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Additive Combinatorics methods in Fractal Geometry II Pablo - - PowerPoint PPT Presentation

Additive Combinatorics methods in Fractal Geometry II Pablo Shmerkin Department of Mathematics and Statistics T. Di Tella University and CONICET Dynamics Beyond Uniform Hyperbolicity, CIRM, May 2019 P . Shmerkin (U.T. Di Tella/CONICET)


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SLIDE 1

Additive Combinatorics methods in Fractal Geometry II

Pablo Shmerkin

Department of Mathematics and Statistics

  • T. Di Tella University and CONICET

Dynamics Beyond Uniform Hyperbolicity, CIRM, May 2019

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 1 / 25

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SLIDE 2

Review: dynamical self-similarity

Definition

G is a compact Abelian group, and h ∈ G is such that the orbit {nh : n ∈ Z} is dense. We let T(g) = g + h. λ ∈ (0, 1) is a contraction parameter. ∆(x) : G → Ad

C is a map taking values in purely atomic measures

in Rd with at most C atoms. We call (G, T, λ, ∆) a model. The measures µx = ∗∞

n=1Sλn∆(T nx)

are called dynamical self-similar measures generated by the model.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 2 / 25

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SLIDE 3

Review: dynamical self-similarity

Definition

G is a compact Abelian group, and h ∈ G is such that the orbit {nh : n ∈ Z} is dense. We let T(g) = g + h. λ ∈ (0, 1) is a contraction parameter. ∆(x) : G → Ad

C is a map taking values in purely atomic measures

in Rd with at most C atoms. We call (G, T, λ, ∆) a model. The measures µx = ∗∞

n=1Sλn∆(T nx)

are called dynamical self-similar measures generated by the model.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 2 / 25

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SLIDE 4

Review: dynamical self-similarity

Definition

G is a compact Abelian group, and h ∈ G is such that the orbit {nh : n ∈ Z} is dense. We let T(g) = g + h. λ ∈ (0, 1) is a contraction parameter. ∆(x) : G → Ad

C is a map taking values in purely atomic measures

in Rd with at most C atoms. We call (G, T, λ, ∆) a model. The measures µx = ∗∞

n=1Sλn∆(T nx)

are called dynamical self-similar measures generated by the model.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 2 / 25

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SLIDE 5

Review: dynamical self-similarity

Definition

G is a compact Abelian group, and h ∈ G is such that the orbit {nh : n ∈ Z} is dense. We let T(g) = g + h. λ ∈ (0, 1) is a contraction parameter. ∆(x) : G → Ad

C is a map taking values in purely atomic measures

in Rd with at most C atoms. We call (G, T, λ, ∆) a model. The measures µx = ∗∞

n=1Sλn∆(T nx)

are called dynamical self-similar measures generated by the model.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 2 / 25

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SLIDE 6

Review: dynamical self-similarity

Definition

G is a compact Abelian group, and h ∈ G is such that the orbit {nh : n ∈ Z} is dense. We let T(g) = g + h. λ ∈ (0, 1) is a contraction parameter. ∆(x) : G → Ad

C is a map taking values in purely atomic measures

in Rd with at most C atoms. We call (G, T, λ, ∆) a model. The measures µx = ∗∞

n=1Sλn∆(T nx)

are called dynamical self-similar measures generated by the model.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 2 / 25

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SLIDE 7

Review: dynamical self-similarity

Definition

G is a compact Abelian group, and h ∈ G is such that the orbit {nh : n ∈ Z} is dense. We let T(g) = g + h. λ ∈ (0, 1) is a contraction parameter. ∆(x) : G → Ad

C is a map taking values in purely atomic measures

in Rd with at most C atoms. We call (G, T, λ, ∆) a model. The measures µx = ∗∞

n=1Sλn∆(T nx)

are called dynamical self-similar measures generated by the model.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 2 / 25

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SLIDE 8

Further examples of dynamical self-similar measures

1

Self-homothetic measures on Rd: they correspond to G = {0}, λ the (common) contraction of maps in the IFS and ∆ =

i piδti

(where ti ∈ Rd are translations) is built from the translations and the probabilities of the IFS.

2

If µ, ν are two measures as above with contractions λ1, λ2, then µ ∗ Sexν are DSSM where G is a finite group if log λ2/ log λ1 ∈ Q, and the circle otherwise. This extends to µ1 ∗ Sex2µ2 ∗ · · · ∗ Sexmµm.

