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Measure Preserving Transformations and Poincare Recurrence
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Approximation and Compactness in C(K)
- 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
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Fubini and Change of Variables
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- 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
- Measurable Functions and Simple Approximation
- 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
- 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
- Subspaces, Products, and Quotients
- Suprema and Infima
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- The Derivative and the Mean Value Theorems
- The Exponential Function
- 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
Finite measure forces almost every visit to a measurable set to be followed by infinitely many returns. The proof starts with disjoint inverse-image towers, so it applies even when the transformation is not invertible. On a second-countable space this gives neighborhood recurrence outside one explicitly defined null set.
The first-return map lives on the measurable core of points returning infinitely often. Its restricted measure is invariant; under ergodicity, Kac's formula gives integral return time one on a probability space, or conditional mean return time . The excursion formula extends this calculation to integrable observables.
Circle rotations distinguish ergodicity from mixing. Irrational rotations are ergodic but fail even weak mixing, while integer-base maps are strongly mixing. A direct cylinder construction gives the fair-coin shift without using Tychonoff's theorem. Compact metric dynamics culminate in Krylov–Bogolyubov: explicit orbit averages have a subsequential invariant probability limit. The local positive-functional representation lemma supplies the measure needed by that argument.
Each result states its choice assumptions. The tower and orbit arguments make explicit finite or least-index constructions; the Lebesgue, completion, fair-coin measure and compact-probability results identify their uses of countable choice. The counterexamples keep strict invariance, invariance modulo null sets, topological density and measure ergodicity separate.
3 · Logical flowchart
4 · Definitions, theorems and proofs
No-return sets have disjoint null preimage towers
Statement
Let be a measure-preserving system with . For put . Then the measurable sets , , are pairwise disjoint and all have measure zero.
Facts & Assumptions
Nonnegative iterates preserve the original measure; only that choice-free clause is used. Compositions, iterates and completions preserve invariance.
Countable additivity gives finite additivity by padding with empty sets. Measures on sigma-algebras.
The measure of a measurable subset is bounded by that of its ambient set. Measures are monotone.
Proof
Given: Let be a measure-preserving system with . For put . Then the measurable sets , , are pairwise disjoint and all have measure zero.
Each is measurable and preserves , so and every are measurable and . Here is the identity.
For , membership of in both and would give and . This contradicts the absence of every positive return from . Thus the tower sets are pairwise disjoint.
For every positive integer , finite additivity and monotonicity give . Since the right side is finite, a positive would violate this bound for an integer . Hence , and step 1.1 makes every tower level null. This also covers and .
Poincare recurrence for finite measure-preserving systems
Statement
In a measure-preserving system with , for every almost every has for infinitely many positive integers .
Facts & Assumptions
The set with no positive return and every one of its inverse-image levels are measurable and null. No-return sets have disjoint null preimage towers.
A countable union of measurable null sets is null. Finite and countable subadditivity of measures.
Proof
Given: In a measure-preserving system with , for every almost every has for infinitely many positive integers .
Put and . Every set in this union is measurable and null, whence is measurable and .
If has only finitely many positive return times, the finite nonempty set has a largest member (it contains zero). There is no positive return to from , so and . Thus every returns infinitely often. Conversely a point of has no visit after , so the exceptional set is exactly and is measurable. The argument includes the case of no positive return by taking .
Topological recurrence on second-countable spaces
Statement
Let have a countable open basis contained in , and let preserve a finite measure on . Outside one measurable null set, every neighborhood of is revisited infinitely often by its positive orbit. If the topology is induced by a metric , there are strictly increasing positive integers with .
Facts & Assumptions
Finite-measure recurrence applies to each measurable basis member. Poincare recurrence for finite measure-preserving systems.
A basis refines each open neighborhood at its point. Second countability: an at most countable basis for the topology.
The exceptional union over the countable basis is null. Finite and countable subadditivity of measures.
Each nonempty set of eligible positive return times has a least member. The well-ordering principle.
