Descriptive Properties of Measure Preserving. Actions and the Associated Unitary Representations. Tzer-jen Wei. Thesis by

Size: px
Start display at page:

Download "Descriptive Properties of Measure Preserving. Actions and the Associated Unitary Representations. Tzer-jen Wei. Thesis by"

Transcription

1 Descriptive Properties of Measure Preserving Actions and the Associated Unitary Representations Thesis by Tzer-jen Wei In Partial Fulllment of the Requirements for the Degree of Doctor of Philosophy California Institue of Technology Pasadena, California 2005 (Defended May 12, 2005)

2 ii c 2005 Tzer-jen Wei All Rights Reserved

3 iii Acknowledgements I would like to thank my advisor, Alekos Kechris, for his instruction, patience, and support in my graduate studies and while I was preparing this work. Thanks also to John Clemens, Christian Rosendal, Orestis Raptis, Todor Tsankov for listening to my presentations and providing useful feedback. I am grateful to the Department of Mathematics at Caltech for its support during my graduate study program and for providing a great environment for research. Finally, I would like to thank my parents and my sister for their encouragement and personal support.

4 iv Abstract Let be a countable group and X a Borel -space with invariant Borel probability measure µ. Let E = E be the countable equivalence relation dened by xey γ (γ x = y). This thesis consists of two independent parts, Chapter 2 and Chapter 3: In Chapter 2, we study the descriptive complexity of the full group [E]. The main result of this chapter is i) If E is not smooth, then [E] is Π 0 3-complete; ii) If E is smooth, then [E] is closed. We also study the descriptive complexity of N[E], the normalizer of [E]. It turns out that N[E] has the same complexity as [E], i.e., N[E] is Π 0 3-complete i E is not smooth and is closed if E is smooth. In Chapter 3, we study descriptive properties of π X, the Koopman unitary representation associated with the action. Consider the induced Polish action on L 2 (X), i.e., γ f = π X (γ)(f). Denote by E L2 (X) the induced countable Borel equivalence relation on L 2 (X), i.e., fe L2 (X) g γ (g = γ f).

5 v Let act on the measure algebra of µ, MALG µ, by γ A = γ(a) and on Aut(X, µ) by γ T = π X (γ)t. We have the induced countable equivalence relations E MALGµ and E Aut(X,µ) respectively. We relate the descriptive complexity of E L2 (X) to that of E X. We show that the smoothness of EL2 (X) is equivalent to the smoothness of E MALGµ and the compressibility of the nonconstant part of E L2 (X) is equivalent to the compressibility of E MALGµ\{X, }. We also connect the smoothness and compressibility of E L2 (X) to mixing properties of the action of on X. Finally, we will show that the amenability of E X implies a certain weak containment property of πx.

6 vi Contents Acknowledgements iii Abstract iv Chapter 1. Introduction 1 Chapter 2. Descriptive Complexity of Full Groups Full groups and their normalizers Upper bound of the complexity of [E] and N(E) Smooth equivalence relations and the closure of [E] The Descriptive Complexity of [E] and N(E) N(E) as a Polishable group 18 Chapter 3. Descriptive Properties of Measure Preserving Actions and the Associated Unitary Representations Introduction Smoothness of E L2 (X,µ) Compressibility Some Embedding and Containment Results 60 Bibliography 74

7 1 CHAPTER 1 Introduction Let be a countable group and X a standard Borel -space with an invariant (nonatomic) Borel probability measure µ. induces an equivalence relation E X on X, which is dened by xe X y γ (γ x = y). By a theorem of Feldman-Moore (see [KM], Theorem 1.3), every countable Borel equivalence relation on a standard Borel space X is induced by some Borel action of some countable group. Denote by Aut(X, µ) the group of µ-measure preserving automorphisms of X (modulo null sets). For each T Aut(X, µ), we can dene a corresponding unitary operator U T U(L 2 (X)), U T (f) = f T 1. And by identifying T and U T, we can view Aut(X, µ) as a subgroup of U(L 2 (X)). The weak topology of Aut(X, µ) is the subspace topology of the weak topology on U(L 2 (X)). Aut(X, µ) is a closed subspace of U(L 2 (X) in the weak topology, hence Polish. In Chapter 2, we will study the descriptive complexity of an important invariant of E, namely the full group of E. The full group of E, denoted by [E], is dened by [E] = {T Aut(X, µ) : xet x a.e.}. The main result of this chapter is i) If E is not smooth, then [E] is Π 0 3-complete. ii) If E is smooth, then [E] is closed. And the same result holds for N[E]:

8 2 i) If E is not smooth, then N[E] is Π 0 3-complete. ii) If E is smooth, then N[E] is closed. Dene π X : Aut(X, µ) U(L 2 (X)), γ T, where T is the element in Aut(X, µ) such that T (x) = γ x for µ-almost every x X. Or equivalently T (f) = U T (f) = f(γ 1 ) for every f L 2 (X). Clearly π X is a homomorphism of into U(L 2 (X)), i.e., π X is a unitary representation of on the Hilbert space L 2 (X). The unitary representation π X induces a natural Polish action on L 2 (X), i.e., γ f = π X (γ)(f). Denote by E L2 (X) the induced countable Borel equivalence relation on L 2 (X), i.e., fe L2 (X) g γ (g = γ f). In Chapter 3, we will study relations between E X and EL2 (X). We will obtain characterizations of the smoothness and compressibility of E L2 (X) and reducibility results. Denote by MALG µ the measure algebra of µ (see Section 3.1.2). Let act on MALG µ by γ A = γ(a). Similarly, we have the induced equivalence relation E MALGµ dened by AE MALGµ B γ (B = γ A).

9 3 We will show that E L2 (X) is smooth i E MALGµ is smooth and the nonconstant part of E L2 (X) is compressible i E MALGµ\{X, } is compressible. These descriptive properties of E L2 (X) also have connections with mixing properties of the action: i) If action is mildly mixing, then E L2 (X) is smooth. ii) The nonconstant part of E L2 (X) is compressible i the action is weakly mixing. Furthermore, we will show that smoothness is related to rigid factors and compressibility is related to isometric factors. At the end of this chapter, we will study some embedding properties, containment properties, and their applications. Denote by λ the regular unitary representation of and by λ /x the quasi-regular unitary representation on λ /x. If the action is amenable, then π X λ (see [Kuhn]). We show that if E X is amenable, then π X X λ / x dµ(x).

10 4 CHAPTER 2 Descriptive Complexity of Full Groups 2.1. Full groups and their normalizers Let µ be a Borel probability measure dened on a standard Borel space X. Recall that Aut(X, µ) denotes the group of all measure preserving Borel isomorphisms (modulo null sets) on X. There are two frequently used topologies dened on Aut(X, µ), namely the uniform topology and the weak topology. Let's use B(X) to denote the set of Borel subsets of X and A = {A n } an algebra generating B(X). The uniform topology has as basis the sets of the form V T,ɛ = {S Aut(X, µ) : sup{µ(s(a) T (A)) : A B(X)} < ɛ}. It has two compatible metrics: d 1 (S, T ) = µ{x S(x) T (x)} and d 2 (S, T ) = sup{µ(s(a) T (A)) A B(X)} = sup{µ(s(a n ) T (A n ))}. n N Aut(X, µ) is not separable in the uniform topology.

11 The weak topology has as sub-basis the sets of the form 5 W T,An,ε = {S µ(s(a n ) T (A n )) < ε} and a complete and compatible metric: ρ(s, T ) = 2 n (µ(s(a n ) T (A n )) + µ(s 1 (A n ) T 1 (A n ))). Aut(X, µ) is a Polish group in the weak topology. Now consider a countable Borel equivalence relation E dened on a standard Borel space X. By Theorem 1.3 in [KM], E is induced by Borel action of a countable group G acting on X, i.e., E = E G, xey g G(g x = y). We call a Borel measure µ on X E-invariant if µ is G-invariant for every countable Borel group G such that E G = E. Dene for µ that which is E invariant [E] = {T Aut(X, µ) : xet x a.e.} and let N(E) Aut(X, µ) be the normalizer of [E], i.e., N(E) = {T Aut(X, µ) : T 1 [E]T = [E]}. The goal of this chapter is to determine the descriptive complexity of the full groups of countable Borel equivalence relations and their normalizers in the weak topology.

12 Upper bound of the complexity of [E] and N(E) Let {f n } [E] be a Cauchy sequence in the uniform topology and assume n m > n d 1 (f n, f m ) < 2 n. For each n N, let Y n = {x m > n(f m (x) = f n (x))}. We have µ(y n ) > 1 2 n, and dene f : X X by f(x) = f n (x) if x Y n. Clearly f is well-dened µ-almost everywhere and is in [E]. Since d 1 (f, f n ) < 2 n, we have f = lim f n. Therefore [E] is complete in the uniform topology In general, [E] is not closed in the weak topology. For example, consider the Vitali equivalence relation E 0 on (X, µ) = ([0, 1], m), xe 0 y i 2 n (x y) N for some n N. Since E 0 is ergodic, for all measurable subsets A, B X, T [E 0 ] (T (A) = T (B) i µ(a) = µ(b). So clearly [E 0 ] = Aut(X, µ) in the weak topology. But [E 0 ] Aut(X, µ) (for example x x + π mod 1 is in Aut(X, µ)\[e 0 ]), thus [E 0 ] is not closed in the weak topology. More generally, let E be an ergodic countable Borel equivalence relation. Then [E] = Aut(X, µ) by the same reason above. We may assume (X, µ) = ([0, 1], m) and consider f r : x x + r mod 1. We have f r Aut(X, µ) and d 1 (f r1, f r2 ) = 1 if r 1 r 2, therefore Aut(X, µ) is not separable in the uniform topology. However, by the following proposition, we can show that [E] is separable in the uniform topology, hence [E] Aut(X, µ) = [E] in the weak topology. Proposition If E is a countable Borel equivalence relation on a standard Borel space X with invariant probability measure µ, then [E] is separable in the uniform topology.

13 7 Proof. Let T, S : X X be Borel maps. Consider the equivalence relation T S µ x(t (x) = S(x)). Denote by [T ] the equivalence class of T. When T is an automorphism, it is customary to write T instead of [T ] if there is no danger of confusion. To avoid the confusion with the [ ] notation of full groups, we will write the equivalence of T as T instead [T ] for all Borel maps too. So when we write T is Borel (modulo null), we mean the equivalence class of T. Let A = {T T : X X is Borel (modulo null).}. We can view (Aut(X, µ), d 1 ) as a metric subspace of (A, d 1 ). We only need to show that there exists a countable subset S A, such that [E] S. Construct S by the following steps. First, let {P m } be a sequence of nite Borel partitions of X where P m = {A m n }, such that for any nite Borel partition {X n } and ε > 0, there is a P m = {A m n } with n (µ(a m n X n ) < ε). Then since E is countable, we may assume X is a countable Borel G-space and E = E G. Let {g i } be a nite subset of G and {g i } P m, dene S {gi },m by S {gn},m A m n = g n A m n. Let S = {S {gn},m} {gn} <,{g n} G. Then clearly S A and is countable.