3

A homogeneous self-similar measure in dimension d is, by definition, a measure of the form µ = ∗∞

n=1SλnOn∆,

O ∈ Od, λ ∈ (0, 1), ∆ ∈ A. It can be realized as a DSSM where G = O, h = O, ∆(g) = g∆.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 3 / 25

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SLIDE 9

Further examples of dynamical self-similar measures

1

Self-homothetic measures on Rd: they correspond to G = {0}, λ the (common) contraction of maps in the IFS and ∆ =

i piδti

(where ti ∈ Rd are translations) is built from the translations and the probabilities of the IFS.

2

If µ, ν are two measures as above with contractions λ1, λ2, then µ ∗ Sexν are DSSM where G is a finite group if log λ2/ log λ1 ∈ Q, and the circle otherwise. This extends to µ1 ∗ Sex2µ2 ∗ · · · ∗ Sexmµm.

3

A homogeneous self-similar measure in dimension d is, by definition, a measure of the form µ = ∗∞

n=1SλnOn∆,

O ∈ Od, λ ∈ (0, 1), ∆ ∈ A. It can be realized as a DSSM where G = O, h = O, ∆(g) = g∆.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 3 / 25

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SLIDE 10

Further examples of dynamical self-similar measures

1

Self-homothetic measures on Rd: they correspond to G = {0}, λ the (common) contraction of maps in the IFS and ∆ =

i piδti

(where ti ∈ Rd are translations) is built from the translations and the probabilities of the IFS.

2

If µ, ν are two measures as above with contractions λ1, λ2, then µ ∗ Sexν are DSSM where G is a finite group if log λ2/ log λ1 ∈ Q, and the circle otherwise. This extends to µ1 ∗ Sex2µ2 ∗ · · · ∗ Sexmµm.

3

A homogeneous self-similar measure in dimension d is, by definition, a measure of the form µ = ∗∞

n=1SλnOn∆,

O ∈ Od, λ ∈ (0, 1), ∆ ∈ A. It can be realized as a DSSM where G = O, h = O, ∆(g) = g∆.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 3 / 25

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SLIDE 11

Discrete approximations and shifted self-similarity

µx = ∗∞

n=0Sλn∆(T nx).

We define the discrete step-n approximations µx,n = ∗n−1

j=0 Sλn∆(T nx).

Note that µx,n is purely atomic with ≤ n−1

j=0 |supp(∆(T jx))| ≤ Cn

atoms. We then have the following crucial shifted self-similarity relationship: µx = µx,n ∗ SλnµT nx. This says that µx is a convex combination of scaled down (by a factor λn) translated copies of µT nx.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 4 / 25

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Review: Frostman exponent

Definition

Let µ be a measure on Rd. The Frostman exponent dim∞(µ) is the supremum of all s such that µ(B(x, r)) ≤ Cs r s for all r ∈ (0, 1] and all x.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 5 / 25

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SLIDE 13

Review: exponential separation

Definition

We say that a model (G, T, λ, ∆) has exponential separation if for Haar-almost all x ∈ G there is R > 0 such that following holds for infinitely many n: the atoms of the discrete approximation µn,x = ∗n

j=1Sλj∆(T jx)

are (distinct and) e−Rn-separated.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 6 / 25

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SLIDE 14

Main Theorem: Frostman exponents of DSSM

Theorem (P .S.)

Let (G, T, λ, ∆) be a model with exponential separation on R. We also assume that the maps x → ∆(x) and x → µx are continuous a.e., and that µx is supported on [0, 1]. Let s = min

  • log ∆(x)∞ dx

log λ , 1

  • ,

where ∆∞ = maxy ∆{y}. Then dim∞(µx) = s for every x ∈ G. Moreover, for every ε > 0 there is a constant Cε such that, for all x ∈ G, y ∈ R and r ∈ (0, 1], µx(B(y, r)) ≤ Cεr s−ε

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 7 / 25

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SLIDE 15

Remarks on main theorem

Remarks

In the self-similar case (corresponding to constant ∆) a version of this result was obtained by M. Hochman but his version is for Hausdorff dimension rather than Frostman exponents. While exponential separation has to be checked for almost all x, the conclusion holds for all x The transitive translation on a compact Abelian group can be replaced by a uniquely ergodic transformation on a compact metric space.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 8 / 25

