Ergodic properties of convolution operators
Jorge Galindo
Joint work with Enrique Jorda,
Universitat Politecnica de Valencia UPV (Spain).
BANACH ALGEBRAS AND APPLICATIONS 2019,
University of Manitoba in Winnipeg, 11-18 July 2019.
Jorge Galindo Ergodic properties of convolution operators
Mean ergodic operators
Notation
Let X be a Banach space.
I If E is a Banach space, L(E) = {T : X → X : T is bounded and linear }.
I If T ∈ L(E), T[n] =1
n
n∑k=1
T k .
Definition
Let T ∈ L(E).
I We say that T is a mean ergodic operator (ME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the strong operator topology.
I We say that T is a uniformly mean ergodic operator (UME, for short) if there is
an operator P ∈ L(E) such that limn→∞ T[n] = P in the operator norm.
I We say that T is a weakly mean ergodic operator (WME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the weak operator topology.
Jorge Galindo Ergodic properties of convolution operators
Mean ergodic operators
Notation
Let X be a Banach space.
I If E is a Banach space, L(E) = {T : X → X : T is bounded and linear }.
I If T ∈ L(E), T[n] =1
n
n∑k=1
T k .
Definition
Let T ∈ L(E).
I We say that T is a mean ergodic operator (ME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the strong operator topology.
I We say that T is a uniformly mean ergodic operator (UME, for short) if there is
an operator P ∈ L(E) such that limn→∞ T[n] = P in the operator norm.
I We say that T is a weakly mean ergodic operator (WME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the weak operator topology.
Jorge Galindo Ergodic properties of convolution operators
Mean ergodic operators
Notation
Let X be a Banach space.
I If E is a Banach space, L(E) = {T : X → X : T is bounded and linear }.
I If T ∈ L(E), T[n] =1
n
n∑k=1
T k .
Definition
Let T ∈ L(E).
I We say that T is a mean ergodic operator (ME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the strong operator topology.
I We say that T is a uniformly mean ergodic operator (UME, for short) if there is
an operator P ∈ L(E) such that limn→∞ T[n] = P in the operator norm.
I We say that T is a weakly mean ergodic operator (WME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the weak operator topology.
Jorge Galindo Ergodic properties of convolution operators
Mean ergodic operators
Notation
Let X be a Banach space.
I If E is a Banach space, L(E) = {T : X → X : T is bounded and linear }.
I If T ∈ L(E), T[n] =1
n
n∑k=1
T k .
Definition
Let T ∈ L(E).
I We say that T is a mean ergodic operator (ME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the strong operator topology.
I We say that T is a uniformly mean ergodic operator (UME, for short) if there is
an operator P ∈ L(E) such that limn→∞ T[n] = P in the operator norm.
I We say that T is a weakly mean ergodic operator (WME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the weak operator topology.
Jorge Galindo Ergodic properties of convolution operators
Mean ergodic operators
Notation
Let X be a Banach space.
I If E is a Banach space, L(E) = {T : X → X : T is bounded and linear }.
I If T ∈ L(E), T[n] =1
n
n∑k=1
T k .
Definition
Let T ∈ L(E).
I We say that T is a mean ergodic operator (ME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the strong operator topology.
I We say that T is a uniformly mean ergodic operator (UME, for short) if there is
an operator P ∈ L(E) such that limn→∞ T[n] = P in the operator norm.
I We say that T is a weakly mean ergodic operator (WME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the weak operator topology.
Jorge Galindo Ergodic properties of convolution operators
Mean ergodic operators
Notation
Let X be a Banach space.
I If E is a Banach space, L(E) = {T : X → X : T is bounded and linear }.
I If T ∈ L(E), T[n] =1
n
n∑k=1
T k .
Definition
Let T ∈ L(E).
I We say that T is a mean ergodic operator (ME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the strong operator topology.
I We say that T is a uniformly mean ergodic operator (UME, for short) if there is
an operator P ∈ L(E) such that limn→∞ T[n] = P in the operator norm.
I We say that T is a weakly mean ergodic operator (WME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the weak operator topology.
Jorge Galindo Ergodic properties of convolution operators
Mean ergodic operators
Notation
Let X be a Banach space.
I If E is a Banach space, L(E) = {T : X → X : T is bounded and linear }.
I If T ∈ L(E), T[n] =1
n
n∑k=1
T k .
Definition
Let T ∈ L(E).
I We say that T is a mean ergodic operator (ME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the strong operator topology.
I We say that T is a uniformly mean ergodic operator (UME, for short) if there is
an operator P ∈ L(E) such that limn→∞ T[n] = P in the operator norm.
I We say that T is a weakly mean ergodic operator (WME, for short) if there is an operator
P ∈ L(E) such that limn→∞ T[n] = P in the weak operator topology.
Jorge Galindo Ergodic properties of convolution operators
Convolution operators
Let G be a locally compact group with left Haar measure dmG .
Definition
Let µ1, µ2 ∈ M(G). We define:
I The convolution of measures:
〈µ1 ∗ µ2, f 〉 =
∫ ∫f (xy)dµ1(x)dµ2(y), for every f ∈ C0(G).
I The convolution operator: λp(µ) : Lp(G)→ Lp(G) given by
λp(µ)(f )(s) = (µ ∗ f )(s) :=
∫f (x−1s)dµ(x), for all f ∈ Lp(G) and all s ∈ G .
Jorge Galindo Ergodic properties of convolution operators
Convolution operators
Let G be a locally compact group with left Haar measure dmG .
Definition
Let µ1, µ2 ∈ M(G). We define:
I The convolution of measures:
〈µ1 ∗ µ2, f 〉 =
∫ ∫f (xy)dµ1(x)dµ2(y), for every f ∈ C0(G).
I The convolution operator: λp(µ) : Lp(G)→ Lp(G) given by
λp(µ)(f )(s) = (µ ∗ f )(s) :=
∫f (x−1s)dµ(x), for all f ∈ Lp(G) and all s ∈ G .
Jorge Galindo Ergodic properties of convolution operators
Convolution operators
Let G be a locally compact group with left Haar measure dmG .
Definition
Let µ1, µ2 ∈ M(G). We define:
I The convolution of measures:
〈µ1 ∗ µ2, f 〉 =
∫ ∫f (xy)dµ1(x)dµ2(y), for every f ∈ C0(G).
I The convolution operator: λp(µ) : Lp(G)→ Lp(G) given by
λp(µ)(f )(s) = (µ ∗ f )(s) :=
∫f (x−1s)dµ(x), for all f ∈ Lp(G) and all s ∈ G .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Vague topology: σ(M(G),C00(G))
Definition
A measure µ ∈ M(G) is vaguely ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Vague topology: σ(M(G),C00(G))
Definition
A measure µ ∈ M(G) is vaguely ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Vague topology: σ(M(G),C00(G))
Definition
A measure µ ∈ M(G) is vaguely ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Vague topology: σ(M(G),C00(G))
Definition
A measure µ ∈ M(G) is vaguely ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Vague topology: σ(M(G),C00(G))
Definition
A measure µ ∈ M(G) is vaguely ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Vague topology: σ(M(G),C00(G))
Definition
A measure µ ∈ M(G) is vaguely ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Vague topology: σ(M(G),C00(G))
Definition
A measure µ ∈ M(G) is vaguely ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Vague topology: σ(M(G),C00(G))
Definition
A measure µ ∈ M(G) is vaguely ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Vague topology: σ(M(G),C00(G))
Definition
A measure µ ∈ M(G) is vaguely ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Definition
A measure µ ∈ M(G) is said vaguely mean ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Definition
A measure µ ∈ M(G) is said vaguely mean ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Definition
A measure µ ∈ M(G) is said vaguely mean ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Definition
A measure µ ∈ M(G) is said vaguely mean ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Definition
A measure µ ∈ M(G) is said vaguely mean ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Definition
A measure µ ∈ M(G) is said vaguely mean ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Continuity of λp
Theorem
Let G be a locally compact group and consider the mapping λp : M(G)→ L(Lp(G)).
1 λp is vague-WOT continuous on norm bounded subsets of M(G), for 1 < p <∞.
2 If G is compact, then λp is vague-SOT sequentially continuous for 1 ≤ p <∞.
Definition
A measure µ ∈ M(G) is said vaguely mean ergodic if the sequence of means
µ[n] =µ+ µ2 + · · ·+ µn
nconverges to µc ∈ M(G) in the vague topology.
Theorem
Let µ ∈ M(G). Then:
1 If µ is vaguely ergodic, then λp(µ) is weakly mean ergodic .
2 If G is compact and µ is vaguely ergodic, then λp(µ) is mean ergodic .
Jorge Galindo Ergodic properties of convolution operators
Multiplication operators
T[n] =1
n
n∑k=1
Tk . T is ME if T[n] is SOT convergent, T is UME if T[n] is norm convergent.
Example (Multiplication operators)
Let X be a compact space, µ a measure on X and ϕ ∈ L∞(X , µ) with ‖ϕ‖∞ ≤ 1.
Define Mϕ : L2(X , µ)→ L2(X , µ) by (Mϕf )(x) = ϕ(x) · f (x). Then, for x with
ϕ(x) 6= 1 and any f ∈ L2(X , µ):
(Mϕ)[n]f =ϕ
n
1− ϕn
1− ϕ=⇒ lim
n→∞‖(Mϕ)[n]f −M1
ϕ−1({1})‖2 = 0.
It follows that Mϕ is mean ergodic.
This immediately implies:
Theorem (von Neumann’s mean ergodic theorem)
Unitary operators, even normal operators of norm ≤ 1, on Hilbert spaces are mean
ergodic .
If G is Abelian, convolution operators λ2(µ) are multiplication operators, via
Fourier-Stieltjes transforms
λ2(µ)f = (µ ∗ f ) = f · µ = Mµ f ,
where µ ∈ CB(G), f ∈ L2(G) and G = {χ : G → T : χ a continuous homomorphism}.
