UHF slicing and classification of nuclear C*-algebras Karen R. - - PowerPoint PPT Presentation

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UHF slicing and classification of nuclear C*-algebras Karen R. - - PowerPoint PPT Presentation

UHF slicing and classification of nuclear C*-algebras Karen R. Strung (joint work with Wilhelm Winter) Mathematisches Institut Universit at M unster Workshop on C*-Algebras and Noncommutative Dynamics Sde Boker, Israel March 2013 Karen


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UHF slicing and classification of nuclear C*-algebras

Karen R. Strung (joint work with Wilhelm Winter)

Mathematisches Institut Universit¨ at M¨ unster

Workshop on C*-Algebras and Noncommutative Dynamics Sde Boker, Israel March 2013

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 1 / 18

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Let A be the class of separable nuclear unital simple C ∗-algebras satisfying

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 2 / 18

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Let A be the class of separable nuclear unital simple C ∗-algebras satisfying

1 A ∈ A =

⇒ A is locally recursive subhomogeneous (RSH) where the RSH algebras can be chosen so that projections can be lifted along an (F, η)-connected decomposition,

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 2 / 18

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Let A be the class of separable nuclear unital simple C ∗-algebras satisfying

1 A ∈ A =

⇒ A is locally recursive subhomogeneous (RSH) where the RSH algebras can be chosen so that projections can be lifted along an (F, η)-connected decomposition,

2 A ∈ A =

⇒ T(A) has finitely many extreme points, each of which induce the same state on K0(A).

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 2 / 18

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Theorem (S.–Winter)

Let A, B ∈ A. Then A ⊗ Z ∼ = B ⊗ Z ⇐ ⇒ Ell(A ⊗ Z) ∼ = Ell(B ⊗ Z)

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 3 / 18

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Theorem (S.–Winter)

Let A, B ∈ A. Then A ⊗ Z ∼ = B ⊗ Z ⇐ ⇒ Ell(A ⊗ Z) ∼ = Ell(B ⊗ Z)

Corollary

Let A, B ∈ A and suppose that A and B have finite decomposition rank. Then A ∼ = B ⇐ ⇒ Ell(A) ∼ = Ell(B)

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 3 / 18

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Key tools

1 Tensor with a UHF algebra to care of the lack of projections.

UHF-stable classification can (often) be used to deduce Z-stable classification (eg. Winter, Lin).

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 4 / 18

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Key tools

1 Tensor with a UHF algebra to care of the lack of projections.

UHF-stable classification can (often) be used to deduce Z-stable classification (eg. Winter, Lin).

2 Tracial approximation for A ⊗ Q, for the universal UHF algebra Q

(i.e. K0(Q) ∼ = Q).

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 4 / 18

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Key tools

1 Tensor with a UHF algebra to care of the lack of projections.

UHF-stable classification can (often) be used to deduce Z-stable classification (eg. Winter, Lin).

2 Tracial approximation for A ⊗ Q, for the universal UHF algebra Q

(i.e. K0(Q) ∼ = Q). We will show that A ∈ A = ⇒ A ⊗ Q is a tracially approximately interval algebra (TAI).

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 4 / 18

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Key tools

1 Tensor with a UHF algebra to care of the lack of projections.

UHF-stable classification can (often) be used to deduce Z-stable classification (eg. Winter, Lin).

2 Tracial approximation for A ⊗ Q, for the universal UHF algebra Q

(i.e. K0(Q) ∼ = Q). We will show that A ∈ A = ⇒ A ⊗ Q is a tracially approximately interval algebra (TAI). Then (Lin, 2009) = ⇒ classification.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 4 / 18

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Tracial approximation

A is tracially approximately S: F ⊂ǫ     (1−p)A(1−p) B     p = 1B, B ∈ S

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 5 / 18

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Tracial approximation

A is tracially approximately S: F ⊂ǫ     (1−p)A(1−p) B     p = 1B, B ∈ S x ∈ A then x ≈ pxp + (1 − p)x(1 − p)

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 5 / 18

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Tracial approximation

A is tracially approximately S: F ⊂ǫ     (1−p)A(1−p) B     p = 1B, B ∈ S x ∈ A then x ≈ pxp + (1 − p)x(1 − p) where τ(1 − p) < ǫ for every τ ∈ T(A)