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SLIDE 16

Remarks on main theorem

Remarks

In the self-similar case (corresponding to constant ∆) a version of this result was obtained by M. Hochman but his version is for Hausdorff dimension rather than Frostman exponents. While exponential separation has to be checked for almost all x, the conclusion holds for all x The transitive translation on a compact Abelian group can be replaced by a uniquely ergodic transformation on a compact metric space.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 8 / 25

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SLIDE 17

Remarks on main theorem

Remarks

In the self-similar case (corresponding to constant ∆) a version of this result was obtained by M. Hochman but his version is for Hausdorff dimension rather than Frostman exponents. While exponential separation has to be checked for almost all x, the conclusion holds for all x The transitive translation on a compact Abelian group can be replaced by a uniquely ergodic transformation on a compact metric space.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 8 / 25

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SLIDE 18

Remarks on main theorem

Remarks

In the self-similar case (corresponding to constant ∆) a version of this result was obtained by M. Hochman but his version is for Hausdorff dimension rather than Frostman exponents. While exponential separation has to be checked for almost all x, the conclusion holds for all x The transitive translation on a compact Abelian group can be replaced by a uniquely ergodic transformation on a compact metric space.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 8 / 25

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Application 1: Furstenberg’s Intersection Conjecture

Theorem (P .S./Meng Wu 2016)

Suppose log p/ log q / ∈ Q. If A, B are closed and Tp, Tq-invariant, then dimH(A ∩ f(B)) ≤ dimB(A ∩ f(B)) ≤ max(dimH(A) + dimH(B) − 1, 0) for all affine bijections f : R → R.

Remark

A Tp-invariant set A can be embedded in a Tpn-Cantor set of dimension dimH(A) + ε (the allowed digits are the length-n sequences appearing in A). So it is enough to prove the theorem under the assumption that A, B are p, q-Cantor sets.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 9 / 25

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Application 1: Furstenberg’s Intersection Conjecture

Theorem (P .S./Meng Wu 2016)

Suppose log p/ log q / ∈ Q. If A, B are closed and Tp, Tq-invariant, then dimH(A ∩ f(B)) ≤ dimB(A ∩ f(B)) ≤ max(dimH(A) + dimH(B) − 1, 0) for all affine bijections f : R → R.

Remark

A Tp-invariant set A can be embedded in a Tpn-Cantor set of dimension dimH(A) + ε (the allowed digits are the length-n sequences appearing in A). So it is enough to prove the theorem under the assumption that A, B are p, q-Cantor sets.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 9 / 25

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SLIDE 21

Review: convolutions of Cantor measures as DSSM

Let A, B be p, q-Cantor sets, and let µ, ν be the natural measures on

  • them. We saw yesterday that

µ ∗ Sexν = ∗∞

n=1Sp−n∆(T nx),

where T(x) = x + log p mod log q and ∆(x) = ∆A ∗ Sex∆B if x ∈ [0, log p) ∆A if x ∈ [log p, log q) .

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 10 / 25

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A corollary of the main result

Corollary

For all u ∈ R \ {0} it holds that dim∞(µ ∗ Suν) = min(dimH(A) + dimH(B), 1) =: s.

Remarks

All the assumptions in the main theorem are clear except exponential separation, which is a simple lemma. A small calculation shows that indeed the value of s given by the main theorem is the RHS above. The main theorem gives the corollary for u ∈ [1, log q]. Using self-similarity it is easy to expand this to all non-zero u.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 11 / 25

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SLIDE 23

A corollary of the main result

Corollary

For all u ∈ R \ {0} it holds that dim∞(µ ∗ Suν) = min(dimH(A) + dimH(B), 1) =: s.

Remarks

All the assumptions in the main theorem are clear except exponential separation, which is a simple lemma. A small calculation shows that indeed the value of s given by the main theorem is the RHS above. The main theorem gives the corollary for u ∈ [1, log q]. Using self-similarity it is easy to expand this to all non-zero u.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 11 / 25

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SLIDE 24

A corollary of the main result

Corollary

For all u ∈ R \ {0} it holds that dim∞(µ ∗ Suν) = min(dimH(A) + dimH(B), 1) =: s.