Jorge Galindo Ergodic properties of convolution operators
Multiplication operators
T[n] =1
n
n∑k=1
Tk . T is ME if T[n] is SOT convergent, T is UME if T[n] is norm convergent.
Example (Multiplication operators)
Let X be a compact space, µ a measure on X and ϕ ∈ L∞(X , µ) with ‖ϕ‖∞ ≤ 1.
Define Mϕ : L2(X , µ)→ L2(X , µ) by (Mϕf )(x) = ϕ(x) · f (x). Then, for x with
ϕ(x) 6= 1 and any f ∈ L2(X , µ):
(Mϕ)[n]f =ϕ
n
1− ϕn
1− ϕ=⇒ lim
n→∞‖(Mϕ)[n]f −M1
ϕ−1({1})‖2 = 0.
It follows that Mϕ is mean ergodic.
This immediately implies:
Theorem (von Neumann’s mean ergodic theorem)
Unitary operators, even normal operators of norm ≤ 1, on Hilbert spaces are mean
ergodic .
If G is Abelian, convolution operators λ2(µ) are multiplication operators, via
Fourier-Stieltjes transforms
λ2(µ)f = (µ ∗ f ) = f · µ = Mµ f ,
where µ ∈ CB(G), f ∈ L2(G) and G = {χ : G → T : χ a continuous homomorphism}.
Jorge Galindo Ergodic properties of convolution operators
Multiplication operators
Example (Multiplication operators)
Let X be a compact space, µ a measure on X and ϕ ∈ L∞(X , µ) with ‖ϕ‖∞ ≤ 1.
Define Mϕ : L2(X , µ)→ L2(X , µ) by (Mϕf )(x) = ϕ(x) · f (x). Then, for x with
ϕ(x) 6= 1 and any f ∈ L2(X , µ):
(Mϕ)[n]f =ϕ
n
1− ϕn
1− ϕ=⇒ lim
n→∞‖(Mϕ)[n]f −M1
ϕ−1({1})‖2 = 0.
It follows that Mϕ is mean ergodic.
This immediately implies:
Theorem (von Neumann’s mean ergodic theorem)
Unitary operators, even normal operators of norm ≤ 1, on Hilbert spaces are mean
ergodic .
If G is Abelian, convolution operators λ2(µ) are multiplication operators, via
Fourier-Stieltjes transforms
λ2(µ)f = (µ ∗ f ) = f · µ = Mµ f ,
where µ ∈ CB(G), f ∈ L2(G) and G = {χ : G → T : χ a continuous homomorphism}.
Jorge Galindo Ergodic properties of convolution operators
Multiplication operators
Example (Multiplication operators)
Let X be a compact space, µ a measure on X and ϕ ∈ L∞(X , µ) with ‖ϕ‖∞ ≤ 1.
Define Mϕ : L2(X , µ)→ L2(X , µ) by (Mϕf )(x) = ϕ(x) · f (x). Then, for x with
ϕ(x) 6= 1 and any f ∈ L2(X , µ):
(Mϕ)[n]f =ϕ
n
1− ϕn
1− ϕ=⇒ lim
n→∞‖(Mϕ)[n]f −M1
ϕ−1({1})‖2 = 0.
It follows that Mϕ is mean ergodic.
This immediately implies:
Theorem (von Neumann’s mean ergodic theorem)
Unitary operators, even normal operators of norm ≤ 1, on Hilbert spaces are mean
ergodic .
If G is Abelian, convolution operators λ2(µ) are multiplication operators, via
Fourier-Stieltjes transforms
λ2(µ)f = (µ ∗ f ) = f · µ = Mµ f ,
where µ ∈ CB(G), f ∈ L2(G) and G = {χ : G → T : χ a continuous homomorphism}.
Jorge Galindo Ergodic properties of convolution operators
Multiplication operators
Example (Multiplication operators)
Let X be a compact space, µ a measure on X and ϕ ∈ L∞(X , µ) with ‖ϕ‖∞ ≤ 1.
Define Mϕ : L2(X , µ)→ L2(X , µ) by (Mϕf )(x) = ϕ(x) · f (x). Then, for x with
ϕ(x) 6= 1 and any f ∈ L2(X , µ):
(Mϕ)[n]f =ϕ
n
1− ϕn
1− ϕ=⇒ lim
n→∞‖(Mϕ)[n]f −M1
ϕ−1({1})‖2 = 0.
It follows that Mϕ is mean ergodic.
This immediately implies:
Theorem (von Neumann’s mean ergodic theorem)
Unitary operators, even normal operators of norm ≤ 1, on Hilbert spaces are mean
ergodic .
If G is Abelian, convolution operators λ2(µ) are multiplication operators, via
Fourier-Stieltjes transforms
λ2(µ)f = (µ ∗ f ) = f · µ = Mµ f ,
where µ ∈ CB(G), f ∈ L2(G) and G = {χ : G → T : χ a continuous homomorphism}.Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem
If T ∈ L(E) is weakly mean ergodic , then:
I ‖T[n]‖n is a bounded sequence.
I WOT− limn→∞T n
n= 0.
I r(T ) ≤ 1.
Theorem
If T ∈ L(E) is mean ergodic , then:
I SOT− limn→∞T n
n= 0.
I E = Fix(T)⊕ (I − T ) (E).
Theorem (Yosida’s mean ergodic theorem)
If E is reflexive and ‖T[n]‖ is bounded, then T ∈ L(E) is mean ergodic if and only if
SOT− limn→∞T n
n= 0.
Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem
If T ∈ L(E) is weakly mean ergodic , then:
I ‖T[n]‖n is a bounded sequence.
I WOT− limn→∞T n
n= 0.
I r(T ) ≤ 1.
Theorem
If T ∈ L(E) is mean ergodic , then:
I SOT− limn→∞T n
n= 0.
I E = Fix(T)⊕ (I − T ) (E).
Theorem (Yosida’s mean ergodic theorem)
If E is reflexive and ‖T[n]‖ is bounded, then T ∈ L(E) is mean ergodic if and only if
SOT− limn→∞T n
n= 0.
Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem
If T ∈ L(E) is weakly mean ergodic , then:
I ‖T[n]‖n is a bounded sequence.
I WOT− limn→∞T n
n= 0.
I r(T ) ≤ 1.
Theorem
If T ∈ L(E) is mean ergodic , then:
I SOT− limn→∞T n
n= 0.
I E = Fix(T)⊕ (I − T ) (E).
Theorem (Yosida’s mean ergodic theorem)
If E is reflexive and ‖T[n]‖ is bounded, then T ∈ L(E) is mean ergodic if and only if
SOT− limn→∞T n
n= 0.
Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem
If T ∈ L(E) is weakly mean ergodic , then:
I ‖T[n]‖n is a bounded sequence.
I WOT− limn→∞T n
n= 0.
I r(T ) ≤ 1.
Theorem
If T ∈ L(E) is mean ergodic , then:
I SOT− limn→∞T n
n= 0.
I E = Fix(T)⊕ (I − T ) (E).
Theorem (Yosida’s mean ergodic theorem)
If E is reflexive and ‖T[n]‖ is bounded, then T ∈ L(E) is mean ergodic if and only if
SOT− limn→∞T n
n= 0.
Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem
If T ∈ L(E) is weakly mean ergodic , then:
I ‖T[n]‖n is a bounded sequence.
I WOT− limn→∞T n
n= 0.
I r(T ) ≤ 1.
Theorem
If T ∈ L(E) is mean ergodic , then:
I SOT− limn→∞T n
n= 0.
I E = Fix(T)⊕ (I − T ) (E).
Theorem (Yosida’s mean ergodic theorem)
If E is reflexive and ‖T[n]‖ is bounded, then T ∈ L(E) is mean ergodic if and only if
SOT− limn→∞T n
n= 0.
Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem
If T ∈ L(E) is weakly mean ergodic , then:
I ‖T[n]‖n is a bounded sequence.
I WOT− limn→∞T n
n= 0.
I r(T ) ≤ 1.
Theorem
If T ∈ L(E) is mean ergodic , then:
I SOT− limn→∞T n
n= 0.
I E = Fix(T)⊕ (I − T ) (E).
Theorem (Yosida’s mean ergodic theorem)
If E is reflexive and ‖T[n]‖ is bounded, then T ∈ L(E) is mean ergodic if and only if
SOT− limn→∞T n
n= 0.
Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem
If T ∈ L(E) is weakly mean ergodic , then:
I ‖T[n]‖n is a bounded sequence.
I WOT− limn→∞T n
n= 0.
I r(T ) ≤ 1.
Theorem
If T ∈ L(E) is mean ergodic , then:
I SOT− limn→∞T n
n= 0.
I E = Fix(T)⊕ (I − T ) (E).
Theorem (Yosida’s mean ergodic theorem)
If E is reflexive and ‖T[n]‖ is bounded, then T ∈ L(E) is mean ergodic if and only if
SOT− limn→∞T n
n= 0.
Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem
If T ∈ L(E) is weakly mean ergodic , then:
I ‖T[n]‖n is a bounded sequence.
I WOT− limn→∞T n
n= 0.
I r(T ) ≤ 1.
Theorem
If T ∈ L(E) is mean ergodic , then:
I SOT− limn→∞T n
n= 0.
I E = Fix(T)⊕ (I − T ) (E).
Theorem (Yosida’s mean ergodic theorem)
If E is reflexive and ‖T[n]‖ is bounded, then T ∈ L(E) is mean ergodic if and only if
SOT− limn→∞T n
n= 0.
Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem (Dunford 1943, Lin 1974)
T ∈ L(E) with SOT− limn→∞T n
n= 0. TFAE:
I T is uniformly mean Ergodic .
I (I − T ) (E) is closed.