14 We only need to show [E] S, that is 8 ε > 0 T [E] S S (d 1 (S, T ) < ε). Since T [E], we can nd a nite subset {g n } n N G and a nite partition {X n } n N such that T X n = g n X n, if n < N, and µ(x N ) < ε. Fix an m so that 2 µ(a m n X n ) < ε 2N. Clearly d 1 (T, S {gn},m) < µ(x N ) + µ(a m n X n ) < ε. Therefore, [E] is separable in the uniform topology. The following proposition gives an upper bound on the Borel complexity of [E]. Proposition If E is a countable Borel equivalence relation on a standard Borel space X with invariant probability measure µ, then [E] is Π 0 3 in the weak topology. Proof. Since [E] is separable in the uniform topology by the above proposition, we can x a countable dense subset {T n } n N [E] in the uniform topology. And since [E] is closed in the uniform topology, we can write [E] = {S : d 2 (S, T n ) < 2 m }. m=1 n=0 Note that {S : d 2 (S, T n ) < 2 m } is an open ball in the d 2 metric. Let A = {A n } be an algebra generating B(X). We can write an open ball in the d 2 metric as

15 9 {S : d 2 (S, T ) < r} = = {S : sup{µ(sa n T A n )} r 2 m } m=1 m=1 n=0 n {S : µ(sa n T A n ) r 2 m }, which is clearly Σ 0 2 in the weak topology. Hence [E] is Π 0 3. We can use this to show that N(E) is in Π 0 3 in the weak topology. Proposition If E is a countable Borel equivalence relation on a standard Borel space X with invariant probability measure µ, and if [E] Π 0 3 in the weak topology, then N(E) Π 0 3 in the weak topology too. In particular, by Proposition 2.2.2, N(E) Π 0 3 in the weak topology. Proof. Let G be a countable group of Borel automorphisms generating E. First note that if T Aut(X, µ) and g G (T gt 1 [E]), then if xey, y = g(x) for some g G, T (y) = T (g(x)) = T gt 1 T (x). Since T gt 1 [E], there is a conull subset Y X, such that x, y Y (xey T (y)et (x)). Similarly if g G (T 1 gt [E]) then there is a conull subset Y X, x, y Y (T (x)et (y) xey). So if g G (T gt 1 [E]) and g G (T 1 gt [E]), then T N(E).

16 On the other hand, if T N[E], then 10 T 1 [E]T = [E] = T [E]T 1, so g G [E], T gt 1 [E], and T 1 gt [E]. Therefore, N(E) = g G{T T gt 1 [E]} {T T 1 gt [E]}. Clearly T T gt 1 and T T 1 gt (for any g G) are continuous maps from Aut(X, µ) to itself, and reduce {T T gt 1 [E]} and {T T 1 gt [E]} to [E], respectively. Therefore N(E) is Π Smooth equivalence relations and the closure of [E] To determine the exact complexity of [E], the simplest case is when E is µ- smooth, i.e., E Y = F Y, where F is smooth and Y X is µ-conull. We can even slightly loosen our conditions. Consider a (not necessarily countable) Borel equivalence relation F on X, andconsider µ a (not necessarily F -invariant) Borel probability measure on X. We dene [F ] = {T Aut(X, µ) µx (T (x)f x)} (which extends the concept of the full group to general Borel equivalence relations). We have the following simple proposition:

17 11 Proposition Let F be a Borel equivalence relation on a standard Borel space X with a Borel probability measure µ. If F is smooth, then [F ] is closed in the weak topology of Aut(X, µ). Proof. F is smooth, hence F B ([0, 1]). Let f : X [0, 1] be a Borel function such that xf y i f(x) = f(y). Then the assignment T f T is a continuous map from Aut(X, µ) to L 2 (X). Note that T [F ] i ft = f (modulo null sets), hence [F ] is closed. Notice that if two Borel equivalence relations F 1 and F 2 agree a.e. in the sense that F 1 Y = F 2 Y for some co-null subset Y X, then [F 1 ] = [F 2 ]. We have: Corollary Let F be a Borel equivalence relation on a standard Borel space X with a Borel probability measure µ. If F is µ-smooth, then [F ] is closed in the weak topology of Aut(X, µ). It remains to nd the complexity of E when it is not µ-smooth. Lemma If E is a countable Borel equivalence relation on a standard Borel space X with invariant probability measure µ, then [E] is closed or Σ 0 2 -hard. Proof. If [E] is not closed, then T [E]\[E]. If [E] is Π 0 2, then since [E] is dense in [E], [E] is comeager in [E]. Hence the coset [E]T is also comeager in [E], but [E] ([E]T ) =, a contradiction. Therefore [E] is not Π 0 2, so it is Σ 0 2 -hard (see [Kechris 2], Theorem 22.10). It makes sense to see what [E] is. Recall the uniform ergodic decomposition for invariant measures of E. Denote by P (X) the set of probability measures on X, by I E P (X) the set of E-invariant Borel probability measures on X and by

18 12 EI E P (X) the set of E-invariant ergodic Borel probability measures on X. We have (see [KM], Theorem 3.3) Theorem (Farrell, Varadarajan) Let E be a countable Borel equivalence relation on a standard Borel space X. Assume I E 0. Then there is a unique (up to null sets) Borel surjection π : X EI E such that (1) π(x) = π(y) if xey; (2) If X e = {x : π(x) = e}, for e EI E, then e(x e ) = 1; (3) For any µ I E, µ = π(x)dµ(x). So we can write EI E = {e x }, where e x = π(x). From now on, we will use the above notations: π, X e to denote the unique ergodic decomposition of (X, E) and F to denote the Borel equivalence relation on X, which is dened by xf y i π(x) = π(y). Since F is smooth, [F ] is closed by and clearly [E] [F ]. Furthermore, we can show that [F ] is the closure of [E]. Theorem Let E be a countable Borel equivalence relation on a standard Borel space X with invariant probability measure µ. Given S [F ] and a Borel set A, then there is a T [E], such that T (A) = S(A). Proof. Let Y be an F - invariant Borel set. Then T (A Y ) = T (A) T (Y ) = T (A) Y, hence µ(a Y ) = µ(t (A) Y ). Consider the set Y = {x : e x (A) > e x (T (A))}. If µ(y ) > 0, then µ(a Y ) > µ(t (A) Y ). But Y is F -invariant, so this contradicts that µ(a Y ) = µ(t (A) Y ). So µ(y )=0. We may assume therefore that x X, e x (A) = e x (T (A)) > 0.

19 13 By a well-known lemma (see [Kechris 3], p.117, Lemma 4.50), there are disjoint E-invariant sets P,Q, and R, such that [A] [T (A)] = P Q R, and A P T (A) P, T (A) Q A Q, A R T (A) R. But P, Q are also F -invariant, µ(a P ) = µ(t (A) P ), µ(a Q) = µ(t (A) Q), so µ(p ) = µ(q) = 0, A T (A). Corollary [F ] is the closure of [E]. Proof. We only need to show that [E] is dense in [F ]. Recall that weak topology of Aut(X, µ) has as basis the sets of the form U S,P,ε = A P{T : µ(t (A) S(A)) < ε}, where S Aut(X, µ), P is a nite Borel partition of X, and ε > 0 is a real. Fix an arbitrary S [F ], a nite Borel partition P = {A i } and an ε > 0. By Theorem 2.3.5, there is a T i [E] such that T i (A i ) = S(A i ) for each A i P. Let T = (T i A i ). Since S is an automorphism, {S(A i )} is a Borel partition. Thus T Aut(X, µ). Since T (x) = T i (x)ex for some i, T [E]. Finally, µ(t (A i ) S(A i )) = µ(t i (A i ) S(A i )) = 0 < ε. Therefore, [E] = [F ]. For a countable Borel E, we can divide E into the periodic part and the aperiodic part, E = E aperiodic E periodic. The periodic part is smooth, E = F in this part. So we only need to deal with the case that E is aperiodic. We have the following isomorphism theorem for (X, F, µ):

20 14 Lemma Let E be a countable Borel equivalence relation on a standard Borel space X with a nonatomic invariant probability measure µ. If E is aperiodic, then (X, µ, F ) = (EI E [0, 1], πµ m, I). Proof. By the isomorphism theorem of standard Borel spaces with nonatomic probability measures (see [Kechris 2], Theorem 17.41), we can assume (X, µ) = ([0, 1], m). Dene f : X EI E [0, 1] x (π(x), π(x)([0, x])) and g : EI E [0, 1] X (e, r) inf{y e([0, y]) r}. Clearly, f and g are Borel, and since gf(x) = g(π(x), π(x)([0, x])) = inf{y π(x)([0, y]) π(x)([0, x])} = inf{y π(x)([y, x]) = 0}.

21 15 Let A = {x gf(x) x}, we have A = {x y < x π(x)([y, x]) = 0} = n N{x π(x)([x 2 n, x]) = 0} Also let A n = {x π(x)([x 2 n, x]) = 0}. It is easy to see that e(a n ) = e(a n X e ) = 0 for all e EI, therefore µ(a n ) = 0, hence µ( A n ) = µ(a) = 0. That is gf(x) = x almost everywhere. It is easy to check that fµ = πµ m and note that f(x e ) = {e} [0, 1], hence (X, µ, F ) = (EI E [0, 1], πµ m, I) The Descriptive Complexity of [E] and N(E) By we know that [E] is either closed or Σ 0 2-hard. In fact, we can show that in the case that [E] is not closed, [E] is not only Σ 0 2-hard but also Π 0 3-complete: Proposition If E is a countable Borel equivalence relation on a standard Borel space X with invariant probability measure µ, then [E] is closed or Π 0 3 -complete. Proof. Assume [E] is not closed. We claim that we can nd a Borel partition {Y i } i N of X, such that µ(y i ) > 0 and [E Y i ] are not closed (hence Σ 0 2-hard by 2.3.3) in Aut(Y i, µ Y i ). Granting this, since [E Y i ] is Σ 0 2-hard, we have Q 2 c [E Y i ] (where Q 2 = {x C : m n > m (x(n) = 0)} is a Σ 0 2-complete set see [Kechris 2], p.179).

22 16 Dene F : i N Aut(Y i, (µ Y i )/µ(y i )) Aut(X, µ), (f i ) i N f = f i, i.e, f Y i = f i. It is easy to see that F is continuous and (f i ) i N [E Y i ] i(f i [E Y i ]) i((( f i ) Y i [E Y i ]) f [E] where f i Aut(Y i, (µ Y i )/µ(y i ). Therefore i N [E Y i] c [E], hence P 3 = {x 2 N N : m (x m Q 2 )} = Q N 2 c [E Y i ] c [E]. i N Since P 3 is Π 0 3-complete (see [Kechris 2], p.179), [E] is Π 0 3-complete. It remains to show that the claim is true. Let X 0 = X. We will dene X i and Y i = X i \X i+1 inductively. Suppose we already have X i such that µ(x i ) > 0 and [E X i ] is not closed (which is clearly true in the base case that i = 0). We can therefore x a T [E X i ]\[E X i ], and the non-null Borel subset A = X i \{x X i T (x)ex}. Then we simply dene X i+1 and Y i+1 to be any Borel partition of X i such that both X i+1 A and Y i+1 A are not null. That is X i+1 Y i+1 = X i and 0 < µ(x i+1 A) < µ(a), 0 < µ(y i+1 A) < µ(a). By Theorem 2.3.5, there is an S [E X i ] such that S(X i+1 ) = T (X i+1 ). Since S 1 T (x)et (x) Ex

23 17 for almost every x A X i and S 1 T [E X i ], we have S 1 T X i+1 [E X i+1 ]\[E X i ], hence [E X i+1 ] is not closed. Similarly, [E Y i+1 ] is not closed. And since X i = X i+1 Y i+1 and X = X 0, {Y i } is a Borel partition of X. This completes the proof. We are ready to prove our main theorem. Theorem Let E be a countable Borel equivalence relation on a standard Borel space X with invariant probability measure µ. If E is µ-smooth, then [E], N(E) are closed. If E is not µ-smooth, then [E] and N(E) are Π 0 3 -complete. Proof. If E is µ-smooth, the result follows from and For non µ-smooth E, since the periodic part is smooth, we can assume E is aperiodic and, furthermore, by 2.3.7, we can assume that (X, µ, F ) = (EI E [0, 1], πµ m, I). Dene h s : (e, r) (e, r + s mod 1). We have h s [ I] = [F ] and d 0 (h s, h t ) = 1 δ s,t. So [F ] is not separable in the uniform topology, while [E] is, hence [E] [F ], [E] is not closed, and [E] is Π 0 3-complete from To determine the complexity of N[E], by and we can nd a Borel subset Y X, S [E], such that S 2 = 1 and {Y, S(Y )} is a partition of X (modulo null sets). For example, Y = g({(e, r) r < 1}), S = g (λ(e, r).(e, r + 1 mod 1)) f with 2 2