Remarks

All the assumptions in the main theorem are clear except exponential separation, which is a simple lemma. A small calculation shows that indeed the value of s given by the main theorem is the RHS above. The main theorem gives the corollary for u ∈ [1, log q]. Using self-similarity it is easy to expand this to all non-zero u.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 11 / 25

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SLIDE 25

A corollary of the main result

Corollary

For all u ∈ R \ {0} it holds that dim∞(µ ∗ Suν) = min(dimH(A) + dimH(B), 1) =: s.

Remarks

All the assumptions in the main theorem are clear except exponential separation, which is a simple lemma. A small calculation shows that indeed the value of s given by the main theorem is the RHS above. The main theorem gives the corollary for u ∈ [1, log q]. Using self-similarity it is easy to expand this to all non-zero u.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 11 / 25

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SLIDE 26

A corollary of the main result

Corollary

For all u ∈ R \ {0} it holds that dim∞(µ ∗ Suν) = min(dimH(A) + dimH(B), 1) =: s.

Remarks

All the assumptions in the main theorem are clear except exponential separation, which is a simple lemma. A small calculation shows that indeed the value of s given by the main theorem is the RHS above. The main theorem gives the corollary for u ∈ [1, log q]. Using self-similarity it is easy to expand this to all non-zero u.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 11 / 25

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SLIDE 27

Some additional remarks

Up to a similarity map, A ∩ (rB + t) is the same as (A × B) ∩ {y = rx + t}. µ(B(x, r)) ≈ r dimH(A) for x ∈ A, and likewise for B, so (µ × ν)(B(x, r)) ≈ r dimH(A)+dimH(B) for (x, y) ∈ A × B. The convolution µ ∗ Suν is the push-forward of µ × ν under the projection Πu(x, y) = x + uy.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 12 / 25

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SLIDE 28

Some additional remarks

Up to a similarity map, A ∩ (rB + t) is the same as (A × B) ∩ {y = rx + t}. µ(B(x, r)) ≈ r dimH(A) for x ∈ A, and likewise for B, so (µ × ν)(B(x, r)) ≈ r dimH(A)+dimH(B) for (x, y) ∈ A × B. The convolution µ ∗ Suν is the push-forward of µ × ν under the projection Πu(x, y) = x + uy.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 12 / 25

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SLIDE 29

Some additional remarks

Up to a similarity map, A ∩ (rB + t) is the same as (A × B) ∩ {y = rx + t}. µ(B(x, r)) ≈ r dimH(A) for x ∈ A, and likewise for B, so (µ × ν)(B(x, r)) ≈ r dimH(A)+dimH(B) for (x, y) ∈ A × B. The convolution µ ∗ Suν is the push-forward of µ × ν under the projection Πu(x, y) = x + uy.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 12 / 25

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SLIDE 30

Conclusion of the proof

Let {B(xj, δ)}M

j=1 be disjoint collection of balls intersecting

(A × B) ∩ y = −x/u + t. We need to bound M from above. (µ × ν)

  • ∪M

j=1B(xj, δ)

  • MδdimH(A)+dimH(B).

But (since Πu is Lipschitz and the line y = −x/u + t is the fiber Π−1

u (tu))

Πu

  • ∪M

j=1B(xj, δ)

  • ⊂ B(tu, Cδ).

Since dim∞(Πu(µ × ν)) = min(dimH(A) + dimH(B), 1), we conclude (µ × ν)

  • ∪M

j=1B(xj, δ)

  • ≤ Πu(µ × ν)Πu
  • ∪M

j=1B(xj, δ)

  • ε δmin(dimH(A)+dimH(B),1)−ε.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 13 / 25

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SLIDE 31

Conclusion of the proof

Let {B(xj, δ)}M

j=1 be disjoint collection of balls intersecting

(A × B) ∩ y = −x/u + t. We need to bound M from above. (µ × ν)

  • ∪M

j=1B(xj, δ)

  • MδdimH(A)+dimH(B).

But (since Πu is Lipschitz and the line y = −x/u + t is the fiber Π−1

u (tu))

Πu

  • ∪M

j=1B(xj, δ)

  • ⊂ B(tu, Cδ).