I E = Fix(T)⊕ (I − T ) (E).
I Either 1 /∈ σ(T ) or 1 is a pole of order 1 of the resolvent of T .
Corollary
If r(T ) < 1, then T is uniformly mean Ergodic .
Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem (Dunford 1943, Lin 1974)
T ∈ L(E) with SOT− limn→∞T n
n= 0. TFAE:
I T is uniformly mean Ergodic .
I (I − T ) (E) is closed.
I E = Fix(T)⊕ (I − T ) (E).
I Either 1 /∈ σ(T ) or 1 is a pole of order 1 of the resolvent of T .
Corollary
If r(T ) < 1, then T is uniformly mean Ergodic .
Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem (Dunford 1943, Lin 1974)
T ∈ L(E) with SOT− limn→∞T n
n= 0. TFAE:
I T is uniformly mean Ergodic .
I (I − T ) (E) is closed.
I E = Fix(T)⊕ (I − T ) (E).
I Either 1 /∈ σ(T ) or 1 is a pole of order 1 of the resolvent of T .
Corollary
If r(T ) < 1, then T is uniformly mean Ergodic .
Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem (Dunford 1943, Lin 1974)
T ∈ L(E) with SOT− limn→∞T n
n= 0. TFAE:
I T is uniformly mean Ergodic .
I (I − T ) (E) is closed.
I E = Fix(T)⊕ (I − T ) (E).
I Either 1 /∈ σ(T ) or 1 is a pole of order 1 of the resolvent of T .
Corollary
If r(T ) < 1, then T is uniformly mean Ergodic .
Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem (Dunford 1943, Lin 1974)
T ∈ L(E) with SOT− limn→∞T n
n= 0. TFAE:
I T is uniformly mean Ergodic .
I (I − T ) (E) is closed.
I E = Fix(T)⊕ (I − T ) (E).
I Either 1 /∈ σ(T ) or 1 is a pole of order 1 of the resolvent of T .
Corollary
If r(T ) < 1, then T is uniformly mean Ergodic .
Jorge Galindo Ergodic properties of convolution operators
General properties of mean ergodic operators
Theorem (Dunford 1943, Lin 1974)
T ∈ L(E) with SOT− limn→∞T n
n= 0. TFAE:
I T is uniformly mean Ergodic .
I (I − T ) (E) is closed.
I E = Fix(T)⊕ (I − T ) (E).
I Either 1 /∈ σ(T ) or 1 is a pole of order 1 of the resolvent of T .
Corollary
If r(T ) < 1, then T is uniformly mean Ergodic .
Jorge Galindo Ergodic properties of convolution operators
A not so simple reduction
Theorem (Herz 1973, Derighetti 1974)
If H is a closed subgroup of G , then the restriction mapping R : Ap(G)→ Ap(H) is
almost an isometry. Its adjoint T∗PMp(H)→ PMp(G) is a multiplicative linear
isometry.
Theorem
If H is a closed subgroup of G and µ ∈ M(G) is supported in H, then λpH(µ) is mean
ergodic (resp. uniformly mean Ergodic ) if and only if λpG (µ) is mean ergodic (resp.
uniformly mean Ergodic ).
Jorge Galindo Ergodic properties of convolution operators
A not so simple reduction
Theorem (Herz 1973, Derighetti 1974)
If H is a closed subgroup of G , then the restriction mapping R : Ap(G)→ Ap(H) is
almost an isometry. Its adjoint T∗PMp(H)→ PMp(G) is a multiplicative linear
isometry.
Theorem
If H is a closed subgroup of G and µ ∈ M(G) is supported in H, then λpH(µ) is mean
ergodic (resp. uniformly mean Ergodic ) if and only if λpG (µ) is mean ergodic (resp.
uniformly mean Ergodic ).
Jorge Galindo Ergodic properties of convolution operators
A simple case, normal measures
Definition
If µ ∈ M(G), µ∗ is defined so that 〈µ∗, h 〉 =⟨µ, h
⟩, with f (s) = f (s−1).
We say that µ isoperator normal if µ ∗ µ∗ = µ∗ ∗ µ.
λ2(µ)∗ = λ2(µ)∗, so µ is operator normal precisely when λ2 is a normal operator.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is mean ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is uniformly mean Ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1 and 1 is not an accumulation point of σ(λ2(µ)).
Jorge Galindo Ergodic properties of convolution operators
A simple case, normal measures
Definition
If µ ∈ M(G), µ∗ is defined so that 〈µ∗, h 〉 =⟨µ, h
⟩, with f (s) = f (s−1).
We say that µ isoperator normal if µ ∗ µ∗ = µ∗ ∗ µ.
λ2(µ)∗ = λ2(µ)∗, so µ is operator normal precisely when λ2 is a normal operator.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is mean ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is uniformly mean Ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1 and 1 is not an accumulation point of σ(λ2(µ)).
Jorge Galindo Ergodic properties of convolution operators
A simple case, normal measures
Definition
If µ ∈ M(G), µ∗ is defined so that 〈µ∗, h 〉 =⟨µ, h
⟩, with f (s) = f (s−1).
We say that µ isoperator normal if µ ∗ µ∗ = µ∗ ∗ µ.
λ2(µ)∗ = λ2(µ)∗, so µ is operator normal precisely when λ2 is a normal operator.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is mean ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is uniformly mean Ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1 and 1 is not an accumulation point of σ(λ2(µ)).
Jorge Galindo Ergodic properties of convolution operators
A simple case, normal measures
Definition
If µ ∈ M(G), µ∗ is defined so that 〈µ∗, h 〉 =⟨µ, h
⟩, with f (s) = f (s−1).
We say that µ isoperator normal if µ ∗ µ∗ = µ∗ ∗ µ.
λ2(µ)∗ = λ2(µ)∗, so µ is operator normal precisely when λ2 is a normal operator.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is mean ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is uniformly mean Ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1 and 1 is not an accumulation point of σ(λ2(µ)).
Jorge Galindo Ergodic properties of convolution operators
A simple case, normal measures
Definition
If µ ∈ M(G), µ∗ is defined so that 〈µ∗, h 〉 =⟨µ, h
⟩, with f (s) = f (s−1).
We say that µ isoperator normal if µ ∗ µ∗ = µ∗ ∗ µ.
λ2(µ)∗ = λ2(µ)∗, so µ is operator normal precisely when λ2 is a normal operator.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is mean ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is uniformly mean Ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1 and 1 is not an accumulation point of σ(λ2(µ)).
Jorge Galindo Ergodic properties of convolution operators
A simple case, normal measures
Definition
If µ ∈ M(G), µ∗ is defined so that 〈µ∗, h 〉 =⟨µ, h
⟩, with f (s) = f (s−1).
We say that µ isoperator normal if µ ∗ µ∗ = µ∗ ∗ µ.
λ2(µ)∗ = λ2(µ)∗, so µ is operator normal precisely when λ2 is a normal operator.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is mean ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is uniformly mean Ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1 and 1 is not an accumulation point of σ(λ2(µ)).
Jorge Galindo Ergodic properties of convolution operators
A simple case, normal measures
Definition
If µ ∈ M(G), µ∗ is defined so that 〈µ∗, h 〉 =⟨µ, h
⟩, with f (s) = f (s−1).
We say that µ isoperator normal if µ ∗ µ∗ = µ∗ ∗ µ.
λ2(µ)∗ = λ2(µ)∗, so µ is operator normal precisely when λ2 is a normal operator.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is mean ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is uniformly mean Ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1 and 1 is not an accumulation point of σ(λ2(µ)).
Jorge Galindo Ergodic properties of convolution operators
A simple case, normal measures
Definition
If µ ∈ M(G), µ∗ is defined so that 〈µ∗, h 〉 =⟨µ, h
⟩, with f (s) = f (s−1).
We say that µ isoperator normal if µ ∗ µ∗ = µ∗ ∗ µ.
λ2(µ)∗ = λ2(µ)∗, so µ is operator normal precisely when λ2 is a normal operator.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is mean ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is uniformly mean Ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1 and 1 is not an accumulation point of σ(λ2(µ)).
Jorge Galindo Ergodic properties of convolution operators
A simple case, normal measures
Definition
If µ ∈ M(G), µ∗ is defined so that 〈µ∗, h 〉 =⟨µ, h
⟩, with f (s) = f (s−1).
We say that µ isoperator normal if µ ∗ µ∗ = µ∗ ∗ µ.
λ2(µ)∗ = λ2(µ)∗, so µ is operator normal precisely when λ2 is a normal operator.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is mean ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1.
Theorem
Let µ ∈ M(G) be operator normal. TFAE:
I λ2(µ) is uniformly mean Ergodic .
I r(λ2(µ)) = ‖λ2(µ)‖ ≤ 1 and 1 is not an accumulation point of σ(λ2(µ)).
Jorge Galindo Ergodic properties of convolution operators
Amenable groups
• Notation: Hµ ≡ closed subgroup generated by supp(µ).
Amenable groups satisfy property Pp for 1 ≤ p <∞: for any ε > 0 and any compact K ⊆ G
there is f ∈ C00(G) with ‖f ‖p = 1 such that ‖x−1 f − f ‖p < ε for x ∈ K .
Theorem (Well-known)
If G is amenable and µ ∈ M(G), then µ(G) is an approximate eigenvalue of λp(µ).
Corollary
Let µ ∈ M+(G) so that Hµ is amenable and 1 < p <∞. TFAE:
I λp(µ) is mean ergodic .
I λp(µ) is weakly mean ergodic .
I ‖µ‖ ≤ 1.
I µ is vaguely ergodic
Theorem
Let µ ∈ M+(G) be operator normal so that Hµ is amenable and let 1 < p <∞. Then λp(µ) is
uniformly mean Ergodic if and only if ‖µ‖ ≤ 1 and 1 is not an accumulation point of σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Amenable groups
• Notation: Hµ ≡ closed subgroup generated by supp(µ).
