Almost twenty years ago, Jean-Christophe Yoccoz gave several lectures (at ETH and Collège de France, for instance) on a proof of Jakobson theorem (based on the so-called Yoccoz puzzles), and he distributed hard copies of his lecture notes whenever they were requested (for example, he gave me such a copy when I became his post-doctoral student in 2007).
More recently, he gave a couple of lectures at Collège de France aiming to generalize his proof of Jakobson theorem to obtain some results improving upon the Wang-Young theory of rank one attractors.
Of course, his lectures (whose videos are available at his website) started by recalling several elements of his proof of Jakobson theorem and I decided to take the opportunity to write a series of posts about Jean-Christophe’s proof of Jakobson theorem (based on his hand-written lecture notes from 1997).
For the first installment of this series, we’ll review some aspects of the dynamics of the one-dimensional quadratic maps and, after that, we’ll state Jakobson’s theorem, describe the three main steps of Yoccoz proof of Jakobson theorem and implement the first step of the strategy.
1. Introduction
The dynamics of one-dimensional affine maps is fairly easy understand. The change of variables provided by the translation
transforms
into
. If
, the choice
shows that the affine map
is conjugated to its linear part
. If
,
is a translation.
In other words, the dynamics of polynomial maps is not very interesting when
. On the other hand, we shall see below that quadratic maps are already sufficiently complicated to produce all kinds of rich dynamical behaviors.
2. Quadratic family
The quadratic family is where
and
.
Remark 1 This family is sometimes presented in the literature as
or
. As it turns out, these presentations are equivalent to each other: indeed, the affine change of variables
converts
into
The dynamics of near infinity is easy to understand: in fact, since
for
, one has that
attracts the orbit
of any
with
.
This means that the interesting dynamics of occurs in the filled-in Julia set:
Note that is totally invariant, that is,
. Also,
is a compact set because
implies that
and
whenever
, so that
(where ).
Moreover, because it contains all periodic points of
(i.e., all solutions of the algebraic equations
,
).
Remark 2
is a full compact set, i.e.,
is connected: indeed, this happens because the maximum principle implies that a bounded open set
with boundary
must be completely contained in
(i.e.,
).
The dynamics of on
is influenced by the behaviour of the orbit
of the critical point
. More precisely, let us consider the Mandelbrot set
Indeed, we shall see in a moment that there is a substantial difference between the dynamics of on
depending on whether
or
.
Remark 3 If
, then one can check by induction that
for all
. Thus, the Mandelbrot set is the compact set
Also, the maximum principle implies that
is full (i.e.,
is connected).Furthermore, the Mandelbrot set is symmetric with respect to the real axis:
if and only if
.
Moreover,
intersects the real axis at the interval
: indeed, we already know that
; on the other hand, the critical orbit
is trapped between the fixed point
(solving the equation
) and its preimage
under
for
, so that
; finally, the fixed point
moves away from the real axis for
and this allows for the critical orbit
to escape to infinity, so that
.
Let us analyze the dynamics of on
. For this sake, let us take
a sufficiently large open disk centered at the origin
(and containing the critical value
). The preimage
is a topological open disk whose closure
is contained in
, and
is a degree two covering map.
By induction, we can define inductively . We have two possibilities:
- (a) if the critical value
belongs to
, then
is a topological disk whose closure is contained in
, and
is a degree two covering map;
- (b) if
for some
, then
is the union of two topological disks
and
whose closures
are disjoint, and
and
are univalent maps with images
; in particular, by Schwarz lemma,
,
, are (uniform) contractions with respect to the Poincaré (hyperbolic) metrics on
and
, the filled-in Julia set
is a Cantor set, and the dynamics of
on
is conjugated to a full unilateral two-shift
,
, via
,
where
.
Remark 4 Observe that, in item (b) above, we got analytical information (
is an uniform contraction) from topological information (
is an open topological disk with
) thanks to some tools from Complex Analysis (namely, Schwarz lemma). This type of argument is a recurrent theme in one-dimensional dynamics.
Note that the situation in item (b) occurs if and only if the critical orbit escapes to infinity, i.e.,
. Otherwise, the sequence of nested topological disks
are defined for all
and
.
In summary, the dynamics of on
falls into the classical realm of hyperbolic dynamical systems when
(cf. item (b)).
From now on, we shall focus on the discussion of for
. Actually, we will talk exclusively about real parameters
in what follows.
3. Statement of Jakobson’s theorem
Suppose that has an attracting periodic orbit
of period
, i.e.,
and
.
It is possible to show that the basin of attraction
must contain the critical point . Thus, given
, there exists at most one attracting periodic orbit
of
.