24 18 notations as in Lemma Dene h : Aut(Y, 2µ Y ) Aut(X, µ), T (x) if x Y h(t )(x) = x if x S(Y ). It is easy to check that h is continuous. If T [E Y ], then h(t ) [E] N(E). Conversely, if h(t ) [E], then there is a null subset N X, such that x, y X\N (xey h(t )xeh(t )y). We may also assume S(N) = N, otherwise, just replace N with N S(N). If x Y \N, then Sx S(Y )\N X\N. We have then T (x) = h(t )(x)eh(t )S(x) = S(x)E(x)) for all x Y, hence T [E Y ]. Therefore T [E Y ] i h(t ) N([E]), so [E Y ] c N[E]. Since E Y is not smooth almost everywhere, [E Y ] is Π 0 3-complete. Combining with 2.2.3, N(E) is also Π 0 3-complete N(E) as a Polishable group Let E be a countable Borel equivalence relation on X and µ an E-invariant ergodic Borel probability measure. Consider [E] as a standard Borel subgroup of Aut(X, µ) in the weak topology. Since [E] is a Polish group in the uniform topology and the identity map is a Borel isomorphism between the weak topology and the uniform topology, [E] is Polishable. N(E) is also a subgroup of Aut(X, µ). But N(E) is in general not separable, hence it is not Polish in the uniform topology. However, we can dene a new topology (see [HO], p.91) in the normalizer group N(E) by saying

25 19 that T n T in N(E) i T n converge to T weakly and T n ST 1 n converges to T ST 1 uniformly for all S [E]. It is easy to check that N(E) is a topological group with this topology. In fact N(E) is a Polish group in this topology (see [HO], Lemma 53). It is easy to check that the identity map is a Borel isomorphism between the weak topology and this topology, so N(E) is also Polishable.

26 20 CHAPTER 3 Descriptive Properties of Measure Preserving Actions and the Associated Unitary Representations 3.1. Introduction Measure Preserving Actions and Unitary Representations. Let be a countable group and X a standard Borel -space with an invariant (nonatomic) Borel probability measure µ. induces an equivalence relation E X on X, which is dened by xe X y γ (γ x = y). On the other hand, by a theorem of Feldman-Moore (see [KM], Theorem 1.3), every countable Borel equivalence relation on a standard Borel space X is induced by some Borel action of some countable group. Denote by Aut(X, µ) the group of µ-measure preserving automorphisms of X. For each T Aut(X, µ), we can dene a corresponding unitary operator U T U(L 2 (X)), U T (f) = f T 1. And by identifying T and U T, we can view Aut(X, µ) as a subgroup of U(L 2 (X)). The weak topology of Aut(X, µ) is the subspace topology of the weak topology dened on U(L 2 (X)). Aut(X, µ) is a closed subspace of U(L 2 (X) in the weak topology, hence it is Polish. Dene π X : Aut(X, µ) U(L 2 (X)), γ T, where T is the element in Aut(X, µ) such that T (x) = γ x for µ-almost every x X. Or equivalently T (f) =

27 21 U T (f) = f(γ 1 ) for every f L 2 (X). Clearly π X is a homomorphism of into U(L 2 (X)), i.e., π X is a unitary representation of on the Hilbert space L 2 (X). The unitary representation π X induces a natural Polish action on L 2 (X), i.e., γ f = π X (γ)(f). Denote by E L2 (X) the induced countable Borel equivalence relation on L 2 (X), i.e., fe L2 (X) g γ (g = γ f). If there is no danger of confusion, we will set E L2 (X) = E L2 (X). In this chapter, we will study relations between E X and (X) EL2. We will obtain some characterizations of the smoothness and compressibility of E L2 (X) and some reducibility results The action on MALG µ and Aut(X, µ). Let X be a standard Borel space with Borel probability measure µ. Denote by MEAS µ the σ-algebra of measurable sets and for A, B MEAS µ, let A = µ B µ(a B) = 0 and denote by [A] the equivalence class of A. Let MALG µ = {[A] : A MEAS µ }. Let [A] [B] = [A B] and δ([a], [B]) = µ(a B). Then (MALG µ, ) is an abelian Polish group with invariant metric δ. For every measure preserving automorphism T Aut(X, µ), [A] [T (A)] is a measure algebra automorphism of MALG µ. Conversely, every measure algebra automorphism of MALG µ is of the form [A] [T (A)] for some T Aut(X, µ). Therefore, we can canonically identify Aut(X, µ) and the group of measure algebra preserving automorphisms of MALG µ (see [Kechris 2], p.118). If µ is continuous, MALG µ is independent of µ and called the Lebesgue Measure Algebra. Consider a countable group and X a Borel -space with invariant Borel probability measure µ. There is a action on MALG µ dened by γ [A] = [γ(a)]. This

28 22 action is continuous. The map [A] χ A is a continuous -space embedding of MALG µ into L 2 (X, µ). Assume now that acts on Aut(X, µ) by left translation and Aut(X, µ) acts on L 2 (X) by T f = U T (f). Let f L 2 (X) and denote by Aut(X, µ) f the stabilizer of f, i.e., Aut(X, µ) f = {T Aut(X, µ) : T f = f}. If Aut(X, µ) f = {1}, then T T f is a continuous -space embedding of Aut(X, µ) into L 2 (X). Many such f exist, for example any f L 2 (X) that is an injection of X into C has a trivial Aut(X, µ)-stabilizer Borel Reducibility. Suppose we have Borel equivalence relations E, F on X, Y respectively. If there is a Borel map α : X Y such that x 1 Ex 2 α(x 1 )F α(x 2 ), for all x 1, x 2 X, we say E is Borel reducible to F. Put E B F if E is Borel reducible to F. When α is a reduction and also an injection, E is said to be Borel embedded in F, in symbols E B F. If, moreover, the image of α, α(x), is F -invariant, E is said to be Borel invariantly embedded in F or E i B F. B stands for Borel in the above symbols. We can replace Borel by another class of maps, say in a class A, and generalize the concept and notations to A- reducible, A, etc. For example, for the class of continuous maps, we will denote continuous reducible, embedded, invariantly embedded by c, c, i c, respectively, where c stands for continuous.

29 Smoothness of E L2 (X,µ) Smooth equivalence relations are the simplest relations in the reduction hierarchy. We rst review some basic properties of smooth relations and show there are simple characterizations of the smoothness of E Aut(X,µ) and E MALGµ. Then Theorem shows that the smoothness of E L2 (X) is equivalent to the smoothness of E MALGµ. It turns out the smoothness of these equivalence relations has interesting connections with the concept of rigid factors, which we will discuss in In 3.2.4, we will discuss some relations between mixing properties and smoothness. In the rest of this section, we will develop some techniques to deal with smoothness in some special kinds of -spaces by using the Peter-Weyl theorem, which is sometimes easier than using Theorem directly General Facts on Smooth Relations. Recall that an equivalence relation E on X is (Borel) smooth if E B (Y ), where (Y ) is the equivalence relation dened on some Polish space Y by y 1 (Y )y 2 y 1 = y 2. A selector is a map s : X X such that xey s(x) = s(y). A transversal for E is a set T X that meets each E-class at exactly one point. Having a Borel selector is equivalent to having a Borel transversal and implies smoothness. The converse is not true in general. But in the case that the E is generated by a discrete Borel group action, i.e., E = E for some countable group, the smoothness of E implies the existence of Borel selectors for E (see [KM], Proposition 6.4). Moreover, we have: Theorem Let X be a Borel -space, where is a countable group. Then the following are equivalent:

30 24 i) E is smooth; ii) E has a Borel selector; iii) X/ = X/E is standard Borel (in its quotient σ-algebra); iv) There is a Polish topology T on X compatible with its Borel structure such that E is closed in the product topology (X, T ) (X, T ); v) There is a countable sequence (A n ) of Borel E -invariant subsets of X separating E i.e. [ n(x A n y A n )] [xey]; vi) E 0 cannot be Borel embedded in E X, where E 0 is the equivalence relation on the Cantor space C = 2 N dened by se 0 t n N(s(n) = t(n)). Proposition Let E be a countable Borel equivalence relation on a uncountable Polish space X. i) If every equivalence class of E is G δ, then E is smooth. ii) If E admits a nonatomic ergodic measure, then E is not smooth. iii) If E is generically ergodic (i.e., every invariant Borel subset is either meager or comeager and every class is meager), then E is not smooth. Let X be a Polish metric space. In this case, we have a converse to Proposition (i). Proposition Let X be a Polish metric space, a countable group acting on X by homeomorphisms. The following are equivalent: i) E is smooth; ii) Every orbit is discrete; iii) x X, x is an isolated point in x; iv) The closure of each orbit is not perfect.

31 25 Proof. iii) ii): If γ i x γ x for some x X γ i, γ, then (γ 1 γ i ) x x. So these two conditions are clearly equivalent. ii) i ): Proposition (i). i) iv): Proof by contradiction. Suppose x is perfect for some x X. Note that x is dense in x which is equivalent to the condition that E ( x) is generically ergodic. By Proposition (iii), E ( x) is not smooth. Therefore E is not smooth. iv) iii): If x is a limit point in x, then γ (γ x is a limit point in x). Therefore x is perfect. Assume now acts on (X, µ) by measure preserving automorphisms. Recall that MALG µ and Aut(X, µ) can be embedded into L 2 (X) as -spaces. We have Corollary E MALGµ is smooth i for every Borel subset A X, there is an r > 0 such that µ(γ(a) A) / (0, r) for every γ. E Aut(X,µ) is smooth i π X ()is discrete in the weak topology The Characterization of Smoothness of E L2 (X). Clearly the smoothness of E L2 (X) implies the smoothness of E MALGµ. The converse is also true. Theorem E MALGµ is smooth i E L2 (X) is smooth. Before we prove the theorem, it would be rst convenient to prove the following lemma: Lemma Let X be a standard Borel space with Borel probability measure µ and g, f 0, f 1, f 2 L 2 (X, µ). If f i µ = f j µ for all i, j, then the following are equivalent:

32 26 i) f 1 i (A) g 1 (A) for every analytic A C; ii) f 1 i (A) g 1 (A) for every Borel A C; iii) f 1 i (A) g 1 (A) for every basic open set A C; iv) f i g. Proof. Obviously, i) ii) iii). Put f ω = g. (ii) i)) Assume ii) is true. We may assume f i is Borel for all i ω. Let B i X\f 1 i (A) be a Borel set such that B i = X\f 1 (A) (modulo null). So f i (B i ) is analytic and f i (B i ) A =. Let B = i ω f i(b i ). By the separation theorem (see [Kechris 2] 28.B), there is a Borel set A, such that A A B. We have i f 1 i (A) f 1 i (A ) f 1 i ( B) f 1 i ( B) = X\B i. Since X\B i = f 1 (A) (modulo null), we have f 1 i (A) = f 1 i (A ) for all i ω. Therefore f 1 i (A) = f 1 i (A ) g 1 (A ) = g 1 (A). (iii) ii)) It is easy to check that the convergence property is preserved under complement and nite union, that is [f 1 i (A) g 1 (A)] [f 1 ( A) g 1 ( A)] i and [ k<n (f 1 i (A k ) g 1 (A k ))] [f 1 ( A k ) f 1 ( A k )]. k<n k<n So we only need to check that the convergence property is preserved under countable union. Suppose now f 1 i (A k ) g 1 (A k ) for all k N. We may assume (A k ) is increasing and put A = k N A k. For any ε > 0, we can nd an n large enough so