Amenable groups satisfy property Pp for 1 ≤ p <∞: for any ε > 0 and any compact K ⊆ G
there is f ∈ C00(G) with ‖f ‖p = 1 such that ‖x−1 f − f ‖p < ε for x ∈ K .
Theorem (Well-known)
If G is amenable and µ ∈ M(G), then µ(G) is an approximate eigenvalue of λp(µ).
Corollary
Let µ ∈ M+(G) so that Hµ is amenable and 1 < p <∞. TFAE:
I λp(µ) is mean ergodic .
I λp(µ) is weakly mean ergodic .
I ‖µ‖ ≤ 1.
I µ is vaguely ergodic
Theorem
Let µ ∈ M+(G) be operator normal so that Hµ is amenable and let 1 < p <∞. Then λp(µ) is
uniformly mean Ergodic if and only if ‖µ‖ ≤ 1 and 1 is not an accumulation point of σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Amenable groups
• Notation: Hµ ≡ closed subgroup generated by supp(µ).
Amenable groups satisfy property Pp for 1 ≤ p <∞: for any ε > 0 and any compact K ⊆ G
there is f ∈ C00(G) with ‖f ‖p = 1 such that ‖x−1 f − f ‖p < ε for x ∈ K .
Theorem (Well-known)
If G is amenable and µ ∈ M(G), then µ(G) is an approximate eigenvalue of λp(µ).
Corollary
Let µ ∈ M+(G) so that Hµ is amenable and 1 < p <∞. TFAE:
I λp(µ) is mean ergodic .
I λp(µ) is weakly mean ergodic .
I ‖µ‖ ≤ 1.
I µ is vaguely ergodic
Theorem
Let µ ∈ M+(G) be operator normal so that Hµ is amenable and let 1 < p <∞. Then λp(µ) is
uniformly mean Ergodic if and only if ‖µ‖ ≤ 1 and 1 is not an accumulation point of σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Amenable groups
• Notation: Hµ ≡ closed subgroup generated by supp(µ).
Amenable groups satisfy property Pp for 1 ≤ p <∞: for any ε > 0 and any compact K ⊆ G
there is f ∈ C00(G) with ‖f ‖p = 1 such that ‖x−1 f − f ‖p < ε for x ∈ K .
Theorem (Well-known)
If G is amenable and µ ∈ M(G), then µ(G) is an approximate eigenvalue of λp(µ).
Corollary
Let µ ∈ M+(G) so that Hµ is amenable and 1 < p <∞. TFAE:
I λp(µ) is mean ergodic .
I λp(µ) is weakly mean ergodic .
I ‖µ‖ ≤ 1.
I µ is vaguely ergodic
Theorem
Let µ ∈ M+(G) be operator normal so that Hµ is amenable and let 1 < p <∞. Then λp(µ) is
uniformly mean Ergodic if and only if ‖µ‖ ≤ 1 and 1 is not an accumulation point of σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Amenable groups
• Notation: Hµ ≡ closed subgroup generated by supp(µ).
Amenable groups satisfy property Pp for 1 ≤ p <∞: for any ε > 0 and any compact K ⊆ G
there is f ∈ C00(G) with ‖f ‖p = 1 such that ‖x−1 f − f ‖p < ε for x ∈ K .
Theorem (Well-known)
If G is amenable and µ ∈ M(G), then µ(G) is an approximate eigenvalue of λp(µ).
Corollary
Let µ ∈ M+(G) so that Hµ is amenable and 1 < p <∞. TFAE:
I λp(µ) is mean ergodic .
I λp(µ) is weakly mean ergodic .
I ‖µ‖ ≤ 1.
I µ is vaguely ergodic
Theorem
Let µ ∈ M+(G) be operator normal so that Hµ is amenable and let 1 < p <∞. Then λp(µ) is
uniformly mean Ergodic if and only if ‖µ‖ ≤ 1 and 1 is not an accumulation point of σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Amenable groups
• Notation: Hµ ≡ closed subgroup generated by supp(µ).
Amenable groups satisfy property Pp for 1 ≤ p <∞: for any ε > 0 and any compact K ⊆ G
there is f ∈ C00(G) with ‖f ‖p = 1 such that ‖x−1 f − f ‖p < ε for x ∈ K .
Theorem (Well-known)
If G is amenable and µ ∈ M(G), then µ(G) is an approximate eigenvalue of λp(µ).
Corollary
Let µ ∈ M+(G) so that Hµ is amenable and 1 < p <∞. TFAE:
I λp(µ) is mean ergodic .
I λp(µ) is weakly mean ergodic .
I ‖µ‖ ≤ 1.
I µ is vaguely ergodic
Theorem
Let µ ∈ M+(G) be operator normal so that Hµ is amenable and let 1 < p <∞. Then λp(µ) is
uniformly mean Ergodic if and only if ‖µ‖ ≤ 1 and 1 is not an accumulation point of σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Amenable groups
• Notation: Hµ ≡ closed subgroup generated by supp(µ).
Amenable groups satisfy property Pp for 1 ≤ p <∞: for any ε > 0 and any compact K ⊆ G
there is f ∈ C00(G) with ‖f ‖p = 1 such that ‖x−1 f − f ‖p < ε for x ∈ K .
Theorem (Well-known)
If G is amenable and µ ∈ M(G), then µ(G) is an approximate eigenvalue of λp(µ).
Corollary
Let µ ∈ M+(G) so that Hµ is amenable and 1 < p <∞. TFAE:
I λp(µ) is mean ergodic .
I λp(µ) is weakly mean ergodic .
I ‖µ‖ ≤ 1.
I µ is vaguely ergodic
Theorem
Let µ ∈ M+(G) be operator normal so that Hµ is amenable and let 1 < p <∞. Then λp(µ) is
uniformly mean Ergodic if and only if ‖µ‖ ≤ 1 and 1 is not an accumulation point of σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Amenable groups
• Notation: Hµ ≡ closed subgroup generated by supp(µ).
Amenable groups satisfy property Pp for 1 ≤ p <∞: for any ε > 0 and any compact K ⊆ G
there is f ∈ C00(G) with ‖f ‖p = 1 such that ‖x−1 f − f ‖p < ε for x ∈ K .
Theorem (Well-known)
If G is amenable and µ ∈ M(G), then µ(G) is an approximate eigenvalue of λp(µ).
Corollary
Let µ ∈ M+(G) so that Hµ is amenable and 1 < p <∞. TFAE:
I λp(µ) is mean ergodic .
I λp(µ) is weakly mean ergodic .
I ‖µ‖ ≤ 1.
I µ is vaguely ergodic
Theorem
Let µ ∈ M+(G) be operator normal so that Hµ is amenable and let 1 < p <∞. Then λp(µ) is
uniformly mean Ergodic if and only if ‖µ‖ ≤ 1 and 1 is not an accumulation point of σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Amenable groups
• Notation: Hµ ≡ closed subgroup generated by supp(µ).
Amenable groups satisfy property Pp for 1 ≤ p <∞: for any ε > 0 and any compact K ⊆ G
there is f ∈ C00(G) with ‖f ‖p = 1 such that ‖x−1 f − f ‖p < ε for x ∈ K .
Theorem (Well-known)
If G is amenable and µ ∈ M(G), then µ(G) is an approximate eigenvalue of λp(µ).
Corollary
Let µ ∈ M+(G) so that Hµ is amenable and 1 < p <∞. TFAE:
I λp(µ) is mean ergodic .
I λp(µ) is weakly mean ergodic .
I ‖µ‖ ≤ 1.
I µ is vaguely ergodic
Theorem
Let µ ∈ M+(G) be operator normal so that Hµ is amenable and let 1 < p <∞. Then λp(µ) is
uniformly mean Ergodic if and only if ‖µ‖ ≤ 1 and 1 is not an accumulation point of σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Fixed points and uniform mean ergodicity
(Dunford) iF T ∈ L(E) satisfies SOT− limn→∞Tn
n= 0. T is uniformly mean Ergodic if and only if either
1 /∈ σ(T ) or 1 is a pole of order 1 of the resolvent of T .
Notation: P(G) ≡ Probability measures on G .
Corollary
If µ ∈ M(G) satisfies SOT− limn→∞λp(µ)
n= 0 and Fix(λp(µ)) = {0}, then λp(µ)
is uniformly mean Ergodic if and only if 1 /∈ σ(λp(µ).
Theorem (Choquet-Deny for Abelian G , Chu for . . . )
Let µ ∈ P(G) . If f ∈ Lp(G), 1 < p <∞ and µ ∗ f = f , then t−1|f| = |f|, for each
t ∈ supp(µ).
Corollary
Let µ ∈ P(G) with noncompact Hµ. If f ∈ Lp(G) and µ ∗ f = f , then f = 0.
Theorem
Let µ ∈ P(G) with noncompact Hµ. Then λp(µ) is uniformly mean Ergodic if and
only if 1 /∈ σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Fixed points and uniform mean ergodicity
(Dunford) iF T ∈ L(E) satisfies SOT− limn→∞Tn
n= 0. T is uniformly mean Ergodic if and only if either
1 /∈ σ(T ) or 1 is a pole of order 1 of the resolvent of T .
Notation: P(G) ≡ Probability measures on G .
Corollary
If µ ∈ M(G) satisfies SOT− limn→∞λp(µ)
n= 0 and Fix(λp(µ)) = {0}, then λp(µ)
is uniformly mean Ergodic if and only if 1 /∈ σ(λp(µ).
Theorem (Choquet-Deny for Abelian G , Chu for . . . )
Let µ ∈ P(G) . If f ∈ Lp(G), 1 < p <∞ and µ ∗ f = f , then t−1|f| = |f|, for each
t ∈ supp(µ).
