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Measure Preserving Transformations and Poincare Recurrence — Examples
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Areas of Elementary Plane Figures
- Binary Operations, Monoids, Groups and Subgroups
- Compactness
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Complex Lp Spaces and Test-Function Conventions
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Countability Axioms and Cardinal Functions
- Density Separability and Convolution in Lᵖ
- Determinants of Matrices over a Commutative Ring
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Fubini and Change of Variables
- Fundamental Trigonometric Identities
- Gaussian Elimination, Elementary Matrices and Reduced Row Echelon Form
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Lebesgue Measure on Euclidean Space
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Measurable Functions and Simple Approximation
- Measure Preserving Transformations and Poincare Recurrence
- Measure-Preserving Systems and Mixing Criteria
- Measures and Their Basic Properties
- Metric Spaces
- Mixed Partials, Taylor Formulae, and Extrema
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Order, Zorn's Lemma, and the Axiom of Choice
- Outer Measure and the Caratheodory Extension Theorem
- Polynomial Rings, the Division Algorithm and Roots
- Power Series and Real-Analytic Functions
- Product Measures and the Fubini Tonelli Theorems
- Properties of the Integral and the Working FTC
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Separation Axioms: the Hierarchy
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sigma Algebras and Borel Sets
- Simple Field Extensions and the Construction of the Complex Numbers
- Sine, Cosine, and the Definition of Pi
- Subspaces, Products, and Quotients
- Suprema and Infima
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- The Complex Exponential and Euler's Formula
- The Derivative and the Mean Value Theorems
- The Exponential Function
- The Lebesgue and Riemann Integrals Compared
- The Lebesgue Integral and the Convergence Theorems
- The Logarithm and General Powers
- The Lᵖ Spaces Holder Minkowski and Riesz Fischer
- The Maximal Function and Lebesgue Differentiation
- The Riemann Integral in Rᵐ and Jordan Content
- The Riemann Integral: Definition and Integrability
- The Topology of Euclidean Space
- The Total Derivative in ℝᵐ → ℝⁿ
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
These computations make the abstract recurrence and invariance statements concrete. Rational rotations have explicit intermediate-measure invariant sets. Doubling and base-three maps have finitely many inverse branches, whose interval lengths can be added directly. Fair-coin cylinder masses count prescribed coordinates.
The return examples distinguish return time from conditional mean return time: a dyadic interval has an explicit set of immediate returns, while Kac's formula gives mean two for a half-circle under an irrational rotation. Singleton and atomic examples show why invariance modulo null sets and the choice of invariant probability matter. In particular, the point mass at the fixed point is ergodic; a mixture with a two-cycle is not.
An exponential observable proves that irrational rotations are not weakly mixing. The identity transformation shows where ergodicity enters the Kac formula with value one. Finally, the Gauss-map example normalizes its density and calculates inverse images of initial intervals by a telescoping logarithmic sum. It establishes measure preservation, with branch endpoints checked separately.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
An explicit invariant set for a rational rotation
Example
Assume countable choice. If with integers , in lowest terms, then is strictly invariant under and has Lebesgue measure . Thus this rational rotation is not ergodic.
Facts & Assumptions
Circle rotations preserve Lebesgue probability and have measurable inverses. Circle rotations preserve Lebesgue measure.
In a probability system ergodicity requires strict invariant sets to have measure zero or one. Ergodicity relative to an invariant measure.
Verification
Given: Assume countable choice. If with integers , in lowest terms, then is strictly invariant under and has Lebesgue measure . Thus this rational rotation is not ergodic.
Write . For with , one has . The residue map is a permutation, with inverse subtraction of . Thus rotation maps the collection of onto itself and, being bijective, satisfies . The half-open convention makes the formula exact at every included left endpoint and excludes every right endpoint.
The intervals are pairwise disjoint and each has length . Hence . It is Borel, and its complement also has measure . By [F1] the ambient system preserves the probability, so [F2] proves nonergodicity. For , this is simply the identity rotation and . Countable choice is used only for the Lebesgue probability supplied by [F1].