33 27 that (f 0 µ)(a\a n ) + (gµ)(a\a n ) < ε. Combine with the condition f i µ = f j µ for all i, j < ω, so we actually have (f i µ)(a\a n ) < ε for all i ω. We can also nd m large enough so that µ(f 1 i (A n ) g 1 (A n )) < ε for all i > m. Therefore, for every i > m µ(f 1 i (A) g 1 (A)) µ(f 1 i (A)\f 1 i (A n )) + µ(f 1 i (A n ) g 1 (A n )) +µ(g 1 (A)\g 1 (A n )) µ(f 1 i (A\A n )) + µ(f 1 i (A n ) g 1 (A n )) +µ(g 1 (A\A n )) 3ε. So f 1 i (A) g 1 (A). (ii) iv)) By simple function approximation, we can nd Borel sets A k C so that and f 0 a k χ f 1 g a k χ f 1 0 (A k) 0 (A k) < ε < ε

34 28 for some a k A k. We can use nitely many A k and assume them to be bounded. Then, because of the condition f i µ = f j µ for all i, j < ω, we have f 1 i (A k ) f i (x) a k 2 dµ(x) = = = s a k 2 d(f i µ)(s) s A k s a k 2 d(f 0 µ)(s) s A k f 0 (x) a k 2 dµ(x). f 1 0 (A k) So we actually have f i a k χ f 1 i (A k ) < ε for all i ω. Since f 1 i (A k ) g 1 (A k ), we can nd m large enough so that ak 2 µ(f 1 i (A k ) g 1 (A k )) < ε 2 for all i > m. Therefore, for every i > m f i g f i a k χ f 1 i (A k ) + a k χ g 1 (A k ) a k χ f 1 < 2ε + ak χ g 1 (A k )\f 1 + g a k χ g 1 (A k ) i (a k ) i (A k ) + ak χ f 1 i (A k )\g 1 (a k ) = 2ε + < 3ε. ak 2 µ(f 1 i (A k ) g 1 (A k )) We have f i g.

35 29 ((iv) (iii)) Since f i g, we have f i µ gµ, hence f i µ = gµ for all i. Let A = B a,r = {s C : s a < r} be an open ball with arbitrary radius r and center a. If f 1 0 (A) is null, then g 1 (A) is null. So assume µ(f 1 0 (A)) > 0. Toward a contradiction, assume f 1 i for all i. Since µ(f 1 i (A)) = µ(g 1 (A)), we have (A) g 1 (A). Pick t > 0 so that µ(f 1 (A) g 1 (A)) > t i µ(f 1 i (A)\g 1 (A)) = µ(g 1 (A)\f 1 i (A)) > t 2. Let A s = B a,r s and x an s such that µ(a\a s ) < t. Then we have 4 µ(f 1 i (A s )\g 1 (A)) µ(f 1 i (A)\g 1 (A)) µ(a\a s ) > t 4. Finally we have f i g i 2 f 1 i (A ε)\g 1 (A) f i g 2 dµ > s2 t 4, contradicting the assumption f i g. Remark. So if f i µ = f j µ for all i, j, then (f i ) converge i f 1 i (A) converge for all basic open sets A, as the limit g in the above lemma can be easily constructed by simple function approximation. We are ready to prove the theorem: Proof. We need to show that if E L2 (X) is not smooth, then E MALGµ is not smooth. Assume E L2 (X) is not smooth. By Proposition 3.2.3, there is an f L 2 (X)

36 30 such that f is a limit point of ( f)\{f}. We can nd a countable sequence {γ i } \ f such that γ i f f. By Lemma 3.2.6, we may assume f(x) C [0, 1]. Otherwise, replace f by α f where α is a Borel isomorphism of C to the Cantor set C. In order to prove this by contradiction, assume E MALGµ is smooth. So for every Borel subset A X, there is an r A > 0 such that µ(γ(a) A) / (0, r A ) for every γ. And since µ(γ i (f 1 (B)) B) 0 for every Borel B C, there is a number m B N such that µ(γ mb (f 1 (B)) B) r f 1 (B) and µ(γ i (f 1 (B)) B) = 0 for all i > m B. Let S = {s C : µ(f 1 (s)) > 0}. Suppose S =. Let P n = {S s,n : s C}, where S s,n = {t C : t n = s n}. Fix an s C, n N f 1 (S s,n ) = f 1 (s), lim n µ(f 1 (S s,n )) = 0. Dene s i, n i inductively. To simplify the notations, let A i = S si,n i, r i = r Ai, m i = m Ssi,n i. m i. Find s 0, n 0 such that 0 < µ(f 1 (S s0,n 0 )) < 1. Let A 0 = f 1 (S s0,n 0 ). Suppose we have s i, n i. Find s i+1, n i+1 > n i such that A i+1 = f 1 (S si+1 ), 0 < µ(a i+1 ) < r i 6 and m i+1 > We can always nd such s i+1, n i+1 because n(#{s P n : µ(f 1 (S)) > r} = 0) for every r > 0. And #{S P n : µ(f 1 (S)) 0} > 0. Let A n = A 0 A 1... A n 1, and [A] = lim n [A n] in MALG µ.

37 and 31 Clearly γ mi A A. Let T n = A\A n. Since r i < 2(A i ), we have µ(a i+1 ) < µ(a i) 3 µ(t i ) µ(a j ) < 3 2 µ(a i). j=i Therefore µ((γ mi A) A) = µ((γ mi (A i )) (γ mi (T i+1 )) A i T i+1 ) µ(γ mi (A i )) A i ) µ(γ mi (T i+1 )) µ(t i+1 ) r i 2µ(T i+1 ) > r i 3µ(A i+1 ) > 0, contradicting the assumption that E MEASµ is smooth. Suppose S, then S is countable. Let f = f 1 + f 2, where f 1 (X) S and f 2 (X) C\S. Note that γ i f 1 f 1 and γ i f 2 f 2 because S and C\S are Borel. If i(γ i f 2 f 2 ), then replacing f by f 2, we are back to the case that S =. So we may assume f = f 1. If S is nite, let m = max s S {m {s} }. Thus γ i f = f for all i > m, contradicting the assumption γ i f f for all i. If S is countably innite, dene s i S inductively. To simplify the notation, let A i = f 1 (s i ), r i = r Ai, m i = m {si }.

38 32 Pick s 0 such that 0 < µ(a 0 ) = µ(f 1 (s 0 )) < 1. Suppose we have s i. Pick s i+1 such that and m i+1 > m i. 0 < µ(a i+1 ) < r i 6 Let A = i=0 A i, T i = j=i A i. We have γ mi A A, and since r i < 2(A i ), we have µ(a i+1 ) < µ(a i) 3 and µ(t i ) < 3 2 µ(a i). Therefore, µ((γ mi A) A) = µ((γ mi (A i )) (γ mi (T i+1 )) A i T i+1 ) µ(γ mi (A i )) A i ) µ(γ mi (T i+1 )) µ(t i+1 ) r i 2µ(T i+1 ) > r i 3µ(A i+1 ) > 0, contradicting the assumption that E MEASµ is smooth. So E MEASµ is not smooth, when E L2 (X) is not smooth Rigid factors and smoothness of E L2 (X). The smoothness of E Aut(X,µ) does not imply the smoothness of E L2 (X,µ). We will study some connections between rigid factors, mixing properties, and the smoothness of E L2 (X,µ). Denition A action on (X, µ) is faithful i π X : Aut(X, µ) is injective. The following notion of rigid factor is from [SW].

39 33 Denition Let X be a -space with invariant probability measure µ. The rigid factor is the set R(, X, µ) = {f L 1 (X, µ, S 1 ) : lim inf γ γ f f L 1 = 0}. The action on X is said to be rigid i the rigid factor is L 1 (X, µ, S 1 ). The action on X is said to have no rigid factor if R(, X, µ) contains only constant functions. There are many equivalent denitions of mildly mixing. For an action of countable group, no rigid factor is equivalent to mildly mixing. Assume now acts on (X, µ) faithfully and µ is a -invariant Borel probability measure. We have: Proposition E Aut(X,µ) is smooth i the action on X is not rigid. Proof. Let f be a Borel isomorphism of X to [0, 1]. Put d(t, S) = T f S f for all S, T Aut(X, µ) so that d is a (left -invariant) metric of the weak topology. Suppose E Aut(X,µ) is not smooth, then lim inf γ d(γ, 1) = 0. Since L 2 (X, µ) is a Polish Aut(X, µ)-space, the map γ γ f is continuous for the weak topology restrict on for every f L 2 (X, µ). We have lim inf γ γ f f = 0 for all f L 2 (X, µ). Assume now the action on X is rigid. We have lim inf γ γ f f = 0. Since the action is faithful, f is trivial and π X () is discrete. In fact, the smoothness of E L2 (X) is strictly between X having no rigid factors and being nonrigid. Let

40 34 (NM) the action on X is mildly mixing. (NRF) the action on X has no rigid factors. (LS) E L2 (X,µ) (MS) E MALGµ (AS) E Aut(X,µ) is smooth. is smooth. is smooth. (NR) the action on X is not rigid. Then we have the following picture: (MM) (NRF) (LS) (MS) (AS) (NR) In 3.2.4, we will show (MM) (LS) (Proposition (iii)) and give an example to show (AS) (LS). Example will show (LS) (NM) Mixing Properties and Smoothness of E L2 (X). Consider the countable Borel -space X with invariant probability measure µ and recall the induced

41 -action on L 2 (X) by unitary operators. Denote by L 2 0(X) the set 35 {f L 2 (X) : f, 1 = 0}. Then L 2 0(X) is an invariant subspace of L 2 (X). Therefore, we have a action on L 2 0(X) and π X 0 := π X L 2 (X), the subrepresentation of π X on L 2 0(X). The mixing properties, including (strong) mixing, mild mixing, weak mixing, ergodicity can be read from the action on L 2 0(X). Let us review these properties from the strongest one to the weakest one: 1) (Strongly) Mixing: An action is strongly mixing if and only if for any Borel A, B X, lim µ(γ A B) = µ(a)µ(b). γ Considering the action on L 2 0(X), this is equivalent to f, g L 2 0(X)( lim γ γ f, g = 0). In the language of unitary representation theory, it is equivalent to saying that π X 0 is a c 0 -representation. 2) Mildly mixing: The action on X is mildly mixing i lim inf γ µ((γ A) A) > 0 for any Borel subset A X that is neither null or conull.

42 36 It is equivalent to that for all f L 2 0(X)\{0}, lim sup γ f, f < f 2. γ 3) Weakly mixing: This is equivalent to saying that the action on L 2 0(X) has no nite dimensional invariant subspace. Or in the language of unitary representation theory, π X 0 has no nite dimensional subrepresentation. 4) Ergodic: The action is ergodic i every -invariant Borel subset of X is either µ-null or µ-conull. This is equivalent to saying that f L 2 0(X)\{0}( f ), where f = {γ : γ f = f}, the stabilizer of f. Or in the language of unitary representations, π X 0 does not contain the trivial one-dimensional representation. Proposition i) E L2 (X) is smooth i E L2 0 (X) is smooth. ii) If E L2 (X) is smooth, then π X () Aut(X, µ) is discrete in the weak topology. iii) If E X H is ergodic for every innite subgroup H, then the action on X is mildly mixing i E L2 0 (X) is smooth. In particular mildly mixing implies the smoothness of E L2 0 (X). iv) Assume E H is ergodic for every subgroup H such that [π X () : π X (H)] <. If E L2 0 (X) is smooth, then the action on X is weakly mixing. Proof. i) It is easy to check that E L2 (X) = E L2 0 (X) (C).