Corollary
Let µ ∈ P(G) with noncompact Hµ. If f ∈ Lp(G) and µ ∗ f = f , then f = 0.
Theorem
Let µ ∈ P(G) with noncompact Hµ. Then λp(µ) is uniformly mean Ergodic if and
only if 1 /∈ σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Fixed points and uniform mean ergodicity
(Dunford) iF T ∈ L(E) satisfies SOT− limn→∞Tn
n= 0. T is uniformly mean Ergodic if and only if either
1 /∈ σ(T ) or 1 is a pole of order 1 of the resolvent of T .
Notation: P(G) ≡ Probability measures on G .
Corollary
If µ ∈ M(G) satisfies SOT− limn→∞λp(µ)
n= 0 and Fix(λp(µ)) = {0}, then λp(µ)
is uniformly mean Ergodic if and only if 1 /∈ σ(λp(µ).
Theorem (Choquet-Deny for Abelian G , Chu for . . . )
Let µ ∈ P(G) . If f ∈ Lp(G), 1 < p <∞ and µ ∗ f = f , then t−1|f| = |f|, for each
t ∈ supp(µ).
Corollary
Let µ ∈ P(G) with noncompact Hµ. If f ∈ Lp(G) and µ ∗ f = f , then f = 0.
Theorem
Let µ ∈ P(G) with noncompact Hµ. Then λp(µ) is uniformly mean Ergodic if and
only if 1 /∈ σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Fixed points and uniform mean ergodicity
(Dunford) iF T ∈ L(E) satisfies SOT− limn→∞Tn
n= 0. T is uniformly mean Ergodic if and only if either
1 /∈ σ(T ) or 1 is a pole of order 1 of the resolvent of T .
Notation: P(G) ≡ Probability measures on G .
Corollary
If µ ∈ M(G) satisfies SOT− limn→∞λp(µ)
n= 0 and Fix(λp(µ)) = {0}, then λp(µ)
is uniformly mean Ergodic if and only if 1 /∈ σ(λp(µ).
Theorem (Choquet-Deny for Abelian G , Chu for . . . )
Let µ ∈ P(G) . If f ∈ Lp(G), 1 < p <∞ and µ ∗ f = f , then t−1|f| = |f|, for each
t ∈ supp(µ).
Corollary
Let µ ∈ P(G) with noncompact Hµ. If f ∈ Lp(G) and µ ∗ f = f , then f = 0.
Theorem
Let µ ∈ P(G) with noncompact Hµ. Then λp(µ) is uniformly mean Ergodic if and
only if 1 /∈ σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Fixed points and uniform mean ergodicity
(Dunford) iF T ∈ L(E) satisfies SOT− limn→∞Tn
n= 0. T is uniformly mean Ergodic if and only if either
1 /∈ σ(T ) or 1 is a pole of order 1 of the resolvent of T .
Notation: P(G) ≡ Probability measures on G .
Corollary
If µ ∈ M(G) satisfies SOT− limn→∞λp(µ)
n= 0 and Fix(λp(µ)) = {0}, then λp(µ)
is uniformly mean Ergodic if and only if 1 /∈ σ(λp(µ).
Theorem (Choquet-Deny for Abelian G , Chu for . . . )
Let µ ∈ P(G) . If f ∈ Lp(G), 1 < p <∞ and µ ∗ f = f , then t−1|f| = |f|, for each
t ∈ supp(µ).
Corollary
Let µ ∈ P(G) with noncompact Hµ. If f ∈ Lp(G) and µ ∗ f = f , then f = 0.
Theorem
Let µ ∈ P(G) with noncompact Hµ. Then λp(µ) is uniformly mean Ergodic if and
only if 1 /∈ σ(λp(µ)).
Jorge Galindo Ergodic properties of convolution operators
Mise-en-scene of the spectral radius
Lemma (Bekka 2017 for p = 2 and µ ∈ P(G))
Let µ ∈ M+(G) with ‖λp(µ)‖ ≤ 1, 1 < p <∞. If r(λp(µ)) = 1, then 1 ∈ σap(λp(µ)).
Theorem
Let µ ∈ P(G) with noncompact Hµ and let 1 < p <∞. Then λp(µ) is uniformly
mean Ergodic if and only if r(λp(µ)) < 1.
Corollary
Let µ ∈ P(G) with Hµ noncompact but amenable, 1 < p <∞. Then λp(µ) is
uniformly mean Ergodic if and only if ‖µ‖ < 1.
Jorge Galindo Ergodic properties of convolution operators
Mise-en-scene of the spectral radius
Lemma (Bekka 2017 for p = 2 and µ ∈ P(G))
Let µ ∈ M+(G) with ‖λp(µ)‖ ≤ 1, 1 < p <∞. If r(λp(µ)) = 1, then 1 ∈ σap(λp(µ)).
Theorem
Let µ ∈ P(G) with noncompact Hµ and let 1 < p <∞. Then λp(µ) is uniformly
mean Ergodic if and only if r(λp(µ)) < 1.
Corollary
Let µ ∈ P(G) with Hµ noncompact but amenable, 1 < p <∞. Then λp(µ) is
uniformly mean Ergodic if and only if ‖µ‖ < 1.
Jorge Galindo Ergodic properties of convolution operators
Mise-en-scene of the spectral radius
Lemma (Bekka 2017 for p = 2 and µ ∈ P(G))
Let µ ∈ M+(G) with ‖λp(µ)‖ ≤ 1, 1 < p <∞. If r(λp(µ)) = 1, then 1 ∈ σap(λp(µ)).
Theorem
Let µ ∈ P(G) with noncompact Hµ and let 1 < p <∞. Then λp(µ) is uniformly
mean Ergodic if and only if r(λp(µ)) < 1.
Corollary
Let µ ∈ P(G) with Hµ noncompact but amenable, 1 < p <∞. Then λp(µ) is
uniformly mean Ergodic if and only if ‖µ‖ < 1.
Jorge Galindo Ergodic properties of convolution operators
Summary
Consider the following properties of µ ∈ M(G), µ > 0 , µ 6= δe :
1 µ is vaguely ergodic.
2 λp(µ) is mean ergodic , 1 < p <∞.
3 λ1(µ) is mean ergodic .
4 λp(µ) is uniformly mean Ergodic , 1 < p <∞.
If Hµ is compact and (‖µ[n]‖)n is bounded, then properties 1–3 are equivalent. If
µ = f dmG , for some f ∈ L1(G), then properties 1–4 are equivalent.
If G is amenable, then properties 1 and 2 are both equivalent to ‖µ‖ ≤ 1. If Hµ is
not compact, (e.g., if G = R for any µ), then 3 never happens and 4 is equivalent to
‖µ‖ = r(λp(µ)) < 1.
Examples
Jorge Galindo Ergodic properties of convolution operators
Summary
Consider the following properties of µ ∈ M(G), µ > 0 , µ 6= δe :
1 µ is vaguely ergodic.
2 λp(µ) is mean ergodic , 1 < p <∞.
3 λ1(µ) is mean ergodic .
4 λp(µ) is uniformly mean Ergodic , 1 < p <∞.
If Hµ is compact and (‖µ[n]‖)n is bounded, then properties 1–3 are equivalent. If
µ = f dmG , for some f ∈ L1(G), then properties 1–4 are equivalent.
If G is amenable, then properties 1 and 2 are both equivalent to ‖µ‖ ≤ 1. If Hµ is
not compact, (e.g., if G = R for any µ), then 3 never happens and 4 is equivalent to
‖µ‖ = r(λp(µ)) < 1.
Examples
Jorge Galindo Ergodic properties of convolution operators
Summary
Consider the following properties of µ ∈ M(G), µ > 0 , µ 6= δe :
1 µ is vaguely ergodic.
2 λp(µ) is mean ergodic , 1 < p <∞.
3 λ1(µ) is mean ergodic .
4 λp(µ) is uniformly mean Ergodic , 1 < p <∞.
If Hµ is compact and (‖µ[n]‖)n is bounded, then properties 1–3 are equivalent. If
µ = f dmG , for some f ∈ L1(G), then properties 1–4 are equivalent.
If G is amenable, then properties 1 and 2 are both equivalent to ‖µ‖ ≤ 1. If Hµ is
not compact, (e.g., if G = R for any µ), then 3 never happens and 4 is equivalent to
‖µ‖ = r(λp(µ)) < 1.
Examples
Jorge Galindo Ergodic properties of convolution operators
Summary
Consider the following properties of µ ∈ M(G), µ > 0 , µ 6= δe :
1 µ is vaguely ergodic.
2 λp(µ) is mean ergodic , 1 < p <∞.
3 λ1(µ) is mean ergodic .
4 λp(µ) is uniformly mean Ergodic , 1 < p <∞.
If Hµ is compact and (‖µ[n]‖)n is bounded, then properties 1–3 are equivalent. If
µ = f dmG , for some f ∈ L1(G), then properties 1–4 are equivalent.
If G is amenable, then properties 1 and 2 are both equivalent to ‖µ‖ ≤ 1. If Hµ is
not compact, (e.g., if G = R for any µ), then 3 never happens and 4 is equivalent to
‖µ‖ = r(λp(µ)) < 1.
Examples
I If G is not amenable, 4 may hold and yet 1 fail. See next slide.
Jorge Galindo Ergodic properties of convolution operators
Summary
Consider the following properties of µ ∈ M(G), µ > 0 , µ 6= δe :
1 µ is vaguely ergodic.
2 λp(µ) is mean ergodic , 1 < p <∞.
3 λ1(µ) is mean ergodic .
4 λp(µ) is uniformly mean Ergodic , 1 < p <∞.
If Hµ is compact and (‖µ[n]‖)n is bounded, then properties 1–3 are equivalent. If
µ = f dmG , for some f ∈ L1(G), then properties 1–4 are equivalent.