Dyadic preimages under doubling
Example
Assume countable choice. For doubling on the circle, , of measure . In contrast, has measure one.
Facts & Assumptions
Doubling preserves Lebesgue probability by inverse images. Doubling preserves Lebesgue measure.
Verification
Given: Assume countable choice. For doubling on the circle, , of measure . In contrast, has measure one.
On , , and is equivalent to . On , , and is equivalent to . These two branches exhaust the circle and their solution intervals are disjoint. Each interval has length , so their union has measure , agreeing with the preservation in [F1].
For , the image ranges through every , with inverse . Thus the forward image has measure one although the source has measure . In particular inverse-image preservation does not assert equality of forward-image measures. The included points 0 and 1/2 map to 0, and the excluded right endpoints 1/4 and 3/4 map to 1/2. Countable choice is inherited from the Lebesgue probability in [F1].
Base-three cylinders and their preimages
Example
Assume countable choice. For , one has , of measure . With , for : applying deletes the first ternary digit.
Facts & Assumptions
On the base-three branch the map is , and the intervals use half-open endpoints. Integer-base maps and b-adic circle intervals.
Integer-base maps preserve Lebesgue probability under countable choice. Integer-base circle maps preserve Lebesgue measure.
Verification
Given: Assume countable choice. For , one has , of measure . With , for : applying deletes the first ternary digit.
For with , [F1] gives . The condition is equivalent to . Substitution of the three values of gives exactly the three stated disjoint intervals. Their lengths add to , as required by [F2].
The interval lies in branch . Its affine image under is . Surjectivity onto that interval is explicit: for use , which lies in . The included left and excluded right endpoints are preserved by this increasing affine map, including where the right endpoint is the excluded point 1. No ambiguous choice of ternary expansion is required. Countable choice enters only in the Lebesgue measure statement of [F2].
Fair-coin cylinder masses and separated blocks
Example
Assume countable choice. Index binary sequences by , and let prescribe the first coordinates. For fair-coin probability , , , , and .
Facts & Assumptions
A cylinder prescribing distinct coordinates has fair-coin mass . Fair-coin measure on binary sequences.
The left shift moves coordinate into position . The fair-coin one-sided shift preserves measure and is mixing.
Verification
Given: Assume countable choice. Index binary sequences by , and let prescribe the first coordinates. For fair-coin probability , , , , and .
The prefix prescribes the single value , so [F1] gives . The prefix prescribes , so its mass is . The prefix prescribes , giving . Repeated symbols do not reduce the number of distinct prescribed coordinates.
By [F2], membership in prescribes . Intersecting with therefore prescribes exactly coordinates , with respective values . Coordinate 2 and all later coordinates remain free. The cylinder mass is by [F1]. Equivalently this intersection is the disjoint union , whose masses sum to . Countable choice is inherited from the measure construction in [F1], not from the finite coordinate count.
Recurrence to a dyadic interval under doubling
Example
Assume countable choice. For Lebesgue doubling and , almost every has for infinitely many positive integers . The points of returning at time one form , of measure .
Facts & Assumptions
Finite measure preservation implies infinitely many positive returns for almost every point of a measurable set. Poincare recurrence for finite measure-preserving systems.
Doubling preserves Lebesgue probability on the circle and its completion. Doubling preserves Lebesgue measure.
Verification
Given: Assume countable choice. For Lebesgue doubling and , almost every has for infinitely many positive integers . The points of returning at time one form , of measure .
The set is Borel, with , and [F2] gives a measure-preserving system of total mass one. Applying [F1] with exactly this proves the stated almost-everywhere infinitely-many-positive-returns conclusion. Countable choice enters through [F2]; the recurrence theorem itself needs no choice axiom.
The two inverse branches give . Intersecting with leaves , whose measure is . This is the first-return-one set because there is no smaller positive time. Return times need not all be one: has successive images , so its first positive return time is four. Zero is fixed and returns at every positive time. These calculations are compatible with recurrence; recurrence alone supplies no return-frequency value or every-point assertion.