Since dim∞(Πu(µ × ν)) = min(dimH(A) + dimH(B), 1), we conclude (µ × ν)

  • ∪M

j=1B(xj, δ)

  • ≤ Πu(µ × ν)Πu
  • ∪M

j=1B(xj, δ)

  • ε δmin(dimH(A)+dimH(B),1)−ε.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 13 / 25

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SLIDE 32

Conclusion of the proof

Let {B(xj, δ)}M

j=1 be disjoint collection of balls intersecting

(A × B) ∩ y = −x/u + t. We need to bound M from above. (µ × ν)

  • ∪M

j=1B(xj, δ)

  • MδdimH(A)+dimH(B).

But (since Πu is Lipschitz and the line y = −x/u + t is the fiber Π−1

u (tu))

Πu

  • ∪M

j=1B(xj, δ)

  • ⊂ B(tu, Cδ).

Since dim∞(Πu(µ × ν)) = min(dimH(A) + dimH(B), 1), we conclude (µ × ν)

  • ∪M

j=1B(xj, δ)

  • ≤ Πu(µ × ν)Πu
  • ∪M

j=1B(xj, δ)

  • ε δmin(dimH(A)+dimH(B),1)−ε.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 13 / 25

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SLIDE 33

Conclusion of the proof

Let {B(xj, δ)}M

j=1 be disjoint collection of balls intersecting

(A × B) ∩ y = −x/u + t. We need to bound M from above. (µ × ν)

  • ∪M

j=1B(xj, δ)

  • MδdimH(A)+dimH(B).

But (since Πu is Lipschitz and the line y = −x/u + t is the fiber Π−1

u (tu))

Πu

  • ∪M

j=1B(xj, δ)

  • ⊂ B(tu, Cδ).

Since dim∞(Πu(µ × ν)) = min(dimH(A) + dimH(B), 1), we conclude (µ × ν)

  • ∪M

j=1B(xj, δ)

  • ≤ Πu(µ × ν)Πu
  • ∪M

j=1B(xj, δ)

  • ε δmin(dimH(A)+dimH(B),1)−ε.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 13 / 25

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SLIDE 34

Exponential separation in the deterministic case I

Fix ∆ ∈ A, λ ∈ (0, 1). Let ν = ν∆,λ = ∗∞

n=0Sλn∆.

The atoms of νn = ∗n−1

j=0 Sλj∆

are of the form P(λ), for a polynomial of degree < 1 with coefficients in D := supp(∆). Therefore exponential separation holds if and only if there are R > 0 and infinitely many n such that |Q(λ)| > e−Rn for all polynomials Q of degree < n with coefficients in D − D. In the Bernoulli convolution setting, D − D = {−1, 0, 1}.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 14 / 25

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SLIDE 35

Exponential separation in the deterministic case II

Lemma (M. Hochman 2014)

If D = supp∆ is algebraic, then there is exponential separation if and only if λ is not a root of a polynomial with coefficients in D − D. For any fixed ∆, there is exponential separation for all λ outside of a set of zero Hausdorff dimension.

Corollary

dim∞(νλ) = 1 for all algebraic numbers in (1/2, 1) which are not roots of a {−1, 0, 1}-polynomial. dim∞(νλ) = 1 for all λ ∈ (1/2, 1) outside of a set of zero Hausdorff dimension.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 15 / 25

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SLIDE 36

Exponential separation in the deterministic case II

Lemma (M. Hochman 2014)

If D = supp∆ is algebraic, then there is exponential separation if and only if λ is not a root of a polynomial with coefficients in D − D. For any fixed ∆, there is exponential separation for all λ outside of a set of zero Hausdorff dimension.

Corollary

dim∞(νλ) = 1 for all algebraic numbers in (1/2, 1) which are not roots of a {−1, 0, 1}-polynomial. dim∞(νλ) = 1 for all λ ∈ (1/2, 1) outside of a set of zero Hausdorff dimension.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 15 / 25

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SLIDE 37

Exponential separation in the deterministic case II

Lemma (M. Hochman 2014)

If D = supp∆ is algebraic, then there is exponential separation if and only if λ is not a root of a polynomial with coefficients in D − D. For any fixed ∆, there is exponential separation for all λ outside of a set of zero Hausdorff dimension.

Corollary

dim∞(νλ) = 1 for all algebraic numbers in (1/2, 1) which are not roots of a {−1, 0, 1}-polynomial. dim∞(νλ) = 1 for all λ ∈ (1/2, 1) outside of a set of zero Hausdorff dimension.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 15 / 25

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SLIDE 38

Exponential separation in the deterministic case II

Lemma (M. Hochman 2014)

If D = supp∆ is algebraic, then there is exponential separation if and only if λ is not a root of a polynomial with coefficients in D − D. For any fixed ∆, there is exponential separation for all λ outside of a set of zero Hausdorff dimension.