Proof
Given: Let have a countable open basis contained in , and let preserve a finite measure on . Outside one measurable null set, every neighborhood of is revisited infinitely often by its positive orbit. If the topology is induced by a metric , there are strictly increasing positive integers with .
For each basis member define its exceptional set explicitly as . The recurrence proof shows that is measurable and null. Thus is measurable and null. This is a prescribed family, not a choice of null covers. A finite basis is handled by a finite union, and the empty space has no points to check.
If and is a neighborhood of , choose an open set with and a basis member with . Since , infinitely many positive iterates enter , and hence .
In the metric case set and let be the least integer exceeding for which , for . Infinitely many visits to the ball make this set nonempty. Least-element recursion supplies the sequence without countable choice; and the displayed bound proves convergence.
First-return times and induced transformations
Definition
Let preserve finite measure and let satisfy . For define the first-return time
A nonempty set of return times has a least element by The well-ordering principle. Define the infinitely returning core
This is the set-limsup convention of Limit superior and limit inferior of a sequence of sets. It is measurable by Sigma-algebras are closed under countable intersections, differences, symmetric differences, and set limits, and Poincare recurrence for finite measure-preserving systems gives . Define the induced transformation and normalized measure by
Here the trace is as in The trace of a sigma-algebra on a subset. Since is measurable, the trace equals : each intersection with is measurable and each such equals . Its closure under relative complement and countable union follows directly from these same operations in ; no sequence of ambient representatives needs to be chosen. This supplies the measurable-subset instance of The trace of a sigma-algebra is a sigma-algebra on the traced subset locally.
For , is finite, and the infinitely many visits after are exactly positive visits of , so . Restricting countable additivity of and dividing by the positive finite number makes a measure; its total mass is . The value is allowed for on , but is never used as an iterate in . No choice axiom enters this construction.
First-return time and induced map are measurable
Statement
With as in the first-return definition, is measurable for the full power-set sigma-algebra on this countable target, and is measurable for .
Facts & Assumptions
The core is measurable and T_E is an everywhere defined self-map of it. First-return times and induced transformations.
Every finite iterate is measurable on the original sigma-algebra. Compositions, iterates and completions preserve invariance.
Trace sets are intersections with the domain. The trace of a sigma-algebra on a subset.
Proof
Given: With as in the first-return definition, is measurable for the full power-set sigma-algebra on this countable target, and is measurable for .
For , the fiber is measurable. At the empty intersection is . The fiber at infinity is . Every inverse image of a subset of the countable target is a countable union of these fibers, proving measurability of .
For the measurability of implies . The identity expresses its inverse image as a measurable subset of , hence a trace set. Empty B gives an empty union of pieces; full B gives all of the core.
Induced transformations preserve restricted finite measure
Statement
For a finite measure-preserving system and a measurable with , its induced transformation on preserves both and . Neither invertibility nor ergodicity is required.
Facts & Assumptions
Return fibers and induced inverse images are measurable. First-return time and induced map are measurable.
The recurrent core is conull in E, and T_E is its self-map. First-return times and induced transformations.
Pullback by T preserves the original measure. Compositions, iterates and completions preserve invariance.
Additivity splits measurable sets into disjoint pieces. Measures on sigma-algebras.
Increasing unions of partial first-return sets have the supremum of their measures. Continuity from below for measures.
Proof
Given: For a finite measure-preserving system and a measurable with , its induced transformation on preserves both and . Neither invertibility nor ergodicity is required.
Fix a trace set ; it is ambient measurable. Write and . Pulling B back once and splitting at E gives . Pulling back and splitting at E gives . Thus for each , .
The H_n are disjoint first-return pieces. Each differs from by a subset of the measurable null set ; these differences are themselves measurable. Consequently the finite-sum identity implies . Passing to the increasing union gives .
Apply the same inequality to . Since maps its entire domain to itself, . All measures here are finite, so gives the reverse inequality. Equality follows for every B; division by proves invariance of .
Inducing an ergodic system gives an ergodic system
Statement
If is an ergodic probability-preserving transformation and , then on is ergodic for .