Kac mean return to a half-circle under irrational rotation
Example
Assume countable choice. Let be irrational, let act on the Lebesgue circle, and put . Its first positive return time satisfies . On the recurrent core with normalized restricted probability , the mean return time is .
Facts & Assumptions
For a positive-measure set in an ergodic probability system, Kac gives unnormalized mean one and normalized mean reciprocal to the set measure. Kac return-time formula without invertibility.
Irrational rotations are ergodic for Lebesgue probability. Circle rotation is ergodic for Lebesgue measure exactly at irrational angles.
Finite sets, including endpoints, are Lebesgue null. Every at most countable subset of is Lebesgue null; in particular .
Verification
Given: Assume countable choice. Let be irrational, let act on the Lebesgue circle, and put . Its first positive return time satisfies . On the recurrent core with normalized restricted probability , the mean return time is .
The set is Borel and is the disjoint union of and . The first has length and the second is null by [F3], so . By [F2] irrationality gives ergodicity of the Lebesgue probability system. All hypotheses of [F1] hold; applying its first conclusion yields . This uses the return time to the closed set as stated, so no unproved comparison between return times for different endpoint conventions is involved.
The recurrent core has restricted mass in [F1], and normalization divides restricted measure by . The second conclusion of [F1] therefore gives . This is an average, not an assertion that all return times equal two. The unnormalized mean is one, and multiplying it by the normalization factor two gives the same answer. Countable choice is propagated from the Lebesgue ergodicity and endpoint-null suppliers [F2] and [F3].
Mod-null invariance need not be strict invariance
Statement refuted
The assertion that every invariant-modulo-null-sets measurable set is strictly invariant is false. Assuming countable choice, for Lebesgue doubling the set satisfies , but .
Facts & Assumptions
Doubling preserves Lebesgue probability. Doubling preserves Lebesgue measure.
Strict invariance is set equality, whereas mod-null invariance is null symmetric difference. Strict and mod-null invariant sigma-algebras.
Singletons are measurable and null under countable choice. Every at most countable subset of is Lebesgue null; in particular .
Counterexample
Given: The assertion that every invariant-modulo-null-sets measurable set is strictly invariant is false. Assuming countable choice, for Lebesgue doubling the set satisfies , but .
For , the equation means is an integer. The only possibilities are or , giving . Its symmetric difference with is exactly , a null measurable set by [F3]. Thus is invariant modulo null sets in the probability system of [F1], by [F2].
The point belongs to and not to , so the sets are not equal and is not strictly invariant by [F2]. Both sets are finite Borel sets; this is an exact failure for the given representative, despite their equality modulo null sets. Countable choice is used only through the Lebesgue measure and null-set suppliers [F1] and [F3].
Doubling ergodicity depends on the invariant measure
Statement refuted
The assertion that doubling has the same ergodicity behavior for every invariant probability is false. Assuming countable choice, it is ergodic for Lebesgue probability and for , but not for .
Facts & Assumptions
Doubling is ergodic for Lebesgue probability under countable choice. Doubling is ergodic for Lebesgue measure.
Ergodicity for a probability means every strict invariant measurable set has measure zero or one. Ergodicity relative to an invariant measure.
Dirac measures are probability measures. A Dirac set function is a probability measure.
Counterexample
Given: The assertion that doubling has the same ergodicity behavior for every invariant probability is false. Assuming countable choice, it is ergodic for Lebesgue probability and for , but not for .
The circle map fixes zero and exchanges with . Thus for every Borel . Every Borel set has -measure either zero or one, so in particular every strictly invariant Borel set does; [F2] proves ergodicity for . Ergodicity for is [F1].
The finite weighted sum is a Borel probability by [F3] and the finite-sum interchange with nonnegative series. Its inverse-image mass is , so it too is invariant. Let . Continuity of the iterates makes this Borel. Since zero is fixed, eventually reaches zero exactly when does; hence . Zero belongs to and neither point of the two-cycle does, so . This contradicts the ergodicity criterion in [F2]. The atomic calculations are choice-free; countable choice is used only to include the Lebesgue system of [F1].