Corollary

dim∞(νλ) = 1 for all algebraic numbers in (1/2, 1) which are not roots of a {−1, 0, 1}-polynomial. dim∞(νλ) = 1 for all λ ∈ (1/2, 1) outside of a set of zero Hausdorff dimension.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 15 / 25

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SLIDE 39

Exponential separation in the deterministic case II

Lemma (M. Hochman 2014)

If D = supp∆ is algebraic, then there is exponential separation if and only if λ is not a root of a polynomial with coefficients in D − D. For any fixed ∆, there is exponential separation for all λ outside of a set of zero Hausdorff dimension.

Corollary

dim∞(νλ) = 1 for all algebraic numbers in (1/2, 1) which are not roots of a {−1, 0, 1}-polynomial. dim∞(νλ) = 1 for all λ ∈ (1/2, 1) outside of a set of zero Hausdorff dimension.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 15 / 25

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SLIDE 40

Exponential separation in the deterministic case II

Lemma (M. Hochman 2014)

If D = supp∆ is algebraic, then there is exponential separation if and only if λ is not a root of a polynomial with coefficients in D − D. For any fixed ∆, there is exponential separation for all λ outside of a set of zero Hausdorff dimension.

Corollary

dim∞(νλ) = 1 for all algebraic numbers in (1/2, 1) which are not roots of a {−1, 0, 1}-polynomial. dim∞(νλ) = 1 for all λ ∈ (1/2, 1) outside of a set of zero Hausdorff dimension.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 15 / 25

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SLIDE 41

Application 2: Densities of Bernoulli convolutions

Theorem (P .S. 2016)

The BC νλ has a density in every Lq for λ ∈ (1/2, 1) outside of a set of exceptions of zero Hausdorff dimension.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 16 / 25

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SLIDE 42

Separating νλ into large and pseudorandom parts

νλ = ∗∞

n=0Sλn∆ =

  • ∗∞

k|nSλn∆

  • ∗∞

k∤nSλn∆

  • =: νλk ∗ ηλ,k.

1

Erd˝

  • s-Kahane: for all λ ∈ (0, 1) outside of a set of zero Hausdorff

dimension, | νλ(ξ)| ≤ Cλ|ξ|−δ(λ): polynomial Fourier decay.

2

The measures ηλ are also homogeneous self-similar measures: the contraction ratio is λk and the atomic measure is ∗k=1

j=0 Sλj∆.

If exponential separation holds for νλ then it also holds for ηλ,k (fewer atoms to consider, we are skipping some digits). So from the main theorem we have dim∞(ηλ,k) = min (k − 1) log 2 k log(1/λ) , 1

  • .

for all λ ∈ (1/2, 1) outside of a zero-dimensional set of exceptions, provided k is taken large enough.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 17 / 25

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SLIDE 43

Separating νλ into large and pseudorandom parts

νλ = ∗∞

n=0Sλn∆ =

  • ∗∞

k|nSλn∆

  • ∗∞

k∤nSλn∆

  • =: νλk ∗ ηλ,k.

1

Erd˝

  • s-Kahane: for all λ ∈ (0, 1) outside of a set of zero Hausdorff

dimension, | νλ(ξ)| ≤ Cλ|ξ|−δ(λ): polynomial Fourier decay.

2

The measures ηλ are also homogeneous self-similar measures: the contraction ratio is λk and the atomic measure is ∗k=1

j=0 Sλj∆.

If exponential separation holds for νλ then it also holds for ηλ,k (fewer atoms to consider, we are skipping some digits). So from the main theorem we have dim∞(ηλ,k) = min (k − 1) log 2 k log(1/λ) , 1

  • .

for all λ ∈ (1/2, 1) outside of a zero-dimensional set of exceptions, provided k is taken large enough.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 17 / 25

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SLIDE 44

Conclusion of the proof

By taking the union of the exceptional sets over all k, we get that for λ ∈ (1/2, 1) outside of a set of zero Hausdorff dimension, we can split νλ = ν′

λ ∗ ηλ,

where ν′

λ has power Fourier decay,

dim∞(ηλ) = 1.