Facts & Assumptions
The induced transformation preserves its probability measure. Induced transformations preserve restricted finite measure.
Positive sets in an ergodic probability system have conull forward entrance sets. Positive sets sweep out ergodic probability systems.
An everywhere invariant finite real measurable function is a.e. constant, and this property characterizes ergodicity. Equivalent invariant-set and invariant-function criteria for ergodicity.
Proof
Given: If is an ergodic probability-preserving transformation and , then on is ergodic for .
Let . It is measurable and conull by positive-set sweep-out. It is strictly invariant: if Tx eventually enters the core then x does; if x eventually enters at a positive time then Tx does, while if x is already in the core, its next positive return belongs to the core. Thus . On U let . The fibers are measurable.
Take any finite real measurable f on the core with everywhere. Define for and otherwise. The measurable q-fibers make F measurable. If , then , hence F(Tx)=F(x). If , then : before the first return there is no E visit, and the first return is in the core. Therefore . On , both x and Tx are outside U and F is zero.
Ergodicity of T and the everywhere invariant-function criterion give a constant c with F=c almost everywhere. Since F=f on the core, f=c for -almost every point there. The same criterion applied to the probability-preserving T_E now proves its ergodicity. Working with everywhere invariant functions avoids choosing representatives for almost-everywhere invariance.
Kac return-time formula without invertibility
Statement
If preserves an ergodic probability measure and is measurable with , then . Equivalently, . The formula does not require invertibility.
Facts & Assumptions
Return-time tails are measurable. First-return time and induced map are measurable.
Avoiding a positive set forever is a null event. Positive sets sweep out ergodic probability systems.
Apply integral invariance to measurable indicators. Integral invariance under measure-preserving maps.
Increasing finite tail sums converge in integral. Monotone convergence for the integral.
Decreasing avoidance sets have limiting measure equal to their intersection. Continuity from above when one set has finite measure.
Proof
Given: If preserves an ergodic probability measure and is measurable with , then . Equivalently, . The formula does not require invertibility.
Put and for . Since , its disjoint split at E consists of and . Indicator invariance and finite additivity therefore give for . In particular at j=0 this is .
For , the simple function equals on E and zero elsewhere. Its integral telescopes to . The sets C_N decrease to points avoiding E at all nonnegative times, a null set by sweep-out. Since , continuity from above yields .
The tail sums increase pointwise to , including infinite return times. Monotone convergence gives . The complement of the infinitely returning core in E is measurable null, so its nonnegative integral is zero, even where . Restriction and normalization therefore give ; multiplying by the positive denominator reverses the equivalence.
Kac integral formula for excursions
Statement
In an ergodic probability-preserving system, let . For nonnegative measurable , define on E, using the infinite nonnegative sum when . Then . For integrable real or complex f the excursion is absolutely summable a.e. on E; setting it to zero on its measurable null failure set gives the same identity.
Facts & Assumptions
In an ergodic probability system, almost every point visits every fixed positive-measure set at some positive time. Positive sets sweep out ergodic probability systems.
Pullback preserves nonnegative and integrable integrals. Integral invariance under measure-preserving maps.
Return-time tails and finite iterates are measurable. First-return time and induced map are measurable.
Nonnegative truncations and excursion partial sums pass through integrals. Monotone convergence for the integral.
After absolute integrability is established, real/complex component integrals combine linearly. The Lebesgue integral is linear on .
The measures of decreasing measurable sets of finite measure converge to the measure of their intersection. Continuity from above when one set has finite measure.
Proof
Given: In an ergodic probability-preserving system, let . For nonnegative measurable , define on E, using the infinite nonnegative sum when . Then . For integrable real or complex f the excursion is absolutely summable a.e. on E; setting it to zero on its measurable null failure set gives the same identity.
First let . Put . Splitting the integral at E and pulling the complement part back gives . More generally pulling back the part of outside E gives the next remainder, while its part on E is . Thus for N>=1 the exact finite identity is . All products are defined piecewise as zero off their indicated sets.