43 37 Therefore E L2 (X) is smooth i E L2 0 (X) is smooth. ii) This follows directly from Corollary and E Aut(X,µ) i c E L2 (X,µ). iii) Suppose the action on X is mildly mixing. Let A MALG µ If µ(a) = 0 or µ(a) = 1, γ [µ((γ A) A) = 0]. Assume A is neither null or conull. Since is mildly mixing, R = lim inf γ µ((γ A) A) > 0. So there S = {γ : 0 < µ((γ A) A) < R} is a nite set. Let r = min γ S {µ((γ A) A))}. We have µ((γ A) A) / (0, min(r, R)) for all γ. Therefore, by Theorem and Corollary 3.2.4, E L2 (X) is smooth. On the other hand, assume E L2 (X) is smooth. Suppose is not mildly mixing on X. Then there is an A MALG µ such that lim inf γ µ((γ A) A) = 0 and 0 < µ(a) < 1. Therefore, S r = {γ : µ((γ A) A) < r} is innite for every r > 0. By Theorem and Corollary 3.2.4, there is an R > 0 such that µ(γ(a) A) / (0, R) for all γ. So S R = {γ : µ((γ A) A) < r} = {γ : µ((γ A) A) = 0}. Let H be the subgroup of generated by S R. E X H is not ergodic because A is H-invariant. This contradicts the condition that E X H is ergodic, when H is innite. So the action on X is mildly mixing. iv) Proof by contradiction. Suppose E L2 (X) is smooth and there is a nite dimensional -invariant subspace V L 2 0(X). Pick an arbitrary f V. Since E L2 (X) is smooth, f V is discrete.

44 38 Therefore f is nite. Thus π X ()/π X ( f ) <. But f xes f L 2 0(X), contradicting the hypothesis that E f is ergodic. Example Let X, Y be faithful Borel -spaces with invariant probability measures µ, ν respectively. Assume the action on X is mildly mixing, and E L2 (Y,ν) not smooth. Consider acting on X Y by the diagonal action. π X Y () is discrete is in Aut(X Y, µ ν), hence E Aut(X Y,µ ν) is smooth. In fact, pick any A X that is neither null or conull. There exists an r > 0 such that (µ ν)((γ (A Y ) (A Y )) < r for almost every γ. But E L2 (X Y ) is clearly nonsmooth because we can nd a B Y and a sequence of γ i so that γ i (X B) X B and γ i (X B) X B for all i. For example, let = S < and G = 2 2 N. Consider the action on G dened by γ ((a g ), (b i )) = ((a γ 1 g), (b γ 1 (i)). Then the action on 2 is mixing, so E Aut(G,µ) is smooth. But E L2 (G) is not smooth because E L2 (2 N ) is not smooth The Peter-Weyl Theorem. We are going to develop several other techniques to determine the smoothness and nonsmoothness of E L2 (X). In some situation, it is easier to use them than directly check the conditions in Theorem Most of these techniques involve the Peter-Weyl theorem.

45 39 Recall the Peter-Weyl theorem from unitary representation theory (see [ Folland, Kechris 1]). Theorem (Peter-Weyl) Let G be a compact Polish group. Then (i) Every irreducible unitary representation of G is nite dimensional; (ii) Ĝ is countable; (iii) Every unitary representation of G is a direct sum of irreducible unitary representations. Consider a compact Polish group G with the (normalized) Haar measure µ. For each irreducible unitary representation π of G, denote by ˆπ the isomorphism class of π and by H π the Hilbert space of it. Also denote by Ĝ the dual of G, which is the countable set {ˆπ : π is an irreducible unitary representation of G}. Denote by ρ G : G U(L 2 (G)) the right regular representation of G, which is the unitary representation dened by (ρ G (g))(f(h)) = f(hg) for all g, h G and f L 2 (G). Fix a representative π for each ˆπ Ĝ and an orthonormal basis {eπ i } 1 i dπ, where d π = dim(h π ). Let π ij (g) = π(g)e π j, e π i be the matrix coecients of π in this basis. π ij L 2 (G) and denote by E π the linear span of {π ij }. Clearly this space is independent of the choice of π, thus we can write Eˆπ = E π. Theorem (Peter-Weyl) Let G be a compact Polish group. Then

46 40 (i) L 2 (G) = ˆπ Ĝ Eˆπ. (ii) { d π π ij } 1 i,j dπ is an orthonormal basis for Eˆπ, so dim(eˆπ ) = d 2 π. (iii) For i = 1,..., d π, the subspace Eˆπ,i of Eˆπ spanned by the ith row of the matrix ( d π π ij ) is invariant under the right regular representation, and the subrepresentation of ρ G determined by Eˆπ,i is isomorphic to π. Dene the character χ π by χ π (g) = trace(π(g)). Trace is also independent of the choice of the basis and the representative π of each isomorphic class, so we put χˆπ = χ π. {χˆπ : ˆπ Ĝ} is an orthonormal set in L2 (G) (see [Folland], 5.23). Suppose is a countable group acting by (topological group) automorphisms on G. Clearly preserves µ. There is a natural action on Ĝ. For a γ, dene (γ π)(g) = π(γ 1 g). Since π is irreducible, γ π is also irreducible. And again, γ π is independent of the choice of π in each isomorphic class. So we can dene γ ˆπ = γ π. Also note that (γ χˆπ )(g) = χˆπ (γ 1 g) = trace(π(γ 1 g)) = trace((γ π)(g)) = χ γ π (g). So γ χˆπ = χ γ ˆπ, nally γ Eˆπ = E γ ˆπ Some Characterizations of Smoothness. Corollary ) Assume X = G is a compact Polish group and acts on G by automorphisms. If E L2 (G) is smooth, then ˆπ π is nite for every irreducible unitary representation π of X. Or equivalently, ˆπ / π is nite for every irreducible unitary representation π of X.

47 41 2) Assume acts on a compact Polish space X by isometries and X has a Borel probability measure that is invariant under any isometry. Then E L2 (X) is smooth i E is uniformly periodic µ-a.e., i.e., N < µ x X( [x] E < N). 3) Assume acts on X by topological group automorphisms where X = G is a connected semisimple Lie group with an invariant Borel probability measure µ. Then E L2 (X) is smooth i E X is uniformly periodic µ-a.e. Proof. 1) Recall that ˆπ is the stabilizer of ˆπ, i.e., ˆπ = {γ : γ π = ˆπ}. Hence ˆπ π = {γ π γ ˆπ } = {γ π γ π = ˆπ}. By the Peter-Weyl Theorem, the subrepresentation of ρ G determined by Eˆπ,i is isomorphic to π. If ˆπ π is innite, then ˆπ π ij is innite for some j. But Eˆπ,i is nite dimensional, so ˆπ π ij, which is contained in the unit sphere of Eˆπ,i, is compact. Therefore ˆπ π ij has at least one limit point and therefore is not closed. By Proposition (iii), E L2 (G) is not smooth. 2) ( ) Since γ N! f = f, E L2 (G) is smooth. ( ) Since Iso(X) is compact, by the Peter-Weyl theorem, π X is the direct product of irreducible nite dimensional unitary representations, say L 2 (X) = i N V i, and V i are nite dimensional π X invariant subspaces.

48 42 For every f L 2 (X), we can write f = f i where f i V i. Suppose f is innite. If f i is innite for some i, then E L2 (X) is not smooth. Assume now f i is nite for every i. Since i( f i ) is nite and f is innite, i<m f i is innite for every M <. Therefore, we can nd a sequence g M i<m f i f\f, and g M f, hence E L2 (X) is not smooth. So if E L2 (X) is smooth, then every orbit of f L 2 (X) is nite. Therefore, we must have a nite upper bound of -orbit on X µ-a.e. 3) Since Aut(G) is compact, this is from the proof of 2) Stabilizers. Consider the action on L 2 (X). We can also describe the stabilizer of f L 2 (X) in terms of the action on X and its full group. Denition Let F be a (not necessarily countable) Borel equivalence relation dened on X and µ a (not necessarily F -invariant) Borel probability measure on X. Denote by [F ] = {T Aut(X, µ) µ x (T (x)ex)} the full group of F. This is a straightforward generalization of the usual concept of full group, which is usually dened in the case that µ is E-invariant and in the context that E is countable. We have the following simple proposition: Proposition Let F be a Borel equivalence relation on a standard Borel space X with a Borel probability measure µ. If F is smooth, then [F ] is closed in the weak topology of Aut(X, µ). Proof. F is smooth, hence F B ([0, 1]). Let f : X [0, 1] be a Borel function such that xf y i f(x) = f(y). Then the assignment T f T is a continuous map

49 43 from Aut(X, µ) to L 2 (X). Note that T [F ] i f T = f (modulo null sets), hence [F ] is closed. Recall the uniform ergodic decomposition for invariant measures of E. Denote by P (X) the set of probability measures on X, by I E P (X) the set of E-invariant Borel probability measures on X, and by EI E P (X) the set of E-invariant ergodic Borel probability measures on X. We have (see [KM], Theorem 3.3) Theorem (Farrell, Varadarajan) Let E be a countable Borel equivalence relation on a standard Borel space X. Assume I E 0. Then there is a unique (up to null sets) Borel surjection π : X EI E such that (1) π(x) = π(y) if xey; (2) If X e = {x : π(x) = e}, for e EI E, then e(x e ) = 1; (3) For any µ I E, µ = π(x)dµ(x). So we can write EI E = {e x }, where e x = π(x). Until the end of this subsection, we will use the above notations: π, X e to denote the unique ergodic decomposition of (X, E) and F (F Xif E = EX ) to denote the Borel equivalence relation on X, which is dened by xf y i π(x) = π(y). Since F is smooth, [F ] is closed by Proposition and clearly [E] [F ]. Furthermore, we can show that [F ] is the closure of [E]. Theorem Let E be a countable Borel equivalence relation on a standard Borel space X with invariant probability measure µ. Given S [F ] and a Borel set A, then there is a T [E], such that T (A) = S(A). Proof. Let Y be an F -invariant Borel set. Then T (A Y ) = T (A) T (Y ) = T (A) Y, hence µ(a Y ) = µ(t (A) Y ).

AMENABLE ACTIONS AND ALMOST INVARIANT SETS

AMENABLE ACTIONS AND ALMOST INVARIANT SETS AMENABLE ACTIONS AND ALMOST INVARIANT SETS ALEXANDER S. KECHRIS AND TODOR TSANKOV Abstract. In this paper, we study the connections between properties of the action of a countable group Γ on a countable

More information

Ergodic Theory and Topological Groups

Ergodic Theory and Topological Groups Ergodic Theory and Topological Groups Christopher White November 15, 2012 Throughout this talk (G, B, µ) will denote a measure space. We call the space a probability space if µ(g) = 1. We will also assume

More information

Quasi-invariant measures for continuous group actions

Quasi-invariant measures for continuous group actions Contemporary Mathematics Quasi-invariant measures for continuous group actions Alexander S. Kechris Dedicated to Simon Thomas on his 60th birthday Abstract. The class of ergodic, invariant probability

More information

Integration on Measure Spaces

Integration on Measure Spaces Chapter 3 Integration on Measure Spaces In this chapter we introduce the general notion of a measure on a space X, define the class of measurable functions, and define the integral, first on a class of

More information

Lebesgue Measure on R n

Lebesgue Measure on R n 8 CHAPTER 2 Lebesgue Measure on R n Our goal is to construct a notion of the volume, or Lebesgue measure, of rather general subsets of R n that reduces to the usual volume of elementary geometrical sets

More information

Part V. 17 Introduction: What are measures and why measurable sets. Lebesgue Integration Theory

Part V. 17 Introduction: What are measures and why measurable sets. Lebesgue Integration Theory Part V 7 Introduction: What are measures and why measurable sets Lebesgue Integration Theory Definition 7. (Preliminary). A measure on a set is a function :2 [ ] such that. () = 2. If { } = is a finite

More information

THEOREMS, ETC., FOR MATH 515

THEOREMS, ETC., FOR MATH 515 THEOREMS, ETC., FOR MATH 515 Proposition 1 (=comment on page 17). If A is an algebra, then any finite union or finite intersection of sets in A is also in A. Proposition 2 (=Proposition 1.1). For every

More information

Lebesgue Measure on R n

Lebesgue Measure on R n CHAPTER 2 Lebesgue Measure on R n Our goal is to construct a notion of the volume, or Lebesgue measure, of rather general subsets of R n that reduces to the usual volume of elementary geometrical sets

More information

Measurable functions are approximately nice, even if look terrible.