Remark 5 If
has an attracting periodic orbit
, then
is hyperbolic in
. Indeed, this follows from the same argument in item (b) above: the basin of attraction
is the interior of
and the boundary
(called Julia set in the literature) is disjoint from the closure of the critical orbit
; thus,
is contained in the open connected set
with
, so that the univalent map
from
to a component
of
is a local contraction with respect to the Poincaré metric
on
; since
is a compact subset of
, it follows that there exists
such that
for all
and
, i.e.,
is uniformly expanding on
.
Denote by the set of parameters
such that
has an attracting periodic point. The hyperbolicity of
on
for
permits to show that
is contained in the interior of the Mandelbrot set
.
The so-called hyperbolicity conjecture of Douady and Hubbard in 1982 asserts that coincides with the interior of
. This conjecture is one of the main open problems in this subject (despite partial important progress in its direction).
Nevertheless, for real parameters , we have a better understanding of the dynamics of
for most choices of
.
More precisely, it was conjectured by Fatou that is dense in
. This conjecture was independently established by Lyubich and Graczyk-Swiatek in 1997: they showed that hyperbolicity of
is open and dense property in real parameter space
. In particular, this gives an extremely satisfactory description of the dynamics of
for a topologically large set of parameters
.
Of course, it is natural to ask for a measure-theoretical counterpart of this result: can we describe the dynamics of for Lebesgue almost every
?
It might be tempting to conjecture that has full Lebesgue measure on
. Jakobson showed already in 1981 that this naive conjecture is false:
does not have full Lebesgue measure on
.
Theorem 1 (Jakobson) Let
be the subset of parameters
such that
- there exists
such that
for Lebesgue almost every
(where
);
preserves a probability measure
which is absolutely continuous with respect to the Lebesgue measure on
.
Then, the Lebesgue measure of
is positive and, in fact,
has density one near
:
(where
stands for the Lebesgue measure).
Nevertheless, Lyubich showed in 2002 that has full Lebesgue measure on
, so that we get a satisfactory description of the dynamics of
for Lebesgue almost every parameters
.
4. Overview of Yoccoz proof of Jakobson theorem
In 1997 and 1998, Jean-Christophe Yoccoz gave a series of lectures at Collège de France where he explained a proof of Jakobson theorem based on some combinatorial objects for the study of called Yoccoz puzzles (see, e.g., the first section of this paper here by Milnor).
Our goal in this series of posts is to describe Yoccoz’s proof of Jakobson theorem by following Yoccoz’s lecture notes (distributed by him to those who asked for them) recently submitted for publication (after this announcement here).
Very roughly speaking, Yoccoz proof of Jakobson’s theorem has three steps. First, one introduces the notion of regular parameters and one shows that
satisfies the conclusion of Jakobson theorem whenever
is a regular parameter. Unfortunately, it is not so easy to estimate the Lebesgue measure of the set
of regular parameters. For this reason, one introduces a notion of strongly regular parameters and one proves that strongly regular parameters are regular (thus justifying the terminology). Finally, one transfers the estimates on “Yoccoz puzzles” in the phase space to the parameter space (via certain analogs of Yoccoz puzzles in parameter space called “Yoccoz parapuzzles”): by studying how the real traces of Yoccoz puzzles move with the parameter
, one completes the proof of Jakobson theorem by showing that
In the remainder of this post, we will implement the first step of this strategy (i.e., the introduction of regular parameters and the derivation of the conclusion of Jakobson theorem for regular parameters via arguments from Thermodynamical Formalism).
4.1. Preliminaries
has two real fixed points
and
for
. Note that
is repulsive for all
, while
is attractive, resp. repulsive for
, resp.
. Moreover, the real filled-in Julia set
equals
for all
.
The dynamical features of are determined by the (recurrence) properties of the critical orbit
. For this reason, we consider
and we will analyze the returns of the critical orbit to the central interval
and its neighborhood where
,
. (Observe that these definitions make sense because the fixed points
and
satisfy
for
.)
Definition 2 A point
is
-regular if there exists
and an open interval
such that
and
is a diffeomorphism.
Definition 3 A parameter
is regular if most points in
are regular, i.e., there are constants
and
such that
for all
. The set of regular parameters is denoted by
.
As we already said, our current goal is to show the following result:
Theorem 4 If
is a regular parameter, then there exists
such that
for Lebesgue a.e.
, and
admits an invariant probability measure which is absolutely continuous with respect to the Lebesgue measure.
4.2. The “tent map” parameter
Before proving Theorem 4, let us warm-up by showing that the parameter is regular and, moreover,
satisfies the conclusions of this theorem.
The polynomial is conjugated to the tent map
This conjugation can be seen by interpreting as a Chebyshev polynomial:
The hyperbolic features displayed by (described below) are related to the fact that the critical point
is pre-periodic:
and
for all
, so that the critical orbit does not enter the central interval
(and, thus, it is not recurrent).