If G is amenable, then properties 1 and 2 are both equivalent to ‖µ‖ ≤ 1. If Hµ is
not compact, (e.g., if G = R for any µ), then 3 never happens and 4 is equivalent to
‖µ‖ = r(λp(µ)) < 1.
Examples
I If (‖µ[n]‖)n is not bounded, then 2 may hold but 1 and 3 fail, even if G is
compact. Take µ = δs − δs2 ∈ M(T), where s3 = 1, s 6= 1.
Jorge Galindo Ergodic properties of convolution operators
Summary
Consider the following properties of µ ∈ M(G), µ > 0 , µ 6= δe :
1 µ is vaguely ergodic.
2 λp(µ) is mean ergodic , 1 < p <∞.
3 λ1(µ) is mean ergodic .
4 λp(µ) is uniformly mean Ergodic , 1 < p <∞.
If Hµ is compact and (‖µ[n]‖)n is bounded, then properties 1–3 are equivalent. If
µ = f dmG , for some f ∈ L1(G), then properties 1–4 are equivalent.
If G is amenable, then properties 1 and 2 are both equivalent to ‖µ‖ ≤ 1. If Hµ is
not compact, (e.g., if G = R for any µ), then 3 never happens and 4 is equivalent to
‖µ‖ = r(λp(µ)) < 1.
Examples
I If Hµ is compact, then 4 is not equivalent to ‖µ‖ = 1. Let G = T, put x1 = e2πiq
and x2 = e2πit with q ∈ Q and t ∈ R \ Q. Then λ2(δx1 ) is uniformly mean
Ergodic while λ2(δx2 ) is not uniformly mean Ergodic .
Jorge Galindo Ergodic properties of convolution operators
Summary
Consider the following properties of µ ∈ M(G), µ > 0 , µ 6= δe :
1 µ is vaguely ergodic.
2 λp(µ) is mean ergodic , 1 < p <∞.
3 λ1(µ) is mean ergodic .
4 λp(µ) is uniformly mean Ergodic , 1 < p <∞.
If Hµ is compact and (‖µ[n]‖)n is bounded, then properties 1–3 are equivalent. If
µ = f dmG , for some f ∈ L1(G), then properties 1–4 are equivalent.
If G is amenable, then properties 1 and 2 are both equivalent to ‖µ‖ ≤ 1. If Hµ is
not compact, (e.g., if G = R for any µ), then 3 never happens and 4 is equivalent to
‖µ‖ = r(λp(µ)) < 1.
Examples
I If µ is not positive, λp(µ) may be uniformly mean Ergodic with r(λp(µ)) = 1.
Take µ = δ1 − δ2 ∈ M(Z), then σ(λ2(µ)) ∩ T = {−1} and λ2(µ) is uniformly
mean Ergodic .
Jorge Galindo Ergodic properties of convolution operators
Summary
Consider the following properties of µ ∈ M(G), µ > 0 , µ 6= δe :
1 µ is vaguely ergodic.
2 λp(µ) is mean ergodic , 1 < p <∞.
3 λ1(µ) is mean ergodic .
4 λp(µ) is uniformly mean Ergodic , 1 < p <∞.
If Hµ is compact and (‖µ[n]‖)n is bounded, then properties 1–3 are equivalent. If
µ = f dmG , for some f ∈ L1(G), then properties 1–4 are equivalent.
If G is amenable, then properties 1 and 2 are both equivalent to ‖µ‖ ≤ 1. If Hµ is
not compact, (e.g., if G = R for any µ), then 3 never happens and 4 is equivalent to
‖µ‖ = r(λp(µ)) < 1.
Examples
I If µ is not positive, it is possible for λq to be uniformly mean Ergodic while λp is
not uniformly mean Ergodic for 1 < p < q <∞. This needs a result of Igari on
functions that operate on B(G).
Jorge Galindo Ergodic properties of convolution operators
Next slide. Measures on free groups.
Theorem
Let F (X ) be a free discrete group and let S ⊆ F (X ). Consider µ =∑
s∈S δs ∈ M+(F (X )).
1 (Akemann and Ostrand, 1976) If S is free, then ‖λ(µ)‖ = 2√|S| − 1.
2 (strong Haagerup inequality. Kemp and Speicher, 2007) If S consists of words of
length n in the semigroup generated by X : ‖λ(µ)‖ ≤ e√n + 1‖µ‖2.
Example (Mean ergodic convolution operators of large norm.)
Let G = F (x1, x2, x3), a free group. Put µ = (δx1 + δx2 + δx3 ), and µr = rµ, r > 0.
I ‖λ2(µnr )‖ ≤(√
3α)n
e√n + 1.
I ‖µnr ‖ = (3r)n.
I ‖λ2(µr )‖ = 2√
2r .
Choose 1√8< α < 1√
3. Then:
I r(λ2(µr )) ≤√
3r < 1 < 2√
2r = ‖λ2(µr )‖. Hence,
I λ2(µ) is uniformly mean Ergodic even if ‖λ2(µ)‖L (L2(G)) > 1.
I Since limn‖µn‖
n=∞, µr is not vaguely ergodic, either.
Jorge Galindo Ergodic properties of convolution operators
Next slide. Measures on free groups.
Theorem
Let F (X ) be a free discrete group and let S ⊆ F (X ). Consider µ =∑
s∈S δs ∈ M+(F (X )).
1 (Akemann and Ostrand, 1976) If S is free, then ‖λ(µ)‖ = 2√|S| − 1.
2 (strong Haagerup inequality. Kemp and Speicher, 2007) If S consists of words of
length n in the semigroup generated by X : ‖λ(µ)‖ ≤ e√n + 1‖µ‖2.
Example (Mean ergodic convolution operators of large norm.)
Let G = F (x1, x2, x3), a free group. Put µ = (δx1 + δx2 + δx3 ), and µr = rµ, r > 0.
I ‖λ2(µnr )‖ ≤(√
3α)n
e√n + 1.
I ‖µnr ‖ = (3r)n.
I ‖λ2(µr )‖ = 2√
2r .
Choose 1√8< α < 1√
3. Then:
I r(λ2(µr )) ≤√
3r < 1 < 2√
2r = ‖λ2(µr )‖. Hence,
I λ2(µ) is uniformly mean Ergodic even if ‖λ2(µ)‖L (L2(G)) > 1.
I Since limn‖µn‖
n=∞, µr is not vaguely ergodic, either.
Jorge Galindo Ergodic properties of convolution operators
Next slide. Measures on free groups.
Theorem
Let F (X ) be a free discrete group and let S ⊆ F (X ). Consider µ =∑
s∈S δs ∈ M+(F (X )).
1 (Akemann and Ostrand, 1976) If S is free, then ‖λ(µ)‖ = 2√|S| − 1.
2 (strong Haagerup inequality. Kemp and Speicher, 2007) If S consists of words of
length n in the semigroup generated by X : ‖λ(µ)‖ ≤ e√n + 1‖µ‖2.
Example (Mean ergodic convolution operators of large norm.)
Let G = F (x1, x2, x3), a free group. Put µ = (δx1 + δx2 + δx3 ), and µr = rµ, r > 0.
I ‖λ2(µnr )‖ ≤(√
3α)n
e√n + 1.
I ‖µnr ‖ = (3r)n.
I ‖λ2(µr )‖ = 2√
2r .
Choose 1√8< α < 1√
3. Then:
I r(λ2(µr )) ≤√
3r < 1 < 2√
2r = ‖λ2(µr )‖. Hence,
I λ2(µ) is uniformly mean Ergodic even if ‖λ2(µ)‖L (L2(G)) > 1.
I Since limn‖µn‖
n=∞, µr is not vaguely ergodic, either.
Jorge Galindo Ergodic properties of convolution operators
Next slide. Measures on free groups.
Theorem
Let F (X ) be a free discrete group and let S ⊆ F (X ). Consider µ =∑
s∈S δs ∈ M+(F (X )).
1 (Akemann and Ostrand, 1976) If S is free, then ‖λ(µ)‖ = 2√|S| − 1.
2 (strong Haagerup inequality. Kemp and Speicher, 2007) If S consists of words of
length n in the semigroup generated by X : ‖λ(µ)‖ ≤ e√n + 1‖µ‖2.
Example (Mean ergodic convolution operators of large norm.)
Let G = F (x1, x2, x3), a free group. Put µ = (δx1 + δx2 + δx3 ), and µr = rµ, r > 0.
I ‖λ2(µnr )‖ ≤(√
3α)n
e√n + 1.
I ‖µnr ‖ = (3r)n.
I ‖λ2(µr )‖ = 2√
2r .
Choose 1√8< α < 1√
3. Then:
I r(λ2(µr )) ≤√
3r < 1 < 2√
2r = ‖λ2(µr )‖. Hence,
I λ2(µ) is uniformly mean Ergodic even if ‖λ2(µ)‖L (L2(G)) > 1.
I Since limn‖µn‖
n=∞, µr is not vaguely ergodic, either.
Jorge Galindo Ergodic properties of convolution operators
Next slide. Measures on free groups.
Theorem
Let F (X ) be a free discrete group and let S ⊆ F (X ). Consider µ =∑
s∈S δs ∈ M+(F (X )).
1 (Akemann and Ostrand, 1976) If S is free, then ‖λ(µ)‖ = 2√|S| − 1.
2 (strong Haagerup inequality. Kemp and Speicher, 2007) If S consists of words of
length n in the semigroup generated by X : ‖λ(µ)‖ ≤ e√n + 1‖µ‖2.
Example (Mean ergodic convolution operators of large norm.)
Let G = F (x1, x2, x3), a free group. Put µ = (δx1 + δx2 + δx3 ), and µr = rµ, r > 0.
I ‖λ2(µnr )‖ ≤(√
3α)n
e√n + 1.
I ‖µnr ‖ = (3r)n.
I ‖λ2(µr )‖ = 2√
2r .