Measurable functions are approximately nice, even if look terrible. Tel Aviv University, 2015 Functions of real variables 74 7 Approximation 7a A terrible integrable function........... 74 7b Approximation of sets................ 76 7c Approximation of functions............

More information

II - REAL ANALYSIS. This property gives us a way to extend the notion of content to finite unions of rectangles: we define

II - REAL ANALYSIS. This property gives us a way to extend the notion of content to finite unions of rectangles: we define 1 Measures 1.1 Jordan content in R N II - REAL ANALYSIS Let I be an interval in R. Then its 1-content is defined as c 1 (I) := b a if I is bounded with endpoints a, b. If I is unbounded, we define c 1

More information

Borel complexity and automorphisms of C*-algebras

Borel complexity and automorphisms of C*-algebras Martino Lupini York University Toronto, Canada January 15th, 2013 Table of Contents 1 Auto-homeomorphisms of compact metrizable spaces 2 Measure preserving automorphisms of probability spaces 3 Automorphisms

More information

Measurable chromatic and independence numbers for ergodic graphs and group actions

Measurable chromatic and independence numbers for ergodic graphs and group actions Measurable chromatic and independence numbers for ergodic graphs and group actions Clinton T. Conley and Alexander S. Kechris July 9, 2010 0 Introduction We study in this paper some combinatorial invariants

More information

Dual Space of L 1. C = {E P(I) : one of E or I \ E is countable}.

Dual Space of L 1. C = {E P(I) : one of E or I \ E is countable}. Dual Space of L 1 Note. The main theorem of this note is on page 5. The secondary theorem, describing the dual of L (µ) is on page 8. Let (X, M, µ) be a measure space. We consider the subsets of X which

More information

int cl int cl A = int cl A.

int cl int cl A = int cl A. BAIRE CATEGORY CHRISTIAN ROSENDAL 1. THE BAIRE CATEGORY THEOREM Theorem 1 (The Baire category theorem. Let (D n n N be a countable family of dense open subsets of a Polish space X. Then n N D n is dense

More information

Examples of non-shy sets

Examples of non-shy sets F U N D A M E N T A MATHEMATICAE 144 (1994) Examples of non-shy sets by Randall D o u g h e r t y (Columbus, Ohio) Abstract. Christensen has defined a generalization of the property of being of Haar measure

More information

1 Topology Definition of a topology Basis (Base) of a topology The subspace topology & the product topology on X Y 3

1 Topology Definition of a topology Basis (Base) of a topology The subspace topology & the product topology on X Y 3 Index Page 1 Topology 2 1.1 Definition of a topology 2 1.2 Basis (Base) of a topology 2 1.3 The subspace topology & the product topology on X Y 3 1.4 Basic topology concepts: limit points, closed sets,

More information

Real Analysis Notes. Thomas Goller

Real Analysis Notes. Thomas Goller Real Analysis Notes Thomas Goller September 4, 2011 Contents 1 Abstract Measure Spaces 2 1.1 Basic Definitions........................... 2 1.2 Measurable Functions........................ 2 1.3 Integration..............................

More information

Chapter 1. Measure Spaces. 1.1 Algebras and σ algebras of sets Notation and preliminaries

Chapter 1. Measure Spaces. 1.1 Algebras and σ algebras of sets Notation and preliminaries Chapter 1 Measure Spaces 1.1 Algebras and σ algebras of sets 1.1.1 Notation and preliminaries We shall denote by X a nonempty set, by P(X) the set of all parts (i.e., subsets) of X, and by the empty set.

More information

MATHS 730 FC Lecture Notes March 5, Introduction

MATHS 730 FC Lecture Notes March 5, Introduction 1 INTRODUCTION MATHS 730 FC Lecture Notes March 5, 2014 1 Introduction Definition. If A, B are sets and there exists a bijection A B, they have the same cardinality, which we write as A, #A. If there exists

More information

Probability and Measure

Probability and Measure Part II Year 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2018 84 Paper 4, Section II 26J Let (X, A) be a measurable space. Let T : X X be a measurable map, and µ a probability

More information

MATH 614 Dynamical Systems and Chaos Lecture 38: Ergodicity (continued). Mixing.

MATH 614 Dynamical Systems and Chaos Lecture 38: Ergodicity (continued). Mixing. MATH 614 Dynamical Systems and Chaos Lecture 38: Ergodicity (continued). Mixing. Ergodic theorems Let (X,B,µ) be a measured space and T : X X be a measure-preserving transformation. Birkhoff s Ergodic

More information

4. Ergodicity and mixing

4. Ergodicity and mixing 4. Ergodicity and mixing 4. Introduction In the previous lecture we defined what is meant by an invariant measure. In this lecture, we define what is meant by an ergodic measure. The primary motivation

More information

A SHORT PROOF OF THE CONNES-FELDMAN-WEISS THEOREM

A SHORT PROOF OF THE CONNES-FELDMAN-WEISS THEOREM A SHORT PROOF OF THE CONNES-FELDMAN-WEISS THEOREM ANDREW MARKS Abstract. In this note, we give a short proof of the theorem due to Connes, Feldman, and Weiss that a countable orel equivalence relation

More information

Analysis Comprehensive Exam Questions Fall F(x) = 1 x. f(t)dt. t 1 2. tf 2 (t)dt. and g(t, x) = 2 t. 2 t

Analysis Comprehensive Exam Questions Fall F(x) = 1 x. f(t)dt. t 1 2. tf 2 (t)dt. and g(t, x) = 2 t. 2 t Analysis Comprehensive Exam Questions Fall 2. Let f L 2 (, ) be given. (a) Prove that ( x 2 f(t) dt) 2 x x t f(t) 2 dt. (b) Given part (a), prove that F L 2 (, ) 2 f L 2 (, ), where F(x) = x (a) Using

More information

ERGODIC DYNAMICAL SYSTEMS CONJUGATE TO THEIR COMPOSITION SQUARES. 0. Introduction

ERGODIC DYNAMICAL SYSTEMS CONJUGATE TO THEIR COMPOSITION SQUARES. 0. Introduction Acta Math. Univ. Comenianae Vol. LXXI, 2(2002), pp. 201 210 201 ERGODIC DYNAMICAL SYSTEMS CONJUGATE TO THEIR COMPOSITION SQUARES G. R. GOODSON Abstract. We investigate the question of when an ergodic automorphism

More information

REPRESENTATION THEORY WEEK 7

REPRESENTATION THEORY WEEK 7 REPRESENTATION THEORY WEEK 7 1. Characters of L k and S n A character of an irreducible representation of L k is a polynomial function constant on every conjugacy class. Since the set of diagonalizable

More information

Finite-dimensional spaces. C n is the space of n-tuples x = (x 1,..., x n ) of complex numbers. It is a Hilbert space with the inner product

Finite-dimensional spaces. C n is the space of n-tuples x = (x 1,..., x n ) of complex numbers. It is a Hilbert space with the inner product Chapter 4 Hilbert Spaces 4.1 Inner Product Spaces Inner Product Space. A complex vector space E is called an inner product space (or a pre-hilbert space, or a unitary space) if there is a mapping (, )

More information

Real Analysis Problems

Real Analysis Problems Real Analysis Problems Cristian E. Gutiérrez September 14, 29 1 1 CONTINUITY 1 Continuity Problem 1.1 Let r n be the sequence of rational numbers and Prove that f(x) = 1. f is continuous on the irrationals.

More information

A BOOLEAN ACTION OF C(M, U(1)) WITHOUT A SPATIAL MODEL AND A RE-EXAMINATION OF THE CAMERON MARTIN THEOREM

A BOOLEAN ACTION OF C(M, U(1)) WITHOUT A SPATIAL MODEL AND A RE-EXAMINATION OF THE CAMERON MARTIN THEOREM A BOOLEAN ACTION OF C(M, U(1)) WITHOUT A SPATIAL MODEL AND A RE-EXAMINATION OF THE CAMERON MARTIN THEOREM JUSTIN TATCH MOORE AND S LAWOMIR SOLECKI Abstract. We will demonstrate that if M is an uncountable

More information

Recall that if X is a compact metric space, C(X), the space of continuous (real-valued) functions on X, is a Banach space with the norm

Recall that if X is a compact metric space, C(X), the space of continuous (real-valued) functions on X, is a Banach space with the norm Chapter 13 Radon Measures Recall that if X is a compact metric space, C(X), the space of continuous (real-valued) functions on X, is a Banach space with the norm (13.1) f = sup x X f(x). We want to identify

More information

l(y j ) = 0 for all y j (1)

l(y j ) = 0 for all y j (1) Problem 1. The closed linear span of a subset {y j } of a normed vector space is defined as the intersection of all closed subspaces containing all y j and thus the smallest such subspace. 1 Show that

More information

ORTHOGONAL MEASURES AND ERGODICITY. By Clinton T. Conley Cornell University and. By Benjamin D. Miller Universität Münster

ORTHOGONAL MEASURES AND ERGODICITY. By Clinton T. Conley Cornell University and. By Benjamin D. Miller Universität Münster Submitted to the Annals of Probability ORTHOGONAL MEASURES AND ERGODICITY By Clinton T. Conley Cornell University and By Benjamin D. Miller Universität Münster We establish a strengthening of the E 0 dichotomy

More information

Rudiments of Ergodic Theory

Rudiments of Ergodic Theory Rudiments of Ergodic Theory Zefeng Chen September 24, 203 Abstract In this note we intend to present basic ergodic theory. We begin with the notion of a measure preserving transformation. We then define

More information

Real Analysis, 2nd Edition, G.B.Folland Elements of Functional Analysis

Real Analysis, 2nd Edition, G.B.Folland Elements of Functional Analysis Real Analysis, 2nd Edition, G.B.Folland Chapter 5 Elements of Functional Analysis Yung-Hsiang Huang 5.1 Normed Vector Spaces 1. Note for any x, y X and a, b K, x+y x + y and by ax b y x + b a x. 2. It

More information

Cayley Graphs of Finitely Generated Groups

Cayley Graphs of Finitely Generated Groups Cayley Graphs of Finitely Generated Groups Simon Thomas Rutgers University 13th May 2014 Cayley graphs of finitely generated groups Definition Let G be a f.g. group and let S G { 1 } be a finite generating

More information

3 (Due ). Let A X consist of points (x, y) such that either x or y is a rational number. Is A measurable? What is its Lebesgue measure?