Irrational rotation is ergodic but not weakly mixing
Statement refuted
Assume countable choice. An irrational rotation of the Lebesgue circle is ergodic but not weakly mixing. The single function has mean zero, and its centered absolute self-correlation equals one at every nonnegative iterate.
Facts & Assumptions
Irrational rotations are ergodic for Lebesgue probability. Circle rotation is ergodic for Lebesgue measure exactly at irrational angles.
Weak mixing requires absolute Cesaro convergence to zero of every centered complex correlation. Mixing correlations extend to L2 functions.
The complex exponential obeys the addition law. , and the complex exponential extends the real exponential.
Purely imaginary exponentials have modulus one and . , , and .
Sine and cosine are differentiable, hence continuous on the real line. The derivatives of sine and cosine are cosine and minus sine.
Rotation by preserves the same Lebesgue probability. Circle rotations preserve Lebesgue measure.
Integrable complex functions have unchanged integrals under measure-preserving composition. Integral invariance under measure-preserving maps.
Counterexample
Given: Assume countable choice. An irrational rotation of the Lebesgue circle is ergodic but not weakly mixing. The single function has mean zero, and its centered absolute self-correlation equals one at every nonnegative iterate.
By [F3] and [F4], , and the same holds for every integer multiple of by multiplication and inversion. Thus is well defined across the circle cut. By the Cartesian formula [F4], it equals and is continuous by [F5] (the limit from below at 1 equals its value at 0), has by [F4], and belongs to both and because the circle has mass one. The addition law gives . By [F6] and [F7], if then , so .
For every , the addition law and integer-period identity give . Hence . The centered correlation of [F2] is the same because the mean is zero. Its modulus is one by [F4], so for every , . It cannot tend to zero; the necessary implication in [F2] disproves weak mixing. Irrationality supplies ergodicity by [F1]. Countable choice is inherited from [F1] and [F6]; only the implication from weak mixing to vanishing absolute correlation averages in [F2] is needed. No Fourier-series completeness or spectral theorem is used.
Kac normalization needs ergodicity
Statement refuted
Assume countable choice. Removing ergodicity from Kac’s probability normalization is invalid. For the identity on and , every point of has , but , not one. The normalized return mean is one, not .
Facts & Assumptions
The return time is the least positive return time, with infinity when there is none. First-return times and induced transformations.
For an ergodic probability-preserving system and a positive-measure set , Kac's theorem gives and normalized mean . Kac return-time formula without invertibility.
Under countable choice, closed intervals have their lengths as Lebesgue measure. A box in with parameters is Lebesgue measurable of measure , whichever of its faces are included.
A strict invariant set of intermediate probability disproves ergodicity. Ergodicity relative to an invariant measure.
Counterexample
Given: Assume countable choice. Removing ergodicity from Kac’s probability normalization is invalid. For the identity on and , every point of has , but , not one. The normalized return mean is one, not .
By [F3] the restricted Lebesgue measure has and . The identity is measurable and satisfies for every Borel , so it preserves this probability. In particular is strictly invariant of measure , and [F4] shows that the system is not ergodic. Countable choice is inherited from the Lebesgue measure in [F3].
For each and each positive integer , . Thus the least positive return time in [F1] is 1 and the infinitely-returning core is all of . The integral of the constant one over is . The normalized restricted probability has total mass one, so the same constant return time has mean one there. Both values differ from the respective ergodic conclusions of [F2], namely one before normalization and afterwards. All endpoints return as well, so no exceptional-point convention is involved.
The Gauss map preserves Gauss measure
Example
Assume countable choice. On put and for . The Borel probability with density relative to Lebesgue measure is -invariant. The same map preserves its completion. This example proves measure preservation only.
Facts & Assumptions
A nonnegative measurable density defines a measure by integration over sets. The indefinite integral of a nonnegative measurable function is a measure.
