H by (x ,K ) 7→ xKx−1 is continuous.
K = {x | xHx−1 = H} is clopen since H is, so G/K is finite.
Then |G/K | = |H| is finite, so L =⋂
x∈G xHx−1 ⊆ H is clopenand normal.
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Two Theorems and a Corollary
I Theorem: If G is a compact 0-dimensional group,then G has a neighborhood basis at the identity ofclopen normal subgroups.
I Corollary: If G is a Cantor group, then G ' lim←−nGn
with Gn finite for each n.
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Two Theorems and a Corollary
I Theorem: If G is a compact 0-dimensional group,then G has a neighborhood basis at the identity ofclopen normal subgroups.
I Corollary: If G is a Cantor group, then G ' lim←−nGn
with Gn finite for each n.
I Theorem: (Fedorchuk, 1991) If X ' lim←−i∈I Xi is astrict projective limit of compact spaces, thenProb(X ) ' lim←−i∈I Prob(Xi ).
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Two Theorems and a Corollary
I Theorem: If G is a compact 0-dimensional group,then G has a neighborhood basis at the identity ofclopen normal subgroups.
I Corollary: If G is a Cantor group, then G ' lim←−nGn
with Gn finite for each n.
I Theorem: (Fedorchuk, 1991) If X ' lim←−i∈I Xi is astrict projective limit of compact spaces, thenProb(X ) ' lim←−i∈I Prob(Xi ).
I Lemma: If ϕ : G → H is a surmorphism of compact groups,then Prob(ϕ)(µG ) = µH .
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Two Theorems and a Corollary
I Theorem: If G is a compact 0-dimensional group,then G has a neighborhood basis at the identity ofclopen normal subgroups.
I Corollary: If G is a Cantor group, then G ' lim←−nGn
with Gn finite for each n.
I Theorem: (Fedorchuk, 1991) If X ' lim←−i∈I Xi is astrict projective limit of compact spaces, thenProb(X ) ' lim←−i∈I Prob(Xi ).
In particular, if X = G ,Xi = Gi are compact groups, thenµG = limi∈I µGi
.
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Two Theorems and a Corollary
I Theorem: If G is a compact 0-dimensional group,then G has a neighborhood basis at the identity ofclopen normal subgroups.
I Corollary: If G is a Cantor group, then G ' lim←−nGn
with Gn finite for each n.Moreover, µG = limn µn, where µn is normalized countingmeasure on Gn.
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It’s all about Abelian Groups
I Theorem: If G = lim←−nGn is a Cantor group, there is a
sequence (Zki )i>0 of cyclic groups so that H = lim←−n(⊕i≤nZki )
has the same Haar measure as G .
Proof: Let G ' lim←−nGn, |Gn| <∞.
Assume |Hn| = |Gn| with Hn abelian.
If φn : Gn+1 → Gn is surjective, then Gn+1/ ker φn ' Gn. So|Gn+1| = |Gn| × | ker φn|.Define Hn+1 = Hn × Z| ker φn|. Then |Hn+1| = |Gn+1|,so µHn = µn = µGn for each n, and H = lim←−n
Hn is abelian.
Hence µH = limn µn = µG .
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Combining Domain Theory and Group Theory
C = lim←−nHn, Hn = ⊕i≤n Zki
Endow Hn with lexicographic order for each n; then
πn : Hn+1 → Hn by πn(x1, . . . , xn+1) = (x1, . . . , xn) &
ιn : Hn ↪→ Hn+1 by ιn(x1, . . . , xn) = (x1, . . . , xn, 0) form
embedding-projection pair.
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Combining Domain Theory and Group Theory
C = lim←−nHn, Hn = ⊕i≤n Zki
Endow Hn with lexicographic order for each n; then
πn : Hn+1 → Hn by πn(x1, . . . , xn+1) = (x1, . . . , xn) &
ιn : Hn ↪→ Hn+1 by ιn(x1, . . . , xn) = (x1, . . . , xn, 0) form
embedding-projection pair.
C ' bilim (Hn, πn, ιn) is bialgebraic chain:
• C totally ordered, has all sups and infs
• K (C) =⋃
n{(x1, . . . , xn, 0, . . .) | (x1, . . . , xn) ∈ Hn}• K (Cop) = {sup (↓k \ {k}) | k ∈ K (C)}
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Combining Domain Theory and Group Theory
C = lim←−nHn, Hn = ⊕i≤n Zki
Endow Hn with lexicographic order for each n; then
πn : Hn+1 → Hn by πn(x1, . . . , xn+1) = (x1, . . . , xn) &
ιn : Hn ↪→ Hn+1 by ιn(x1, . . . , xn) = (x1, . . . , xn, 0) form
embedding-projection pair.