3 (Due ). Let A X consist of points (x, y) such that either x or y is a rational number. Is A measurable? What is its Lebesgue measure? MA 645-4A (Real Analysis), Dr. Chernov Homework assignment 1 (Due ). Show that the open disk x 2 + y 2 < 1 is a countable union of planar elementary sets. Show that the closed disk x 2 + y 2 1 is a countable

More information

Riesz Representation Theorems

Riesz Representation Theorems Chapter 6 Riesz Representation Theorems 6.1 Dual Spaces Definition 6.1.1. Let V and W be vector spaces over R. We let L(V, W ) = {T : V W T is linear}. The space L(V, R) is denoted by V and elements of

More information

REAL AND COMPLEX ANALYSIS

REAL AND COMPLEX ANALYSIS REAL AND COMPLE ANALYSIS Third Edition Walter Rudin Professor of Mathematics University of Wisconsin, Madison Version 1.1 No rights reserved. Any part of this work can be reproduced or transmitted in any

More information

Measure-theoretic unfriendly colorings

Measure-theoretic unfriendly colorings Measure-theoretic unfriendly colorings Clinton T. Conley August 26, 2013 Abstract We consider the problem of finding a measurable unfriendly partition of the vertex set of a locally finite Borel graph

More information

THE COMPLEXITY OF CLASSIFICATION PROBLEMS IN ERGODIC THEORY

THE COMPLEXITY OF CLASSIFICATION PROBLEMS IN ERGODIC THEORY THE COMPLEXITY OF CLASSIFICATION PROBLEMS IN ERGODIC THEORY ALEXANDER S. KECHRIS AND ROBIN D. TUCKER-DROB Dedicated to the memory of Greg Hjorth (1963-2011) The last two decades have seen the emergence

More information

On a measurable analogue of small topological full groups

On a measurable analogue of small topological full groups On a measurable analogue of small topological full groups François Le Maître November 5, 2018 arxiv:1608.07399v2 [math.ds] 7 May 2018 Abstract We initiate the study of a measurable analogue of small topological

More information

Combinatorial Variants of Lebesgue s Density Theorem

Combinatorial Variants of Lebesgue s Density Theorem Combinatorial Variants of Lebesgue s Density Theorem Philipp Schlicht joint with David Schrittesser, Sandra Uhlenbrock and Thilo Weinert September 6, 2017 Philipp Schlicht Variants of Lebesgue s Density

More information

Since G is a compact Lie group, we can apply Schur orthogonality to see that G χ π (g) 2 dg =

Since G is a compact Lie group, we can apply Schur orthogonality to see that G χ π (g) 2 dg = Problem 1 Show that if π is an irreducible representation of a compact lie group G then π is also irreducible. Give an example of a G and π such that π = π, and another for which π π. Is this true for

More information

MATH 202B - Problem Set 5

MATH 202B - Problem Set 5 MATH 202B - Problem Set 5 Walid Krichene (23265217) March 6, 2013 (5.1) Show that there exists a continuous function F : [0, 1] R which is monotonic on no interval of positive length. proof We know there

More information

Topology. Xiaolong Han. Department of Mathematics, California State University, Northridge, CA 91330, USA address:

Topology. Xiaolong Han. Department of Mathematics, California State University, Northridge, CA 91330, USA  address: Topology Xiaolong Han Department of Mathematics, California State University, Northridge, CA 91330, USA E-mail address: Xiaolong.Han@csun.edu Remark. You are entitled to a reward of 1 point toward a homework

More information

3. (a) What is a simple function? What is an integrable function? How is f dµ defined? Define it first

3. (a) What is a simple function? What is an integrable function? How is f dµ defined? Define it first Math 632/6321: Theory of Functions of a Real Variable Sample Preinary Exam Questions 1. Let (, M, µ) be a measure space. (a) Prove that if µ() < and if 1 p < q

More information

7 About Egorov s and Lusin s theorems

7 About Egorov s and Lusin s theorems Tel Aviv University, 2013 Measure and category 62 7 About Egorov s and Lusin s theorems 7a About Severini-Egorov theorem.......... 62 7b About Lusin s theorem............... 64 7c About measurable functions............

More information

Notions such as convergent sequence and Cauchy sequence make sense for any metric space. Convergent Sequences are Cauchy

Notions such as convergent sequence and Cauchy sequence make sense for any metric space. Convergent Sequences are Cauchy Banach Spaces These notes provide an introduction to Banach spaces, which are complete normed vector spaces. For the purposes of these notes, all vector spaces are assumed to be over the real numbers.

More information

Introduction to Topology

Introduction to Topology Introduction to Topology Randall R. Holmes Auburn University Typeset by AMS-TEX Chapter 1. Metric Spaces 1. Definition and Examples. As the course progresses we will need to review some basic notions about

More information

Metric Spaces and Topology

Metric Spaces and Topology Chapter 2 Metric Spaces and Topology From an engineering perspective, the most important way to construct a topology on a set is to define the topology in terms of a metric on the set. This approach underlies

More information

Measures and Measure Spaces

Measures and Measure Spaces Chapter 2 Measures and Measure Spaces In summarizing the flaws of the Riemann integral we can focus on two main points: 1) Many nice functions are not Riemann integrable. 2) The Riemann integral does not

More information

Gaussian automorphisms whose ergodic self-joinings are Gaussian

Gaussian automorphisms whose ergodic self-joinings are Gaussian F U N D A M E N T A MATHEMATICAE 164 (2000) Gaussian automorphisms whose ergodic self-joinings are Gaussian by M. L e m a ńc z y k (Toruń), F. P a r r e a u (Paris) and J.-P. T h o u v e n o t (Paris)

More information

Course 212: Academic Year Section 1: Metric Spaces

Course 212: Academic Year Section 1: Metric Spaces Course 212: Academic Year 1991-2 Section 1: Metric Spaces D. R. Wilkins Contents 1 Metric Spaces 3 1.1 Distance Functions and Metric Spaces............. 3 1.2 Convergence and Continuity in Metric Spaces.........

More information

Compact operators on Banach spaces

Compact operators on Banach spaces Compact operators on Banach spaces Jordan Bell jordan.bell@gmail.com Department of Mathematics, University of Toronto November 12, 2017 1 Introduction In this note I prove several things about compact

More information

Analysis Comprehensive Exam Questions Fall 2008

Analysis Comprehensive Exam Questions Fall 2008 Analysis Comprehensive xam Questions Fall 28. (a) Let R be measurable with finite Lebesgue measure. Suppose that {f n } n N is a bounded sequence in L 2 () and there exists a function f such that f n (x)

More information

are Banach algebras. f(x)g(x) max Example 7.4. Similarly, A = L and A = l with the pointwise multiplication

are Banach algebras. f(x)g(x) max Example 7.4. Similarly, A = L and A = l with the pointwise multiplication 7. Banach algebras Definition 7.1. A is called a Banach algebra (with unit) if: (1) A is a Banach space; (2) There is a multiplication A A A that has the following properties: (xy)z = x(yz), (x + y)z =

More information

4 Countability axioms

4 Countability axioms 4 COUNTABILITY AXIOMS 4 Countability axioms Definition 4.1. Let X be a topological space X is said to be first countable if for any x X, there is a countable basis for the neighborhoods of x. X is said

More information

CONTENTS. 4 Hausdorff Measure Introduction The Cantor Set Rectifiable Curves Cantor Set-Like Objects...

CONTENTS. 4 Hausdorff Measure Introduction The Cantor Set Rectifiable Curves Cantor Set-Like Objects... Contents 1 Functional Analysis 1 1.1 Hilbert Spaces................................... 1 1.1.1 Spectral Theorem............................. 4 1.2 Normed Vector Spaces.............................. 7 1.2.1

More information

MATH MEASURE THEORY AND FOURIER ANALYSIS. Contents

MATH MEASURE THEORY AND FOURIER ANALYSIS. Contents MATH 3969 - MEASURE THEORY AND FOURIER ANALYSIS ANDREW TULLOCH Contents 1. Measure Theory 2 1.1. Properties of Measures 3 1.2. Constructing σ-algebras and measures 3 1.3. Properties of the Lebesgue measure

More information

Math 4121 Spring 2012 Weaver. Measure Theory. 1. σ-algebras

Math 4121 Spring 2012 Weaver. Measure Theory. 1. σ-algebras Math 4121 Spring 2012 Weaver Measure Theory 1. σ-algebras A measure is a function which gauges the size of subsets of a given set. In general we do not ask that a measure evaluate the size of every subset,

More information

MATS113 ADVANCED MEASURE THEORY SPRING 2016

MATS113 ADVANCED MEASURE THEORY SPRING 2016 MATS113 ADVANCED MEASURE THEORY SPRING 2016 Foreword These are the lecture notes for the course Advanced Measure Theory given at the University of Jyväskylä in the Spring of 2016. The lecture notes can

More information

PROBLEMS. (b) (Polarization Identity) Show that in any inner product space

PROBLEMS. (b) (Polarization Identity) Show that in any inner product space 1 Professor Carl Cowen Math 54600 Fall 09 PROBLEMS 1. (Geometry in Inner Product Spaces) (a) (Parallelogram Law) Show that in any inner product space x + y 2 + x y 2 = 2( x 2 + y 2 ). (b) (Polarization

More information

OPERATOR THEORY ON HILBERT SPACE. Class notes. John Petrovic

OPERATOR THEORY ON HILBERT SPACE. Class notes. John Petrovic OPERATOR THEORY ON HILBERT SPACE Class notes John Petrovic Contents Chapter 1. Hilbert space 1 1.1. Definition and Properties 1 1.2. Orthogonality 3 1.3. Subspaces 7 1.4. Weak topology 9 Chapter 2. Operators

More information

Math 210C. The representation ring

Math 210C. The representation ring Math 210C. The representation ring 1. Introduction Let G be a nontrivial connected compact Lie group that is semisimple and simply connected (e.g., SU(n) for n 2, Sp(n) for n 1, or Spin(n) for n 3). Let

More information

CHARACTERISTIC POLYNOMIAL PATTERNS IN DIFFERENCE SETS OF MATRICES

CHARACTERISTIC POLYNOMIAL PATTERNS IN DIFFERENCE SETS OF MATRICES CHARACTERISTIC POLYNOMIAL PATTERNS IN DIFFERENCE SETS OF MATRICES MICHAEL BJÖRKLUND AND ALEXANDER FISH Abstract. We show that for every subset E of positive density in the set of integer squarematrices

More information

here, this space is in fact infinite-dimensional, so t σ ess. Exercise Let T B(H) be a self-adjoint operator on an infinitedimensional

here, this space is in fact infinite-dimensional, so t σ ess. Exercise Let T B(H) be a self-adjoint operator on an infinitedimensional 15. Perturbations by compact operators In this chapter, we study the stability (or lack thereof) of various spectral properties under small perturbations. Here s the type of situation we have in mind:

More information

The Lebesgue Integral

The Lebesgue Integral The Lebesgue Integral Brent Nelson In these notes we give an introduction to the Lebesgue integral, assuming only a knowledge of metric spaces and the iemann integral. For more details see [1, Chapters

More information

2 (Bonus). Let A X consist of points (x, y) such that either x or y is a rational number. Is A measurable? What is its Lebesgue measure?