The logarithm has derivative on the positive reals. The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t.
The logarithm is continuous, strictly increasing, vanishes at one, and obeys the quotient law. Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm.
Continuous functions on closed bounded intervals are bounded and Riemann integrable. A continuous function on is Riemann integrable, by Heine-Cantor and Riemann's criterion.
The Riemann integral of an integrable derivative is the primitive difference, including one-sided endpoint derivatives. The second fundamental theorem: if is differentiable on with and is integrable, then .
Under countable choice, bounded Riemann integrable functions have the same Lebesgue integral. A bounded Riemann integrable function on a closed bounded interval is Lebesgue measurable and has the same integral.
At most countable sets are Lebesgue measurable and null under countable choice. Every at most countable subset of is Lebesgue null; in particular .
It suffices to check a measurable self-map on a generating pi-system for a finite measure. Measure preservation can be checked on a generating pi-system.
A measure-preserving transformation extends to the completed measure space. Compositions, iterates and completions preserve invariance.
Rational points are dense in the real line. Both and are dense in , and every nonempty open subset of is uncountable.
The rationals are countable. is countably infinite.
Verification
Given: Assume countable choice. On put and for . The Borel probability with density relative to Lebesgue measure is -invariant. The same map preserves its completion. This example proves measure preservation only.
By [F3], , so is positive, bounded by , and continuous on . By [F4] it is Riemann integrable on every closed subinterval. The derivative of is by [F2], using the translated difference quotient, also one-sided at subinterval endpoints. Thus [F5] and [F6] yield for . Singletons and countable sets have zero density integral because they are null by [F7] and is bounded. Consequently endpoints do not change this interval value. By [F1] the density defines a Borel measure, and the value with is one; removing the endpoint 1 does not change it.
The Borel sets , , partition . On , , and on the singleton it is zero. Each branch is the restriction of a continuous real function and takes values in , so for every open subset of its inverse image is a countable union of Borel branch inverse images and possibly . This proves Borel measurability. For , the exact inverse image is . The displayed intervals are pairwise disjoint because . The only endpoint outside is 1 when .
Using the interval integral of step 1.1 and countable additivity, is times the sum over of . The quotient law [F3] and the identity rewrite the partial sum through as . All original summands are nonnegative. Continuity of at 1 gives the limit , so . For , the preimage is , an explicitly enumerated countable null set, and both masses are zero. The full space also has equal inverse-image mass one.
The family consisting of , the empty set, and all with is a pi-system. It generates the Borel sets of : complements give , and increasing unions of initial closed intervals give ; intersections give ordinary open intervals, which form a countable rational-endpoint base for the interval topology. Conversely all generators are Borel. The measure is finite and is measurable, so [F8] applies to step 2.1 and proves preservation for every Borel set. By [F9] the map is measurable and preserving on the completion as well. Countable choice is inherited in the Lebesgue/Riemann comparison, null-set and completion suppliers; the branch sums and partial-sum telescoping make no choices. The rational-base assertion uses [F10]. The rational-base assertion uses [F11].
The corresponding inverse-branch density calculation can also be seen directly. On , the inverse branch is , with . Hence . The algebraic identity gives the partial sum , tending to . This verifies the density balance numerically; the interval proof in steps 1.1–3.1 already establishes measure preservation without assuming a change-of-variables theorem. The separate endpoint computations in step 2.1 account for .
Sources
- E–W Proposition 2.16
- E–W Example 2.4
- E–W Example 2.4 pp.14–15, base-three specialization; MT-22 binding example amendment
- E–W Examples 2.8–2.9
- E–W Theorem 2.11 and Example 2.4
- Sarig Theorem 1.7, specialization
- E–W Proposition 2.14, doubling specialization
- E–W Definition 2.13 and periodic orbit specialization
- E–W Example 2.40; Exercise 2.7.7
- Sarig Theorem 1.7 hypotheses
- E–W Lemma 3.5, Gauss measure