Choose 1√8< α < 1√
3. Then:
I r(λ2(µr )) ≤√
3r < 1 < 2√
2r = ‖λ2(µr )‖. Hence,
I λ2(µ) is uniformly mean Ergodic even if ‖λ2(µ)‖L (L2(G)) > 1.
I Since limn‖µn‖
n=∞, µr is not vaguely ergodic, either.
Jorge Galindo Ergodic properties of convolution operators
Next slide. Measures on free groups.
Theorem
Let F (X ) be a free discrete group and let S ⊆ F (X ). Consider µ =∑
s∈S δs ∈ M+(F (X )).
1 (Akemann and Ostrand, 1976) If S is free, then ‖λ(µ)‖ = 2√|S| − 1.
2 (strong Haagerup inequality. Kemp and Speicher, 2007) If S consists of words of
length n in the semigroup generated by X : ‖λ(µ)‖ ≤ e√n + 1‖µ‖2.
Example (Mean ergodic convolution operators of large norm.)
Let G = F (x1, x2, x3), a free group. Put µ = (δx1 + δx2 + δx3 ), and µr = rµ, r > 0.
I ‖λ2(µnr )‖ ≤(√
3α)n
e√n + 1.
I ‖µnr ‖ = (3r)n.
I ‖λ2(µr )‖ = 2√
2r .
Choose 1√8< α < 1√
3. Then:
I r(λ2(µr )) ≤√
3r < 1 < 2√
2r = ‖λ2(µr )‖. Hence,
I λ2(µ) is uniformly mean Ergodic even if ‖λ2(µ)‖L (L2(G)) > 1.
I Since limn‖µn‖
n=∞, µr is not vaguely ergodic, either.
Jorge Galindo Ergodic properties of convolution operators
Next slide. Measures on free groups.
Theorem
Let F (X ) be a free discrete group and let S ⊆ F (X ). Consider µ =∑
s∈S δs ∈ M+(F (X )).
1 (Akemann and Ostrand, 1976) If S is free, then ‖λ(µ)‖ = 2√|S| − 1.
2 (strong Haagerup inequality. Kemp and Speicher, 2007) If S consists of words of
length n in the semigroup generated by X : ‖λ(µ)‖ ≤ e√n + 1‖µ‖2.
Example (Mean ergodic convolution operators of large norm.)
Let G = F (x1, x2, x3), a free group. Put µ = (δx1 + δx2 + δx3 ), and µr = rµ, r > 0.
I ‖λ2(µnr )‖ ≤(√
3α)n
e√n + 1.
I ‖µnr ‖ = (3r)n.
I ‖λ2(µr )‖ = 2√
2r .
Choose 1√8< α < 1√
3. Then:
I r(λ2(µr )) ≤√
3r < 1 < 2√
2r = ‖λ2(µr )‖. Hence,
I λ2(µ) is uniformly mean Ergodic even if ‖λ2(µ)‖L (L2(G)) > 1.
I Since limn‖µn‖
n=∞, µr is not vaguely ergodic, either.
Jorge Galindo Ergodic properties of convolution operators
Next slide. Measures on free groups.
Theorem
Let F (X ) be a free discrete group and let S ⊆ F (X ). Consider µ =∑
s∈S δs ∈ M+(F (X )).
1 (Akemann and Ostrand, 1976) If S is free, then ‖λ(µ)‖ = 2√|S| − 1.
2 (strong Haagerup inequality. Kemp and Speicher, 2007) If S consists of words of
length n in the semigroup generated by X : ‖λ(µ)‖ ≤ e√n + 1‖µ‖2.
Example (Mean ergodic convolution operators of large norm.)
Let G = F (x1, x2, x3), a free group. Put µ = (δx1 + δx2 + δx3 ), and µr = rµ, r > 0.
I ‖λ2(µnr )‖ ≤(√
3α)n
e√n + 1.
I ‖µnr ‖ = (3r)n.
I ‖λ2(µr )‖ = 2√
2r .
Choose 1√8< α < 1√
3. Then:
I r(λ2(µr )) ≤√
3r < 1 < 2√
2r = ‖λ2(µr )‖. Hence,
I λ2(µ) is uniformly mean Ergodic even if ‖λ2(µ)‖L (L2(G)) > 1.
I Since limn‖µn‖
n=∞, µr is not vaguely ergodic, either.
Jorge Galindo Ergodic properties of convolution operators
Next slide. Measures on free groups.
Theorem
Let F (X ) be a free discrete group and let S ⊆ F (X ). Consider µ =∑
s∈S δs ∈ M+(F (X )).
1 (Akemann and Ostrand, 1976) If S is free, then ‖λ(µ)‖ = 2√|S| − 1.
2 (strong Haagerup inequality. Kemp and Speicher, 2007) If S consists of words of
length n in the semigroup generated by X : ‖λ(µ)‖ ≤ e√n + 1‖µ‖2.
Example (Mean ergodic convolution operators of large norm.)
Let G = F (x1, x2, x3), a free group. Put µ = (δx1 + δx2 + δx3 ), and µr = rµ, r > 0.
I ‖λ2(µnr )‖ ≤(√
3α)n
e√n + 1.
I ‖µnr ‖ = (3r)n.
I ‖λ2(µr )‖ = 2√
2r .
Choose 1√8< α < 1√
3. Then:
I r(λ2(µr )) ≤√
3r < 1 < 2√
2r = ‖λ2(µr )‖. Hence,
I λ2(µ) is uniformly mean Ergodic even if ‖λ2(µ)‖L (L2(G)) > 1.
I Since limn‖µn‖
n=∞, µr is not vaguely ergodic, either.
Jorge Galindo Ergodic properties of convolution operators
Next slide. Measures on free groups.
Theorem
Let F (X ) be a free discrete group and let S ⊆ F (X ). Consider µ =∑
s∈S δs ∈ M+(F (X )).
1 (Akemann and Ostrand, 1976) If S is free, then ‖λ(µ)‖ = 2√|S| − 1.
2 (strong Haagerup inequality. Kemp and Speicher, 2007) If S consists of words of
length n in the semigroup generated by X : ‖λ(µ)‖ ≤ e√n + 1‖µ‖2.
Example (Mean ergodic convolution operators of large norm.)
Let G = F (x1, x2, x3), a free group. Put µ = (δx1 + δx2 + δx3 ), and µr = rµ, r > 0.
I ‖λ2(µnr )‖ ≤(√
3α)n
e√n + 1.
I ‖µnr ‖ = (3r)n.
I ‖λ2(µr )‖ = 2√
2r .
Choose 1√8< α < 1√
3. Then:
I r(λ2(µr )) ≤√
3r < 1 < 2√
2r = ‖λ2(µr )‖. Hence,
I λ2(µ) is uniformly mean Ergodic even if ‖λ2(µ)‖L (L2(G)) > 1.
I Since limn‖µn‖
n=∞, µr is not vaguely ergodic, either.
Jorge Galindo Ergodic properties of convolution operators
Next slide. Measures on free groups.
Theorem
Let F (X ) be a free discrete group and let S ⊆ F (X ). Consider µ =∑
s∈S δs ∈ M+(F (X )).
1 (Akemann and Ostrand, 1976) If S is free, then ‖λ(µ)‖ = 2√|S| − 1.
2 (strong Haagerup inequality. Kemp and Speicher, 2007) If S consists of words of
length n in the semigroup generated by X : ‖λ(µ)‖ ≤ e√n + 1‖µ‖2.
Example (Mean ergodic convolution operators of large norm.)
Let G = F (x1, x2, x3), a free group. Put µ = (δx1 + δx2 + δx3 ), and µr = rµ, r > 0.
I ‖λ2(µnr )‖ ≤(√
3α)n
e√n + 1.
I ‖µnr ‖ = (3r)n.
I ‖λ2(µr )‖ = 2√
2r .
Choose 1√8< α < 1√
3. Then:
I r(λ2(µr )) ≤√
3r < 1 < 2√
2r = ‖λ2(µr )‖. Hence,
I λ2(µ) is uniformly mean Ergodic even if ‖λ2(µ)‖L (L2(G)) > 1.
I Since limn‖µn‖
n=∞, µr is not vaguely ergodic, either.
Jorge Galindo Ergodic properties of convolution operators
Open ends
Concerning mean ergodicity, we don’t know much when G is not amenable or µ is not
positive:
Question
Is it true that λp(µ) is mean ergodic if and only if λp(µ) is power bounded.
This is true for Abelian G and p = 2 and for amenable G with µ > 0.
If G = F (x1, x2, x3), a free group, we don’t know if α(δx1 + δx2 + δx3 ) ∈ M(G), with1√8< α < 1√
3is power bounded.
Question
Suppose that λp(µ) is mean ergodic for some 1 < p <∞, is λq(µ) mean
ergodic for all 1 < q <∞?
For weak mean ergodicity, yes. If µ ∈ P(G) and Hµ is compact, yes.
Jorge Galindo Ergodic properties of convolution operators
Open ends
Concerning mean ergodicity, we don’t know much when G is not amenable or µ is not
positive:
Question
Is it true that λp(µ) is mean ergodic if and only if λp(µ) is power bounded.
This is true for Abelian G and p = 2 and for amenable G with µ > 0.
If G = F (x1, x2, x3), a free group, we don’t know if α(δx1 + δx2 + δx3 ) ∈ M(G), with1√8< α < 1√
3is power bounded.
Question
Suppose that λp(µ) is mean ergodic for some 1 < p <∞, is λq(µ) mean
ergodic for all 1 < q <∞?
For weak mean ergodicity, yes. If µ ∈ P(G) and Hµ is compact, yes.
Jorge Galindo Ergodic properties of convolution operators
Open ends
Concerning mean ergodicity, we don’t know much when G is not amenable or µ is not
positive:
Question
Is it true that λp(µ) is mean ergodic if and only if λp(µ) is power bounded.