C ' bilim (Hn, πn, ιn) is bialgebraic chain:
ϕ : K (C)→ [0, 1] by ϕ(x1, . . . , xn, 0, 0, . . .) =∑
i≤nxi
k1···ki strictlymonotone
induces ϕ̂ : C → [0, 1] monotone, Lawson continuous.
Direct calculation shows:
µC(ϕ̂−1(a, b)) = λ((a, b)) for a ≤ b ∈ [0, 1]; i.e., Prob(ϕ̂)(µC) = λ.
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Alternative Proof
1. Cantor Tree: CT ' Σ∞ = Σ∗ ∪ Σω, Σ = {0, 1}s ≤ t ⇐⇒ (∃u) su = t. Then Max CT ' C.
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Alternative Proof
1. Cantor Tree: CT ' Σ∞ = Σ∗ ∪ Σω, Σ = {0, 1}s ≤ t ⇐⇒ (∃u) su = t. Then Max CT ' C.
2. Interval domain: Int([0, 1]) = ({[a, b] | 0 ≤ a ≤ b ≤ 1},⊇)
φ̂ : C → [0, 1] extends to Φ: CT → Int([0, 1]) Scottcontinuous.
Then Prob(Φ): Prob(CT )→ Prob(Int([0, 1])), so
λ = Prob(Φ)(µC) = lim Prob(Φ)(µn), where
Prob(Φ)(µn) =∑
1≤i≤2n12n · δ[ i−1
2n, i2n
]
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Skorohod’s Theorem
Theorem: (Skorohod) If ν is a Borel probability measure on a Polishspace X , then there is a measurable map ξν : [0, 1]→ X satisfyingProb(ξν)(λ) = ν; i.e., ν(A) = λ(ξ−1ν (A)).
Corollary: If ν is a Borel probability measure on a Polish space X , thenthere is a measurable map ξν : C → X satisfying Prob(ξν)(µC) = ν.
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Skorohod’s Theorem
Theorem: (Skorohod) If ν is a Borel probability measure on a Polishspace X , then there is a measurable map ξν : [0, 1]→ X satisfyingProb(ξν)(λ) = ν; i.e., ν(A) = λ(ξ−1ν (A)).
Corollary: If ν is a Borel probability measure on a Polish space X , thenthere is a measurable map ξν : C → X satisfying Prob(ξν)(µC) = ν.
Proof using Domain Theory:
1◦ : X ↪→ X ⊆ [0, 1]N & X is dense Gδ in X ; Prob(X ) ↪→ Prob(X ).
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Skorohod’s Theorem
Theorem: (Skorohod) If ν is a Borel probability measure on a Polishspace X , then there is a measurable map ξν : [0, 1]→ X satisfyingProb(ξν)(λ) = ν; i.e., ν(A) = λ(ξ−1ν (A)).
Corollary: If ν is a Borel probability measure on a Polish space X , thenthere is a measurable map ξν : C → X satisfying Prob(ξν)(µC) = ν.
Proof using Domain Theory:
1◦ : X ↪→ X ⊆ [0, 1]N & X is dense Gδ in X ; Prob(X ) ↪→ Prob(X ).
2◦ : X is a continuous image of C: ∃ψ : C →→ X .
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Skorohod’s Theorem
Theorem: (Skorohod) If ν is a Borel probability measure on a Polishspace X , then there is a measurable map ξν : [0, 1]→ X satisfyingProb(ξν)(λ) = ν; i.e., ν(A) = λ(ξ−1ν (A)).
Corollary: If ν is a Borel probability measure on a Polish space X , thenthere is a measurable map ξν : C → X satisfying Prob(ξν)(µC) = ν.
Proof using Domain Theory:
1◦ : X ↪→ X ⊆ [0, 1]N & X is dense Gδ in X ; Prob(X ) ↪→ Prob(X ).
2◦ : X is a continuous image of C: ∃ψ : C →→ X .
3◦ : Prob(ψ) : Prob(C)→→ Prob(X ).
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Skorohod’s Theorem
Theorem: (Skorohod) If ν is a Borel probability measure on a Polishspace X , then there is a measurable map ξν : [0, 1]→ X satisfyingProb(ξν)(λ) = ν; i.e., ν(A) = λ(ξ−1ν (A)).
Corollary: If ν is a Borel probability measure on a Polish space X , thenthere is a measurable map ξν : C → X satisfying Prob(ξν)(µC) = ν.
Proof using Domain Theory:
1◦ : X ↪→ X ⊆ [0, 1]N & X is dense Gδ in X ; Prob(X ) ↪→ Prob(X ).
2◦ : X is a continuous image of C: ∃ψ : C →→ X .
3◦ : Prob(ψ) : Prob(C)→→ Prob(X ).
4◦ : So it suffices to show every ν ∈ Prob(C) satisfies the Corollary.