Proposition (P .S.-B. Solomyak 2016)

If ρ has power Fourier decay and η has full Frostman exponent, then the convolution ρ ∗ η is absolutely continuous and the density is in Lq for all finite q.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 18 / 25

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SLIDE 45

Conclusion of the proof

By taking the union of the exceptional sets over all k, we get that for λ ∈ (1/2, 1) outside of a set of zero Hausdorff dimension, we can split νλ = ν′

λ ∗ ηλ,

where ν′

λ has power Fourier decay,

dim∞(ηλ) = 1.

Proposition (P .S.-B. Solomyak 2016)

If ρ has power Fourier decay and η has full Frostman exponent, then the convolution ρ ∗ η is absolutely continuous and the density is in Lq for all finite q.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 18 / 25

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SLIDE 46

Conclusion of the proof

By taking the union of the exceptional sets over all k, we get that for λ ∈ (1/2, 1) outside of a set of zero Hausdorff dimension, we can split νλ = ν′

λ ∗ ηλ,

where ν′

λ has power Fourier decay,

dim∞(ηλ) = 1.

Proposition (P .S.-B. Solomyak 2016)

If ρ has power Fourier decay and η has full Frostman exponent, then the convolution ρ ∗ η is absolutely continuous and the density is in Lq for all finite q.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 18 / 25

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SLIDE 47

Lq dimensions

Definition

Given a probability µ on Rd and q ∈ (1, ∞), we let Sn(µ, q) =

  • I∈Dn

µ(I)q, dimq(µ) = lim inf

n→∞

log Sn(µ, q) n(1 − q) ∈ [0, d]. q → dimq(µ) is non-increasing and dimq(µ) → dim∞(µ) as q → ∞. The main theorem holds not only for Frostman exponents but also for Lq dimensions. In the proof it is crucial that q < ∞.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 19 / 25

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SLIDE 48

Lq dimensions

Definition

Given a probability µ on Rd and q ∈ (1, ∞), we let Sn(µ, q) =

  • I∈Dn

µ(I)q, dimq(µ) = lim inf

n→∞

log Sn(µ, q) n(1 − q) ∈ [0, d]. q → dimq(µ) is non-increasing and dimq(µ) → dim∞(µ) as q → ∞. The main theorem holds not only for Frostman exponents but also for Lq dimensions. In the proof it is crucial that q < ∞.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 19 / 25

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SLIDE 49

Lq dimensions

Definition

Given a probability µ on Rd and q ∈ (1, ∞), we let Sn(µ, q) =

  • I∈Dn

µ(I)q, dimq(µ) = lim inf

n→∞

log Sn(µ, q) n(1 − q) ∈ [0, d]. q → dimq(µ) is non-increasing and dimq(µ) → dim∞(µ) as q → ∞. The main theorem holds not only for Frostman exponents but also for Lq dimensions. In the proof it is crucial that q < ∞.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 19 / 25

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SLIDE 50

Lq dimensions

Definition

Given a probability µ on Rd and q ∈ (1, ∞), we let Sn(µ, q) =

  • I∈Dn

µ(I)q, dimq(µ) = lim inf

n→∞

log Sn(µ, q) n(1 − q) ∈ [0, d]. q → dimq(µ) is non-increasing and dimq(µ) → dim∞(µ) as q → ∞. The main theorem holds not only for Frostman exponents but also for Lq dimensions. In the proof it is crucial that q < ∞.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 19 / 25

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SLIDE 51

Main Theorem: Lq dimensions of DSSM

Theorem (P .S.)

Let (G, T, λ, ∆) be a model with exponential separation on R. We also assume that the maps x → ∆(x) and x → µx are continuous a.e., and that µx is supported on [0, 1]. Let s(q) = min

  • log ∆(x)q

q dx

(q − 1) log λ , 1

  • ,

where ∆q

q = y ∆(y)q.

Then dimq(µx) = s(q) for every x ∈ G and q > 1.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 20 / 25

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SLIDE 52

Tools involved in the proof

1

Additive combinatorics: an inverse theorem for the Lq norm of the convolution of two finitely supported measures(Balog-Szemerédi-Gowers Theorem, Bourgain’s additive part of discretized sum-product results).

2

Ergodic theory: key role played by subadditive cocycle over a uniquely ergodic transformation (cocycle borrowed from Nazarov-Peres-S. 2012, uses the proof of the subadditive ergodic theorem given by Katznelson-Weiss).