This is true for Abelian G and p = 2 and for amenable G with µ > 0.
If G = F (x1, x2, x3), a free group, we don’t know if α(δx1 + δx2 + δx3 ) ∈ M(G), with1√8< α < 1√
3is power bounded.
Question
Suppose that λp(µ) is mean ergodic for some 1 < p <∞, is λq(µ) mean
ergodic for all 1 < q <∞?
For weak mean ergodicity, yes. If µ ∈ P(G) and Hµ is compact, yes.
Jorge Galindo Ergodic properties of convolution operators
Open ends
Concerning mean ergodicity, we don’t know much when G is not amenable or µ is not
positive:
Question
Is it true that λp(µ) is mean ergodic if and only if λp(µ) is power bounded.
This is true for Abelian G and p = 2 and for amenable G with µ > 0.
If G = F (x1, x2, x3), a free group, we don’t know if α(δx1 + δx2 + δx3 ) ∈ M(G), with1√8< α < 1√
3is power bounded.
Question
Suppose that λp(µ) is mean ergodic for some 1 < p <∞, is λq(µ) mean
ergodic for all 1 < q <∞?
For weak mean ergodicity, yes. If µ ∈ P(G) and Hµ is compact, yes.
Jorge Galindo Ergodic properties of convolution operators
Open ends
Concerning mean ergodicity, we don’t know much when G is not amenable or µ is not
positive:
Question
Is it true that λp(µ) is mean ergodic if and only if λp(µ) is power bounded.
This is true for Abelian G and p = 2 and for amenable G with µ > 0.
If G = F (x1, x2, x3), a free group, we don’t know if α(δx1 + δx2 + δx3 ) ∈ M(G), with1√8< α < 1√
3is power bounded.
Question
Suppose that λp(µ) is mean ergodic for some 1 < p <∞, is λq(µ) mean
ergodic for all 1 < q <∞?
For weak mean ergodicity, yes. If µ ∈ P(G) and Hµ is compact, yes.
Jorge Galindo Ergodic properties of convolution operators
Open ends
Concerning mean ergodicity, we don’t know much when G is not amenable or µ is not
positive:
Question
Is it true that λp(µ) is mean ergodic if and only if λp(µ) is power bounded.
This is true for Abelian G and p = 2 and for amenable G with µ > 0.
If G = F (x1, x2, x3), a free group, we don’t know if α(δx1 + δx2 + δx3 ) ∈ M(G), with1√8< α < 1√
3is power bounded.
Question
Suppose that λp(µ) is mean ergodic for some 1 < p <∞, is λq(µ) mean
ergodic for all 1 < q <∞?
For weak mean ergodicity, yes.
If µ ∈ P(G) and Hµ is compact, yes.
Jorge Galindo Ergodic properties of convolution operators
Open ends
Concerning mean ergodicity, we don’t know much when G is not amenable or µ is not
positive:
Question
Is it true that λp(µ) is mean ergodic if and only if λp(µ) is power bounded.
This is true for Abelian G and p = 2 and for amenable G with µ > 0.
If G = F (x1, x2, x3), a free group, we don’t know if α(δx1 + δx2 + δx3 ) ∈ M(G), with1√8< α < 1√
3is power bounded.
Question
Suppose that λp(µ) is mean ergodic for some 1 < p <∞, is λq(µ) mean
ergodic for all 1 < q <∞?
For weak mean ergodicity, yes. If µ ∈ P(G) and Hµ is compact, yes.
Jorge Galindo Ergodic properties of convolution operators
Open ends
Concerning mean ergodicity, we don’t know much when G is not amenable or µ is not
positive:
Question
Is it true that λp(µ) is mean ergodic if and only if λp(µ) is power bounded.
This is true for Abelian G and p = 2 and for amenable G with µ > 0.
If G = F (x1, x2, x3), a free group, we don’t know if α(δx1 + δx2 + δx3 ) ∈ M(G), with1√8< α < 1√
3is power bounded.
Question
Suppose that λp(µ) is mean ergodic for some 1 < p <∞, is λq(µ) mean
ergodic for all 1 < q <∞?
For weak mean ergodicity, yes. If µ ∈ P(G) and Hµ is compact, yes.
Jorge Galindo Ergodic properties of convolution operators
Open ends (ctd)
Consider the following conditions:
1 ‖µ‖ < 1.
2 r(λ(µ)) < 1 =⇒ .
3 1 is not an accumulation point of σ(λp(µ)).
Clearly,
(1) =⇒ (2) =⇒ uniformly mean Ergodic =⇒ (3).
Question
Let µ ∈ P(G). Under which conditions is it true that conditions (1), (2) or (3)
characterize uniform mean ergodicity?
I (3) works when G is Abelian and p = 2 or when Hµ is amenable.
I (2) works when Hµ is not compact.
I If Hµ is amenable and noncompact, then (1) works.
Jorge Galindo Ergodic properties of convolution operators
Open ends (ctd)
Consider the following conditions:
1 ‖µ‖ < 1.
2 r(λ(µ)) < 1 =⇒ .
3 1 is not an accumulation point of σ(λp(µ)).
Clearly,
(1) =⇒ (2) =⇒ uniformly mean Ergodic =⇒ (3).
Question
Let µ ∈ P(G). Under which conditions is it true that conditions (1), (2) or (3)
characterize uniform mean ergodicity?
I (3) works when G is Abelian and p = 2 or when Hµ is amenable.
I (2) works when Hµ is not compact.
I If Hµ is amenable and noncompact, then (1) works.
Jorge Galindo Ergodic properties of convolution operators
Open ends (ctd)
Consider the following conditions:
1 ‖µ‖ < 1.
2 r(λ(µ)) < 1 =⇒ .
3 1 is not an accumulation point of σ(λp(µ)).
Clearly,
(1) =⇒ (2) =⇒ uniformly mean Ergodic =⇒ (3).
Question
Let µ ∈ P(G). Under which conditions is it true that conditions (1), (2) or (3)
characterize uniform mean ergodicity?
I (3) works when G is Abelian and p = 2 or when Hµ is amenable.
I (2) works when Hµ is not compact.
I If Hµ is amenable and noncompact, then (1) works.
Jorge Galindo Ergodic properties of convolution operators
Open ends (ctd)
Consider the following conditions:
1 ‖µ‖ < 1.
2 r(λ(µ)) < 1 =⇒ .
3 1 is not an accumulation point of σ(λp(µ)).
Clearly,
(1) =⇒ (2) =⇒ uniformly mean Ergodic =⇒ (3).
Question
Let µ ∈ P(G). Under which conditions is it true that conditions (1), (2) or (3)
characterize uniform mean ergodicity?
I (3) works when G is Abelian and p = 2 or when Hµ is amenable.
I (2) works when Hµ is not compact.
I If Hµ is amenable and noncompact, then (1) works.
Jorge Galindo Ergodic properties of convolution operators
Open ends (ctd)
Consider the following conditions:
1 ‖µ‖ < 1.
2 r(λ(µ)) < 1 =⇒ .
3 1 is not an accumulation point of σ(λp(µ)).
Clearly,
(1) =⇒ (2) =⇒ uniformly mean Ergodic =⇒ (3).
Question
Let µ ∈ P(G). Under which conditions is it true that conditions (1), (2) or (3)
characterize uniform mean ergodicity?
I (3) works when G is Abelian and p = 2 or when Hµ is amenable.
I (2) works when Hµ is not compact.
I If Hµ is amenable and noncompact, then (1) works.
Jorge Galindo Ergodic properties of convolution operators
Open ends (ctd)
Consider the following conditions:
1 ‖µ‖ < 1.
2 r(λ(µ)) < 1 =⇒ .
3 1 is not an accumulation point of σ(λp(µ)).
Clearly,
(1) =⇒ (2) =⇒ uniformly mean Ergodic =⇒ (3).
Question
Let µ ∈ P(G). Under which conditions is it true that conditions (1), (2) or (3)
characterize uniform mean ergodicity?
I (3) works when G is Abelian and p = 2 or when Hµ is amenable.
I (2) works when Hµ is not compact.
I If Hµ is amenable and noncompact, then (1) works.
Jorge Galindo Ergodic properties of convolution operators
Open ends (ctd)
Consider the following conditions:
1 ‖µ‖ < 1.
2 r(λ(µ)) < 1 =⇒ .
3 1 is not an accumulation point of σ(λp(µ)).
Clearly,
(1) =⇒ (2) =⇒ uniformly mean Ergodic =⇒ (3).
Question
Let µ ∈ P(G). Under which conditions is it true that conditions (1), (2) or (3)
characterize uniform mean ergodicity?
I (3) works when G is Abelian and p = 2 or when Hµ is amenable.
I (2) works when Hµ is not compact.
I If Hµ is amenable and noncompact, then (1) works.
Jorge Galindo Ergodic properties of convolution operators
Open ends (ctd)
Consider the following conditions:
1 ‖µ‖ < 1.
2 r(λ(µ)) < 1 =⇒ .
3 1 is not an accumulation point of σ(λp(µ)).
Clearly,
(1) =⇒ (2) =⇒ uniformly mean Ergodic =⇒ (3).
Question
Let µ ∈ P(G). Under which conditions is it true that conditions (1), (2) or (3)
characterize uniform mean ergodicity?
I (3) works when G is Abelian and p = 2 or when Hµ is amenable.
I (2) works when Hµ is not compact.
I If Hµ is amenable and noncompact, then (1) works.
Jorge Galindo Ergodic properties of convolution operators
THANK YOU FOR YOUR ATTENTION. . .
. . . AND PATTIENCE
Jorge Galindo Ergodic properties of convolution operators
THANK YOU FOR YOUR ATTENTION. . .
. . . AND PATTIENCE
Jorge Galindo Ergodic properties of convolution operators