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 5 / 18

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Tracial approximation

A is tracially approximately S: F ⊂ǫ     (1−p)A(1−p) B     p = 1B, B ∈ S x ∈ A then x ≈ pxp + (1 − p)x(1 − p) where τ(1 − p) < ǫ for every τ ∈ T(A) and pxp ∈ǫ B.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 5 / 18

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Tracial approximation

A is tracially approximately S: F ⊂ǫ     (1−p)A(1−p) B     p = 1B, B ∈ S x ∈ A then x ≈ pxp + (1 − p)x(1 − p) where τ(1 − p) < ǫ for every τ ∈ T(A) and pxp ∈ǫ B. I = {(⊕K

k=1C([0, 1]) ⊗ Mnk) ⊕ (⊕L l=1Mnl)}

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 5 / 18

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Main theorem

Theorem (S.–Winter)

Let A ∈ A. Then A ⊗ Q is TAI.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 6 / 18

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Main theorem

Theorem (S.–Winter)

Let A ∈ A. Then A ⊗ Q is TAI. Recall: A is the class of separable nuclear unital simple C ∗-algebras satisfying

1 A ∈ A =

⇒ A is locally recursive subhomoeneous (RSH) where the RSH algebras can be chosen so that projections can be lifted along an (F, η)-connected decomposition,

2 A ∈ A =

⇒ T(A) has finitely many extreme points, each of which induce the same state on K0(A).

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 6 / 18

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Recursive subhomogeneous C ∗-algebras

[Phillips 2001] B is RSH if it can be written as an iterated pullback B =

  • . . .
  • C0 ⊕C (0)

1

C1

  • ⊕C (0)

2

C2

  • . . .
  • ⊕C (0)

R CR,

where Cl = C(Xl) ⊗ Mnl for some compact metrizable Xl and C (0)

l

= C(Ωl) ⊗ Mnl for a closed subset Ωl ⊂ Xl.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 7 / 18

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Recursive subhomogeneous C ∗-algebras

The lth stage Bl is given by Bl = Bl−1 ⊕C (0)

l

Cl = {(b, c) ∈ Bl−1 ⊕ Cl | φ(b) = ρ(c)} where φ : Bl−1 → C (0)

l

is a unital ∗-homomorphism, and ρ : Cl → C (0)

l

is the restriction map.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 8 / 18

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The decomposition is not unique, so we keep track of it: [Bl, Xl, Ωl, nl, φl]R

l=1.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 9 / 18

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The decomposition is not unique, so we keep track of it: [Bl, Xl, Ωl, nl, φl]R

l=1.

We say that projections can be lifted along this decomposition if: ∀n ∈ N, ∀l = 1, . . . , R − 1 and for every projection p ∈ Bl ⊗ Mn, there exists a projection ˜ p ∈ Bl+1 ⊗ Mn lifting p.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 9 / 18

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The decomposition is not unique, so we keep track of it: [Bl, Xl, Ωl, nl, φl]R

l=1.

We say that projections can be lifted along this decomposition if: ∀n ∈ N, ∀l = 1, . . . , R − 1 and for every projection p ∈ Bl ⊗ Mn, there exists a projection ˜ p ∈ Bl+1 ⊗ Mn lifting p.

Proposition

If dim(Xl) ≤ 1 for l = 2, . . . , R then projections can be lifted along [Bl, Xl, Ωl, nl, φl]R

l=1.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 9 / 18

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Idea of proof (A ∈ A = ⇒ A TAI):

Given F ⊂⊂ A ⊗ Q, ǫ > 0, need C ∈ I with τ(1C) bounded away from 0, ∀τ,

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 10 / 18

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Idea of proof (A ∈ A = ⇒ A TAI):

Given F ⊂⊂ A ⊗ Q, ǫ > 0, need C ∈ I with τ(1C) bounded away from 0, ∀τ, and 1C commutes up to ǫ with f ∈ F

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 10 / 18

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Idea of proof (A ∈ A = ⇒ A TAI):

Given F ⊂⊂ A ⊗ Q, ǫ > 0, need C ∈ I with τ(1C) bounded away from 0, ∀τ, and 1C commutes up to ǫ with f ∈ F and that approximates 1C F 1C up to ǫ. Assume τ0, τ1 are the only extreme tracial states.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 10 / 18