The relationship between and the tent map allows us to organize the returns of the orbits of
to
as follows. Let
and define recursively
and
as
Note that the interpretation of as a Chebyshev polynomial says that
In particular, is a decreasing sequence converging to
and
is an increasing sequence converging to
.
In terms of these sequences, the return map of
to
is not difficult to describe:
- recall that the critical point
does not return to
(because
for all
);
- the points
at
return after one iteration:
;
- for
, the return map
on the intervals
and
is precisely
; moreover,
is an orientation-preserving, resp. orientation-reversing, diffeomorphism from
, resp.
, onto
, and
,
;
- for
,
extends into diffeomorphisms from neighborhoods of
to
.
The graph of the return map of
to
looks like two copies of the Gauss map
(where
denotes the fractional part): it is an instructive exercise to draw the graph of
.
At this point, we are ready to establish the regularity of .
Proposition 5 The parameter
is regular.
Proof: From the previous description of the return map , we see that, for
, the set of
-regular points is precisely
Therefore,
so that is a regular parameter because, for
and some constant
, one has
for all .
Next, we show that satisfies the conclusion of Jakobson theorem.
Proposition 6
preserves the probability measure
on
and
for Lebesgue a.e.
.
Proof: The reader can easily check (either by direct computation or by inspection of the conjugation equation between and the tent map) that
for all and
with
). It follows that
preserves the probability measure
on
.
So, our task is reduced to compute the Lyapunov exponent of . Since Lebesgue a.e.
eventually enters the central interval
and the normalized restriction
is absolutely continuous with respect to the Lebesgue measure, it suffices to prove that
for -a.e.
.
Denote by the first return time of
, so that
(by definition).
Note that is an ergodic
-invariant probability measure such that
Therefore, is a
-integrable function, so that Birkhoff’s theorem says that
This asymptotic information on the return times permits to compute the Lyapunov exponent of as follows.
Since the -orbit of a point
is confined to
and
, we see from the chain rule that
for all . By combining this estimate with (2), we obtain
for -a.e.
.
In other words, it suffices to compute the Lyapunov exponent along the subsequence of return times. As it turns out, this task is not difficult. Indeed, from (1), we have
Since for
, we conclude that
as . This completes the proof of the proposition.
4.3. Dynamics of when
is regular
We shall use the same ideas from the previous subsection to show that satisfies the conclusion of Theorem 4 when
is regular. More precisely, we will use the returns to
of certain “maximal” intervals of regular points to describe the return map
of
as an uniformly expanding countable Markov map. As it turns out, one can easily construct a
-invariant absolutely continuous probability
(via the classical approach of thermodynamical formalism [i.e., analysis of Ruelle transfer operator]), and our regularity assumption on
permits to convert
into a
-invariant absolutely continuous probability measure (by a standard summation procedure).
Definition 7 An interval
is regular of order
if there exists a neighborhood
of
such that
is a diffeomorphism from
to
with
. We denote by
the inverse branch of the restriction of
to
.
Remark 6 By definition, all points in a regular interval
of order
are
-regular.
As we are going to see in a moment, the definition of regular interval of order
was setup in a such a way that the “margin” provided by
ensures good distortion and expansion properties of
.
Remark 7 In a certain sense, the previous paragraph is the real analog of Koebe distortion theorem and Schwarz lemma ensuring good properties for univalent maps in terms of the modulus of certain annuli.
4.3.1. Distortion estimates
The Schwarzian derivative measures how far is a
diffeomorphism
from a Möbius transformation, and, for this reason, it is extremely efficient for studying distortion effects on derivative.
In fact, the composition rule reveals that the iterates
have negative Schwarzian derivative on any regular interval
of order
(because
has negative Schwarzian derivative).
In particular, if is the inverse branch of the restriction of
to the neighborhood
a regular interval of order
, then
has positive Schwarzian derivative on
.
Since a diffeomorphism
with positive Schwarzian derivative satisfies the estimate
(see, e.g., Exercise 6.4 at page 166 of this book of de Faria-de Melo), we conclude:
Lemma 8 (Bounded distortion estimate) For any regular interval
, the inverse branch
satisfies
for all
. In particular,
and, for all measurable subset
,
where
.
4.3.2. Expansion estimates
Let be the countable family of regular intervals
of positive order
which are maximal for these properties.
Given , the composition
is the inverse branch associated to a regular interval
. Conversely, all regular intervals contained in
are obtained in this way.
The bounded distortion estimates above allow to deduce uniform expansion estimates for the first return map of
on regular intervals.