2 (Bonus). Let A X consist of points (x, y) such that either x or y is a rational number. Is A measurable? What is its Lebesgue measure? MA 645-4A (Real Analysis), Dr. Chernov Homework assignment 1 (Due 9/5). Prove that every countable set A is measurable and µ(a) = 0. 2 (Bonus). Let A consist of points (x, y) such that either x or y is

More information

(1) Consider the space S consisting of all continuous real-valued functions on the closed interval [0, 1]. For f, g S, define

(1) Consider the space S consisting of all continuous real-valued functions on the closed interval [0, 1]. For f, g S, define Homework, Real Analysis I, Fall, 2010. (1) Consider the space S consisting of all continuous real-valued functions on the closed interval [0, 1]. For f, g S, define ρ(f, g) = 1 0 f(x) g(x) dx. Show that

More information

Countable Borel equivalence relations. Konstantin Slutsky

Countable Borel equivalence relations. Konstantin Slutsky Countable Borel equivalence relations Konstantin Slutsky Chapter 1 First contact 1.1 Hi, my name is Cber. Definition 1.1.1. An equivalence relation on a set X is a set E X X such that for all x, y, z X

More information

1. If 1, ω, ω 2, -----, ω 9 are the 10 th roots of unity, then (1 + ω) (1 + ω 2 ) (1 + ω 9 ) is A) 1 B) 1 C) 10 D) 0

1. If 1, ω, ω 2, -----, ω 9 are the 10 th roots of unity, then (1 + ω) (1 + ω 2 ) (1 + ω 9 ) is A) 1 B) 1 C) 10 D) 0 4 INUTES. If, ω, ω, -----, ω 9 are the th roots of unity, then ( + ω) ( + ω ) ----- ( + ω 9 ) is B) D) 5. i If - i = a + ib, then a =, b = B) a =, b = a =, b = D) a =, b= 3. Find the integral values for

More information

MAT 449 : Problem Set 7

MAT 449 : Problem Set 7 MAT 449 : Problem Set 7 Due Thursday, November 8 Let be a topological group and (π, V ) be a unitary representation of. A matrix coefficient of π is a function C of the form x π(x)(v), w, with v, w V.

More information

Measure Theory on Topological Spaces. Course: Prof. Tony Dorlas 2010 Typset: Cathal Ormond

Measure Theory on Topological Spaces. Course: Prof. Tony Dorlas 2010 Typset: Cathal Ormond Measure Theory on Topological Spaces Course: Prof. Tony Dorlas 2010 Typset: Cathal Ormond May 22, 2011 Contents 1 Introduction 2 1.1 The Riemann Integral........................................ 2 1.2 Measurable..............................................

More information

We have the following immediate corollary. 1

We have the following immediate corollary. 1 1. Thom Spaces and Transversality Definition 1.1. Let π : E B be a real k vector bundle with a Euclidean metric and let E 1 be the set of elements of norm 1. The Thom space T (E) of E is the quotient E/E

More information

MATRIX LIE GROUPS AND LIE GROUPS

MATRIX LIE GROUPS AND LIE GROUPS MATRIX LIE GROUPS AND LIE GROUPS Steven Sy December 7, 2005 I MATRIX LIE GROUPS Definition: A matrix Lie group is a closed subgroup of Thus if is any sequence of matrices in, and for some, then either

More information

Math 5051 Measure Theory and Functional Analysis I Homework Assignment 2

Math 5051 Measure Theory and Functional Analysis I Homework Assignment 2 Math 551 Measure Theory and Functional nalysis I Homework ssignment 2 Prof. Wickerhauser Due Friday, September 25th, 215 Please do Exercises 1, 4*, 7, 9*, 11, 12, 13, 16, 21*, 26, 28, 31, 32, 33, 36, 37.

More information

7 Complete metric spaces and function spaces

7 Complete metric spaces and function spaces 7 Complete metric spaces and function spaces 7.1 Completeness Let (X, d) be a metric space. Definition 7.1. A sequence (x n ) n N in X is a Cauchy sequence if for any ɛ > 0, there is N N such that n, m

More information

A topological semigroup structure on the space of actions modulo weak equivalence.

A topological semigroup structure on the space of actions modulo weak equivalence. A topological semigroup structure on the space of actions modulo wea equivalence. Peter Burton January 8, 08 Abstract We introduce a topology on the space of actions modulo wea equivalence finer than the

More information

arxiv: v2 [math.ds] 14 Mar 2009

arxiv: v2 [math.ds] 14 Mar 2009 ON ERGODIC TRANSFORMATIONS THAT ARE BOTH WEAKLY MIXING AND UNIFORMLY RIGID JENNIFER JAMES, THOMAS KOBERDA, KATHRYN LINDSEY, CESAR E. SILVA, AND PETER SPEH arxiv:0809.4406v2 [math.ds] 14 Mar 2009 Abstract.

More information

Measure Theory. John K. Hunter. Department of Mathematics, University of California at Davis

Measure Theory. John K. Hunter. Department of Mathematics, University of California at Davis Measure Theory John K. Hunter Department of Mathematics, University of California at Davis Abstract. These are some brief notes on measure theory, concentrating on Lebesgue measure on R n. Some missing

More information

1/12/05: sec 3.1 and my article: How good is the Lebesgue measure?, Math. Intelligencer 11(2) (1989),

1/12/05: sec 3.1 and my article: How good is the Lebesgue measure?, Math. Intelligencer 11(2) (1989), Real Analysis 2, Math 651, Spring 2005 April 26, 2005 1 Real Analysis 2, Math 651, Spring 2005 Krzysztof Chris Ciesielski 1/12/05: sec 3.1 and my article: How good is the Lebesgue measure?, Math. Intelligencer

More information

Algebraic Number Theory

Algebraic Number Theory TIFR VSRP Programme Project Report Algebraic Number Theory Milind Hegde Under the guidance of Prof. Sandeep Varma July 4, 2015 A C K N O W L E D G M E N T S I would like to express my thanks to TIFR for

More information

Ergodic Theory. Constantine Caramanis. May 6, 1999

Ergodic Theory. Constantine Caramanis. May 6, 1999 Ergodic Theory Constantine Caramanis ay 6, 1999 1 Introduction Ergodic theory involves the study of transformations on measure spaces. Interchanging the words measurable function and probability density

More information

Lecture Notes in Advanced Calculus 1 (80315) Raz Kupferman Institute of Mathematics The Hebrew University

Lecture Notes in Advanced Calculus 1 (80315) Raz Kupferman Institute of Mathematics The Hebrew University Lecture Notes in Advanced Calculus 1 (80315) Raz Kupferman Institute of Mathematics The Hebrew University February 7, 2007 2 Contents 1 Metric Spaces 1 1.1 Basic definitions...........................

More information

THE RADON NIKODYM PROPERTY AND LIPSCHITZ EMBEDDINGS

THE RADON NIKODYM PROPERTY AND LIPSCHITZ EMBEDDINGS THE RADON NIKODYM PROPERTY AND LIPSCHITZ EMBEDDINGS Motivation The idea here is simple. Suppose we have a Lipschitz homeomorphism f : X Y where X and Y are Banach spaces, namely c 1 x y f (x) f (y) c 2

More information

MAGIC010 Ergodic Theory Lecture Entropy

MAGIC010 Ergodic Theory Lecture Entropy 7. Entropy 7. Introduction A natural question in mathematics is the so-called isomorphism problem : when are two mathematical objects of the same class the same (in some appropriately defined sense of

More information

FUNCTIONAL ANALYSIS CHRISTIAN REMLING

FUNCTIONAL ANALYSIS CHRISTIAN REMLING FUNCTIONAL ANALYSIS CHRISTIAN REMLING Contents 1. Metric and topological spaces 2 2. Banach spaces 12 3. Consequences of Baire s Theorem 30 4. Dual spaces and weak topologies 34 5. Hilbert spaces 50 6.

More information

x n x or x = T -limx n, if every open neighbourhood U of x contains x n for all but finitely many values of n

x n x or x = T -limx n, if every open neighbourhood U of x contains x n for all but finitely many values of n Note: This document was written by Prof. Richard Haydon, a previous lecturer for this course. 0. Preliminaries This preliminary chapter is an attempt to bring together important results from earlier courses

More information

Coarse Geometry. Phanuel Mariano. Fall S.i.g.m.a. Seminar. Why Coarse Geometry? Coarse Invariants A Coarse Equivalence to R 1

Coarse Geometry. Phanuel Mariano. Fall S.i.g.m.a. Seminar. Why Coarse Geometry? Coarse Invariants A Coarse Equivalence to R 1 Coarse Geometry 1 1 University of Connecticut Fall 2014 - S.i.g.m.a. Seminar Outline 1 Motivation 2 3 The partition space P ([a, b]). Preliminaries Main Result 4 Outline Basic Problem 1 Motivation 2 3

More information

Measures. Chapter Some prerequisites. 1.2 Introduction

Measures. Chapter Some prerequisites. 1.2 Introduction Lecture notes Course Analysis for PhD students Uppsala University, Spring 2018 Rostyslav Kozhan Chapter 1 Measures 1.1 Some prerequisites I will follow closely the textbook Real analysis: Modern Techniques

More information

Chapter 3: Baire category and open mapping theorems

Chapter 3: Baire category and open mapping theorems MA3421 2016 17 Chapter 3: Baire category and open mapping theorems A number of the major results rely on completeness via the Baire category theorem. 3.1 The Baire category theorem 3.1.1 Definition. A

More information

Functional Analysis I

Functional Analysis I Functional Analysis I Course Notes by Stefan Richter Transcribed and Annotated by Gregory Zitelli Polar Decomposition Definition. An operator W B(H) is called a partial isometry if W x = X for all x (ker

More information

08a. Operators on Hilbert spaces. 1. Boundedness, continuity, operator norms

08a. Operators on Hilbert spaces. 1. Boundedness, continuity, operator norms (February 24, 2017) 08a. Operators on Hilbert spaces Paul Garrett garrett@math.umn.edu http://www.math.umn.edu/ garrett/ [This document is http://www.math.umn.edu/ garrett/m/real/notes 2016-17/08a-ops

More information

Countable Borel Equivalence Relations: The Appendix

Countable Borel Equivalence Relations: The Appendix Countable Borel Equivalence Relations: The Appendix Simon Thomas Rutgers University 17th November 2007 Popa s Cocycle Superrigidity Theorem In this lecture, we shall sketch the proof of: Theorem (Popa)

More information

Solutions to Problem Set 1

Solutions to Problem Set 1 Solutions to Problem Set 1 18.904 Spring 2011 Problem 1 Statement. Let n 1 be an integer. Let CP n denote the set of all lines in C n+1 passing through the origin. There is a natural map π : C n+1 \ {0}

More information

Exercise Solutions to Functional Analysis

Exercise Solutions to Functional Analysis Exercise Solutions to Functional Analysis Note: References refer to M. Schechter, Principles of Functional Analysis Exersize that. Let φ,..., φ n be an orthonormal set in a Hilbert space H. Show n f n

More information

CHAPTER 6. Representations of compact groups

CHAPTER 6. Representations of compact groups CHAPTER 6 Representations of compact groups Throughout this chapter, denotes a compact group. 6.1. Examples of compact groups A standard theorem in elementary analysis says that a subset of C m (m a positive

More information

The Banach Tarski Paradox and Amenability Lecture 19: Reiter s Property and the Følner Condition. 6 October 2011

The Banach Tarski Paradox and Amenability Lecture 19: Reiter s Property and the Følner Condition. 6 October 2011 The Banach Tarski Paradox and Amenability Lecture 19: Reiter s Property and the Følner Condition 6 October 211 Invariant means and amenability Definition Let G be a locally compact group. An invariant

More information

Functional Analysis. Franck Sueur Metric spaces Definitions Completeness Compactness Separability...

Functional Analysis. Franck Sueur Metric spaces Definitions Completeness Compactness Separability... Functional Analysis Franck Sueur 2018-2019 Contents 1 Metric spaces 1 1.1 Definitions........................................ 1 1.2 Completeness...................................... 3 1.3 Compactness......................................

More information

3. G. Groups, as men, will be known by their actions. - Guillermo Moreno

3. G. Groups, as men, will be known by their actions. - Guillermo Moreno 3.1. The denition. 3. G Groups, as men, will be known by their actions. - Guillermo Moreno D 3.1. An action of a group G on a set X is a function from : G X! X such that the following hold for all g, h

More information