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Idea of proof (A ∈ A = ⇒ A TAI):

Given F ⊂⊂ A ⊗ Q, ǫ > 0, need C ∈ I with τ(1C) bounded away from 0, ∀τ, and 1C commutes up to ǫ with f ∈ F and that approximates 1C F 1C up to ǫ. Assume τ0, τ1 are the only extreme tracial states. W.L.O.G., assume F = F0 ⊗{1Q} with F0 ⊂⊂ RSH algebra B.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 10 / 18

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Idea of proof (A ∈ A = ⇒ A TAI):

Given F ⊂⊂ A ⊗ Q, ǫ > 0, need C ∈ I with τ(1C) bounded away from 0, ∀τ, and 1C commutes up to ǫ with f ∈ F and that approximates 1C F 1C up to ǫ. Assume τ0, τ1 are the only extreme tracial states. W.L.O.G., assume F = F0 ⊗{1Q} with F0 ⊂⊂ RSH algebra B. Find a tracially large interval: Take a ∈ (A ⊗ Q)+ with τ0(a) ≈ 0 and τ(a) ≈ 1 (Brown–Toms 2007), then take C ∗(a, 1).

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 10 / 18

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Idea of proof (A ∈ A = ⇒ A TAI):

Given F ⊂⊂ A ⊗ Q, ǫ > 0, need C ∈ I with τ(1C) bounded away from 0, ∀τ, and 1C commutes up to ǫ with f ∈ F and that approximates 1C F 1C up to ǫ. Assume τ0, τ1 are the only extreme tracial states. W.L.O.G., assume F = F0 ⊗{1Q} with F0 ⊂⊂ RSH algebra B. Find a tracially large interval: Take a ∈ (A ⊗ Q)+ with τ0(a) ≈ 0 and τ(a) ≈ 1 (Brown–Toms 2007), then take C ∗(a, 1). Must move this interval into position (w.r.t. F): model an interval in B ⊗ Q, use strict comparison.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 10 / 18

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Interval model: excisors and bridges

Definition

B unital RSH with decomposition [Bl, Xl, Ωl, nl, φl], F ⊂⊂ B+

1 , η > 0. An

(F, η)-excisor (E, ρ, σ, κ) consists of

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 11 / 18

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Interval model: excisors and bridges

Definition

B unital RSH with decomposition [Bl, Xl, Ωl, nl, φl], F ⊂⊂ B+

1 , η > 0. An

(F, η)-excisor (E, ρ, σ, κ) consists of

1 a finite dimensional algebra E = ⊕R

l=1El,

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 11 / 18

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Interval model: excisors and bridges

Definition

B unital RSH with decomposition [Bl, Xl, Ωl, nl, φl], F ⊂⊂ B+

1 , η > 0. An

(F, η)-excisor (E, ρ, σ, κ) consists of

1 a finite dimensional algebra E = ⊕R

l=1El,

2 a unital ∗-homomorphism ρ = ⊕R

l=1ρl : B → ⊕R l=1El

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 11 / 18

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Interval model: excisors and bridges

Definition

B unital RSH with decomposition [Bl, Xl, Ωl, nl, φl], F ⊂⊂ B+

1 , η > 0. An

(F, η)-excisor (E, ρ, σ, κ) consists of

1 a finite dimensional algebra E = ⊕R

l=1El,

2 a unital ∗-homomorphism ρ = ⊕R

l=1ρl : B → ⊕R l=1El

3 an isometric c.p. order zero map σ = ⊕R

l=1σl : ⊕R l=1El → B ⊗ Q

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 11 / 18

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Interval model: excisors and bridges

Definition

B unital RSH with decomposition [Bl, Xl, Ωl, nl, φl], F ⊂⊂ B+

1 , η > 0. An

(F, η)-excisor (E, ρ, σ, κ) consists of

1 a finite dimensional algebra E = ⊕R

l=1El,

2 a unital ∗-homomorphism ρ = ⊕R

l=1ρl : B → ⊕R l=1El

3 an isometric c.p. order zero map σ = ⊕R

l=1σl : ⊕R l=1El → B ⊗ Q such

that σ(1E)(b ⊗ 1Q) = σ ◦ ρ(b) < η for all b ∈ F,

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 11 / 18

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Interval model: excisors and bridges