Lemma 9 (Expansion estimates) Let
be a regular interval of positive order contained in
and denote
. Then,
and
where
Proof: The first inequality follows from Lemma 8 by setting and
. The second estimate follows from the first inequality after taking into account the definition of
. Finally, the third estimate follows from the second inequality, the distortion estimate in Lemma 8 and the fact that
(so that
, and, hence,
for some
).
4.3.3. Thermodynamical formalism for regular parameters
Let be a regular parameter. By definition,
for some constants and all
. In particular, if
then . Thus, most of the dynamics of the return map
is described by
,
where is the order of
.
Note that is a countable uniformly expanding Markov map (thanks to Lemmas 8 and 9). Using this fact, we will construct a
-invariant absolutely continuous probability measure.
For this sake, we consider the dual of the pullback operator
acting on finite absolutely continuous measures
on
. More concretely, the (Ruelle operator)
acts on densities by the formula
derived from the change of variables formula and the definition .
We will take advantage of tools from Complex Analysis in order to study .
More precisely, we want to use the standard procedure (from the usual proof of Bogolyubov-Krylov theorem) of building invariant measures as the limit of Cesaro means
where is the constant function on
taking the value one. Thus, our task is to show the convergence of the sequence
(and this amounts to establish adequate estimates on
).
In this direction, let us show that admits an holomorphic extension. Let
be the simply connected domain
. Since the critical values of
are all real (for all
and
), the inverse branches
associated to regular intervals
extend to univalent maps
satisfying
Given a regular interval, let be the sign of
on
and define
The family is normal on
because
are univalent functions on
such that
and
is uniformly bounded (by the distortion estimate in Lemma 8).
Since for all
, the series
defines a holomorphic extension to of the functions
Moreover, the distortion estimates in Lemma 8 say that
Therefore, the family ,
, is normal (because
belongs to the closed convex hull of the normal family
) and we can extract a subsequence of
converging uniformly on compact subsets of
to a holomorphic function
on
such that
Lemma 10
is an ergodic
-invariant measure equivalent to Lebesgue measure with total mass
.
Proof: By (4), is a measure equivalent to the Lebesgue measure. Since
preserves the total mass,
and is uniformly bounded (thanks to (3)), we obtain that
is a
-invariant measure with total mass
.
Finally, the ergodicity of is proved by the following standard argument (exploiting the good distortion and expansion properties of
). Suppose that
is a
-invariant subset of positive
, or equivalently Lebesgue, measure. Fix
a Lebesgue density point and, for each
, denote by
the regular interval containing
. By Lemma 9, we know that
(exponentially fast) as
. Hence, given
, there exists
such that
for all . By plugging this information into the distortion estimate in Lemma 8 for
,
, and by using the
-invariance of
, we get
Since is arbitrary, we conclude that
as desired.
4.3.4. Lyapunov exponent of for
For any , the return time function
and the logarithm
of the derivative of the return function are
-integrable with respect to
for all
. Indeed, the regularity of the parameter
means that
and hence the -integrability of
follows from the fact that
is equivalent to the Lebesgue measure (cf. Lemma 10). Also, the expansion estimate in Lemma 9 says that
is bounded from below (by
), while the fact that
for all
says that
, so that the
-integrability of
follows from the corresponding fact for
.
By Birkhoff theorem, we have (i.e., Lebesgue) almost everywhere convergence of the Birkhoff sums
where .
Note that (because
for all
),
(by Lemma 9) and
Let us compute the Lyapunov exponent of using (6) and the same argument from Section 4.
Proposition 11 Let
be a regular parameter. Then, for Lebesgue almost every
, one has
Proof: Recall that, for every and
, we have
Since (5) implies that as
, the desired proposition is a consequence of the estimate above and (6).
4.3.5. Absolutely continuous invariant measures for ,
Let us use the invariant measure of the acceleration
of
to build an invariant measure
of
on
.
The basic idea is very simple: we want to use the iterates of between the initial time and the return time to produce
from
. More concretely, given a continuous function
on
, let
Remark 8
is well-defined because
and
for all
.
Note that has total mass
(by Lemma 10). Moreover,
is supported on
that is
for . Furthermore,
is
-invariant is a consequence of the
-invariance of
because
differs from
by a coboundary:
Also, is
-ergodic: any
-invariant function
restricts to a
-invariant function on
; hence, the ergodicity of
implies that
is almost everywhere constant, and so
is almost everywhere constant on
.
Finally, the formula (7) defining shows that it is absolutely continuous with respect to the Lebesgue measure and its density
is given by
This completes the verification of the conclusion of Jakobson theorem for regular parameters .
Closing this post, let us observe that the density of is not square-integrable.
Remark 9 By inspecting the terms
,
and
in the definition of
, we see that the distortion estimates (4) imply that
for almost every
,
for almost every
and
for almost every
. Therefore,
is bounded away from zero but
is not
in
.
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