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Skorohod’s Theorem
Theorem: (Skorohod) If ν is a Borel probability measure on a Polishspace X , then there is a measurable map ξν : [0, 1]→ X satisfyingProb(ξν)(λ) = ν; i.e., ν(A) = λ(ξ−1ν (A)).
Corollary: If ν is a Borel probability measure on a Polish space X , thenthere is a measurable map ξν : C → X satisfying Prob(ξν)(µC) = ν.
Proof using Domain Theory:
4◦ : So it suffices to show every ν ∈ Prob(C) satisfies the Corollary.
ν ∈ Prob(C) qua valuation on Σ(C) preserves all suprema, so
Fν : C → [0, 1] by Fν(x) = ν(↓x) preserves all infima – Fν is the ‘cdf” ofν.
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Skorohod’s Theorem
Theorem: (Skorohod) If ν is a Borel probability measure on a Polishspace X , then there is a measurable map ξν : [0, 1]→ X satisfyingProb(ξν)(λ) = ν; i.e., ν(A) = λ(ξ−1ν (A)).
Corollary: If ν is a Borel probability measure on a Polish space X , thenthere is a measurable map ξν : C → X satisfying Prob(ξν)(µC) = ν.
Proof using Domain Theory:
4◦ : So it suffices to show every ν ∈ Prob(C) satisfies the Corollary.
ν ∈ Prob(C) qua valuation on Σ(C) preserves all suprema, so
Fν : C → [0, 1] by Fν(x) = ν(↓x) preserves all infima – Fν is the ‘cdf” ofν.
Fν has a lower adjoint χν : [0, 1]→ C preserving all suprema;
χν(r) ≤ x iff r ≤ Fν(x).
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Skorohod’s Theorem
Theorem: (Skorohod) If ν is a Borel probability measure on a Polishspace X , then there is a measurable map ξν : [0, 1]→ X satisfyingProb(ξν)(λ) = ν; i.e., ν(A) = λ(ξ−1ν (A)).
Corollary: If ν is a Borel probability measure on a Polish space X , thenthere is a measurable map ξν : C → X satisfying Prob(ξν)(µC) = ν.
Proof using Domain Theory:
4◦ : So it suffices to show every ν ∈ Prob(C) satisfies the Corollary.
ν ∈ Prob(C) qua valuation on Σ(C) preserves all suprema, so
Fν : C → [0, 1] by Fν(x) = ν(↓x) preserves all infima – Fν is the ‘cdf” ofν.
Fν has a lower adjoint χν : [0, 1]→ C preserving all suprema;χν(r) ≤ x iff r ≤ Fν(x). So
λ({r | χν(r) ≤ x}) = λ({r | r ≤ Fν(x)}) = λ([0,Fν(x)]) = Fν(x).
Now φ : C → [0, 1] has an upper adjoint φ∗ : [0, 1]→ C.
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Skorohod’s Theorem
Theorem: (Skorohod) If ν is a Borel probability measure on a Polishspace X , then there is a measurable map ξν : [0, 1]→ X satisfyingProb(ξν)(λ) = ν; i.e., ν(A) = λ(ξ−1ν (A)).
Corollary: If ν is a Borel probability measure on a Polish space X , thenthere is a measurable map ξν : C → X satisfying Prob(ξν)(µC) = ν.
Proof using Domain Theory:
4◦ : So it suffices to show every ν ∈ Prob(C) satisfies the Corollary.
ν ∈ Prob(C) qua valuation on Σ(C) preserves all suprema, so
Fν : C → [0, 1] by Fν(x) = ν(↓x) preserves all infima – Fν is the ‘cdf” ofν.
Fν has a lower adjoint χν : [0, 1]→ C preserving all suprema;χν(r) ≤ x iff r ≤ Fν(x). So
λ({r | χν(r) ≤ x}) = λ({r | r ≤ Fν(x)}) = λ([0,Fν(x)]) = Fν(x).
Now φ : C → [0, 1] has an upper adjoint φ∗ : [0, 1]→ C.
Then ξν = φ ◦ χν : C → C is lower adjoint to φ∗ ◦ Fν : C → C, so itpreserves all sups and gives the desired result. 2
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Skorohod’s Theorem
Theorem: (Skorohod) If ν is a Borel probability measure on a Polishspace X , then there is a measurable map ξν : [0, 1]→ X satisfyingProb(ξν)(λ) = ν; i.e., ν(A) = λ(ξ−1ν (A)).
Corollary: If ν is a Borel probability measure on a Polish space X , thenthere is a measurable map ξν : C → X satisfying Prob(ξν)(µC) = ν.
Proof using Domain Theory:
Then ξν = φ ◦ χν : C → C is lower adjoint to φ∗ ◦ Fν : C → C, so itpreserves all sups and gives the desired result. 2
Remark: Notice that, in the case of ν ∈ Prob(C), we have provedmore than claimed, since ξν preserves all suprema, and so it isScott continuous, rather than being just measurable.