Definition

B unital RSH with decomposition [Bl, Xl, Ωl, nl, φl], F ⊂⊂ B+

1 , η > 0. An

(F, η)-excisor (E, ρ, σ, κ) consists of

1 a finite dimensional algebra E = ⊕R

l=1El,

2 a unital ∗-homomorphism ρ = ⊕R

l=1ρl : B → ⊕R l=1El

3 an isometric c.p. order zero map σ = ⊕R

l=1σl : ⊕R l=1El → B ⊗ Q such

that σ(1E)(b ⊗ 1Q) = σ ◦ ρ(b) < η for all b ∈ F,

4 a unital ∗-homomorphism κ : E → Q. Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 11 / 18

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Interval model: excisors and bridges

We say that (E, ρ, σ, κ) is compatible with the RSH decomposition if each ρl factorizes through B

ψl

  • ρl

El

Bl

ˇ ψl

C( ˇ

Xl) ⊗ Mrl

ˇ ρl

  • for some compact ˇ

Xl ⊂ Xl \ Ωl.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 12 / 18

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Interval model: excisors and bridges

Definition

An (F, η)-bridge between (E0, ρ0, σ0, κ0) and (E1, ρ1, σ1, κ1) consists of K ∈ N and (F, η)-excisors (Ej/K, ρj/K, σj/K, κj/K), j = 1, . . . , K − 1 satisfying κj/K ◦ ρj/K(b) − κ(j+1)/K ◦ ρ(j+1)/K(b) < η for all b ∈ F and j = 0, . . . , K − 1.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 13 / 18

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Interval model: excisors and bridges

Definition

An (F, η)-bridge between (E0, ρ0, σ0, κ0) and (E1, ρ1, σ1, κ1) consists of K ∈ N and (F, η)-excisors (Ej/K, ρj/K, σj/K, κj/K), j = 1, . . . , K − 1 satisfying κj/K ◦ ρj/K(b) − κ(j+1)/K ◦ ρ(j+1)/K(b) < η for all b ∈ F and j = 0, . . . , K − 1. In this case, write (E0, ρ0, σ0, κ0) ∼(F,η) (E1, ρ1, σ1, κ1).

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 13 / 18

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(F, η)-connected decomposition

[Bl, Xl, Ωl, nl, φl]R

l=1 the RSH decomposition.

For every l = 1, . . . , R and every x ∈ Xl we can define an (F, η)-excisor.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 14 / 18

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(F, η)-connected decomposition

[Bl, Xl, Ωl, nl, φl]R

l=1 the RSH decomposition.

For every l = 1, . . . , R and every x ∈ Xl we can define an (F, η)-excisor. The decomposition is (F, η)-connected if, for any l = 1, . . . , R and any x, y ∈ Xl, we can always find an (F, η)-bridge between their corresponding (F, η)-excisors.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 14 / 18

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Interval model: large trace

With a suitable calculus for (F, η)-excisors, we can find (E0, ρ0, σ0, κ0) and (E1, ρ0, σ0, κ0) with τi(σ(1Ei)) large and τi(σj(1Ej)) small, i = j ∈ {0, 1}.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 15 / 18

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Interval model: large trace

With a suitable calculus for (F, η)-excisors, we can find (E0, ρ0, σ0, κ0) and (E1, ρ0, σ0, κ0) with τi(σ(1Ei)) large and τi(σj(1Ej)) small, i = j ∈ {0, 1}. It remains to find an (F, η)-bridge through the decomposition.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 15 / 18

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Interval model: large trace

With a suitable calculus for (F, η)-excisors, we can find (E0, ρ0, σ0, κ0) and (E1, ρ0, σ0, κ0) with τi(σ(1Ei)) large and τi(σj(1Ej)) small, i = j ∈ {0, 1}. It remains to find an (F, η)-bridge through the decomposition. To do this, we use linear algebra based on equations which we can read off the RSH decomposition.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 15 / 18

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Interval model: large trace

With a suitable calculus for (F, η)-excisors, we can find (E0, ρ0, σ0, κ0) and (E1, ρ0, σ0, κ0) with τi(σ(1Ei)) large and τi(σj(1Ej)) small, i = j ∈ {0, 1}. It remains to find an (F, η)-bridge through the decomposition. To do this, we use linear algebra based on equations which we can read off the RSH decomposition. This is where we require that projections can be lifted and that each tracial state induces the same state on K0.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 15 / 18

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What we get...