3

Multifractal analysis (Lq spectrum, regularity at points of differentiability).

4

General scheme of proof follows Mike Hochman’s strategy in his landmark paper on the dimensions of self-similar measures, but there are substantial differences.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 21 / 25

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SLIDE 53

Tools involved in the proof

1

Additive combinatorics: an inverse theorem for the Lq norm of the convolution of two finitely supported measures(Balog-Szemerédi-Gowers Theorem, Bourgain’s additive part of discretized sum-product results).

2

Ergodic theory: key role played by subadditive cocycle over a uniquely ergodic transformation (cocycle borrowed from Nazarov-Peres-S. 2012, uses the proof of the subadditive ergodic theorem given by Katznelson-Weiss).

3

Multifractal analysis (Lq spectrum, regularity at points of differentiability).

4

General scheme of proof follows Mike Hochman’s strategy in his landmark paper on the dimensions of self-similar measures, but there are substantial differences.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 21 / 25

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SLIDE 54

Tools involved in the proof

1

Additive combinatorics: an inverse theorem for the Lq norm of the convolution of two finitely supported measures(Balog-Szemerédi-Gowers Theorem, Bourgain’s additive part of discretized sum-product results).

2

Ergodic theory: key role played by subadditive cocycle over a uniquely ergodic transformation (cocycle borrowed from Nazarov-Peres-S. 2012, uses the proof of the subadditive ergodic theorem given by Katznelson-Weiss).

3

Multifractal analysis (Lq spectrum, regularity at points of differentiability).

4

General scheme of proof follows Mike Hochman’s strategy in his landmark paper on the dimensions of self-similar measures, but there are substantial differences.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 21 / 25

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SLIDE 55

Tools involved in the proof

1

Additive combinatorics: an inverse theorem for the Lq norm of the convolution of two finitely supported measures(Balog-Szemerédi-Gowers Theorem, Bourgain’s additive part of discretized sum-product results).

2

Ergodic theory: key role played by subadditive cocycle over a uniquely ergodic transformation (cocycle borrowed from Nazarov-Peres-S. 2012, uses the proof of the subadditive ergodic theorem given by Katznelson-Weiss).

3

Multifractal analysis (Lq spectrum, regularity at points of differentiability).

4

General scheme of proof follows Mike Hochman’s strategy in his landmark paper on the dimensions of self-similar measures, but there are substantial differences.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 21 / 25

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SLIDE 56

A submultiplicative cocycle

dimq(µx) = lim

m→∞

log

  • I∈Dmµ(I)q
  • (1 − q)n

. Let ψn(x) =

  • I∈Dm(n)

µ(I)q, where 2m(n) ≈ λn (so that |I| ≈ λn). Then dimq(µx) = lim

n→∞

log ψn(x) (q − 1)(log λ)n.

Lemma

ψn+k(x) ≤ Cqψn(x)ψk(T nx).

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 22 / 25

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SLIDE 57

Use of unique ergodicity

ψn+k(x) ≤ Cqψn(x)ψk(T nx). By the subadditive ergodic theorem, there exists D(q) such that lim

n→∞

log ψn(x) (q − 1)(log λ)n = D(q) for a.e. x ∈ G.

Lemma (Furman; follows from the Katznelson-Weiss proof of the subadditive ergodic theorem)

lim inf

n→∞

log ψn(x) (q − 1)(log λ)n ≥ D(q) uniformly in x ∈ G.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 23 / 25

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SLIDE 58

Reduction from “everywhere” to “almost everywhere”

We need to show that dimq(µx) = lim

n→∞

log ψn(x) (q − 1)(log λ)n = min

  • log ∆(x)q

q dx

(q − 1) log λ , 1

  • =: s(q).

The upper bound dimq(µ, x) ≤ s(q) for all x is easy. But we saw that lim inf

n→∞

log ψn(x) (q − 1)(log λ)n ≥ D(q) for all x. So it is enough to show that D(q) = s(q). In other words, it is enough to prove that lim

m→∞

log

I∈Dm µ(I)q

(1 − q)m = s(q) for almost all x ∈ G.

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 24 / 25

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SLIDE 59

End of part II

Merci beaucoup!

P . Shmerkin (U.T. Di Tella/CONICET) Additive Combinatorics & Fractals CIRM-Luminy, 14.05.2019 25 / 25