With two extreme tracial states τ0, τ1, we find (F, η)-excisors (E0, ρ0, σ0, κ0) ∼(F,η) (E1, ρ1, σ1, κ)

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 16 / 18

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What we get...

With two extreme tracial states τ0, τ1, we find (F, η)-excisors (E0, ρ0, σ0, κ0) ∼(F,η) (E1, ρ1, σ1, κ) such that (τi ⊗ τQ)(σi(1Ei)) ≥ 1/3.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 16 / 18

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What we get...

With two extreme tracial states τ0, τ1, we find (F, η)-excisors (E0, ρ0, σ0, κ0) ∼(F,η) (E1, ρ1, σ1, κ) such that (τi ⊗ τQ)(σi(1Ei)) ≥ 1/3. Now use strict comparison to move the elements in a partition of unity of the actual interval under this model.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 16 / 18

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What we get...

With two extreme tracial states τ0, τ1, we find (F, η)-excisors (E0, ρ0, σ0, κ0) ∼(F,η) (E1, ρ1, σ1, κ) such that (τi ⊗ τQ)(σi(1Ei)) ≥ 1/3. Now use strict comparison to move the elements in a partition of unity of the actual interval under this model. This will be an interval which is large in trace, and the condition σ(1E)(b ⊗ 1Q) = σ ◦ ρ(b) < η for all b ∈ F, for (F, η)-excisors allows us to properly approximate elements in the finite subset.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 16 / 18

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What we get...

With two extreme tracial states τ0, τ1, we find (F, η)-excisors (E0, ρ0, σ0, κ0) ∼(F,η) (E1, ρ1, σ1, κ) such that (τi ⊗ τQ)(σi(1Ei)) ≥ 1/3. Now use strict comparison to move the elements in a partition of unity of the actual interval under this model. This will be an interval which is large in trace, and the condition σ(1E)(b ⊗ 1Q) = σ ◦ ρ(b) < η for all b ∈ F, for (F, η)-excisors allows us to properly approximate elements in the finite subset. A ⊗ Q is TAI.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 16 / 18

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Main theorem

Theorem (S.–Winter)

Let A, B ∈ A. Then A ⊗ Z ∼ = B ⊗ Z ⇐ ⇒ Ell(A ⊗ Z) ∼ = Ell(B ⊗ Z).

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 17 / 18

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SLIDE 50

Main theorem

Theorem (S.–Winter)

Let A, B ∈ A. Then A ⊗ Z ∼ = B ⊗ Z ⇐ ⇒ Ell(A ⊗ Z) ∼ = Ell(B ⊗ Z). Where A is the class of separable nuclear unital simple C ∗-algebras satisfying

1 A ∈ A =

⇒ A is locally recursive subhomoeneous (RSH) where the RSH algebras can be chosen so that projections can be lifted along an (F, η)-connected decomposition,

2 A ∈ A =

⇒ T(A) has finitely many extreme points, each of which induce the same state on K0(A).

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 17 / 18

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Some consequences

  • 1. Elliott 1996 – Simple approximately SH algebras constructed by

attaching 1-dimensional spaces to the circle. Theorem = ⇒ classification when restricted to finitely many extreme tracial states, each inducing same K0-state.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 18 / 18

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Some consequences

  • 1. Elliott 1996 – Simple approximately SH algebras constructed by

attaching 1-dimensional spaces to the circle. Theorem = ⇒ classification when restricted to finitely many extreme tracial states, each inducing same K0-state.

  • 2. Lin–Matui 2005 – A := C(X × T) ⋊ Z. Restricting to finitely many

traces each inducing same state on K0, theorem = ⇒ A{x} ⊗ Q is TAI, then (S.-Winter 2010) = ⇒ A ⊗ Q TAI = ⇒ classification.

Karen R. Strung (University of M¨ unster) UHF slicing March 14, 2013 18 / 18