The sets decrease, and their intersection is the complement of . This intersection is null by [F1]. Since the ambient probability measure is finite, [F6] gives . The remainder is bounded between zero and and hence vanishes. The excursion partial sums on E increase pointwise to S_Ef; monotone convergence proves the identity for bounded nonnegative f.
For arbitrary nonnegative f use . These increase pointwise to f, and : one inequality is termwise, and the other follows by first restricting to any finite number of excursion terms and then increasing m. Monotone convergence on X and E proves the equality, including infinite values.
For integrable real or complex f, apply step 3.1 to : . Thus is finite a.e. (otherwise its integral is at least times the positive measure of its infinity set for every K). On this conull set the excursion is absolutely summable. Apply step 3.1 to the positive and negative parts of the real and imaginary components, each bounded by . Their excursion integrals are finite, so linearity yields the asserted identity without subtracting infinities. Null-set values have no effect.
The circle, rotations and the doubling map
Definition
The circle is with distance . The minimum is attained, since . It is nonnegative and symmetric, and it vanishes precisely when . For minimizing integers k,l, , proving the triangle inequality.
Write for fractional part. The rotation of angle and the doubling map are
They satisfy and by the integer-minimum formula, so are continuous in the circle metric. This topology differs from the ordinary interval topology at zero: points tending to 1 from below tend to 0 on the circle.
Open circle balls of radius less than are single ordinary intervals or two intervals meeting the cut at 0 and 1. By Both and are dense in , and every nonempty open subset of is uncountable, is countably infinite and A product of two at most countable sets is at most countable, balls with rational centers and positive rational radii form a countable base: given a ball about x, take a rational center close enough to x and a smaller rational radius whose ball contains x and stays inside the original ball. Thus circle-open sets are countable unions of ordinary Borel sets. Conversely ordinary interval-open subsets of are circle-open, and the singleton is circle-closed. Every relatively open subset of is therefore circle-Borel. The two Borel sigma-algebras agree.
For measures we assume countable choice The Axiom of Countable Choice (). Let be the restriction of Lebesgue measurable sets, the family , and the restricted set function to , either on Borel sets or on Lebesgue measurable sets. The measure and volume clauses of Assuming countable choice, is a sigma-algebra containing every elementary set and is a complete measure extending elementary volume give its total mass one: singletons have measure zero by covering them with intervals of arbitrarily small length, so changing an interval endpoint does not change length. By is exactly the completion of the restriction of to the Borel sets, the latter version is the completion of the former (intersect its Borel representatives and null covers with ). Countable choice is used for these measure constructions only; the circle metric and maps above are choice-free.
Circle rotations preserve Lebesgue measure
Statement
Assume countable choice. For every real , is an invertible measure-preserving transformation for both Borel Lebesgue probability on the circle and its completion.
Facts & Assumptions
The circle has Borel probability and R_alpha is continuous; the measure construction uses countable choice. The circle, rotations and the doubling map.
Translation preserves Lebesgue measurable sets and their measures. Lebesgue outer measure, Lebesgue measurability and Lebesgue measure are unchanged by translation.
A generating pi-system containing the finite-mass whole space tests preservation. Measure preservation can be checked on a generating pi-system.
A Borel preserving map also preserves the completion under countable choice. Compositions, iterates and completions preserve invariance.
Proof
Given: Assume countable choice. For every real , is an invertible measure-preserving transformation for both Borel Lebesgue probability on the circle and its completion.
Let . For any Borel , . The two pieces lie respectively in and and are disjoint. Translation invariance and additivity give . For a=0 the second piece is empty.
In particular this proves the inverse-image identity on the pi-system of half-open intervals and the whole circle. These generate the circle Borel sigma-algebra: ordinary open intervals are countable unions of half-open subintervals, and the Borel sigma-algebras agree by the circle definition. The whole-space measure is one, so the generating criterion applies (or directly use the identity for every Borel B in step 1.1). The completion clause extends preservation to all completed sets. The countable-choice use is exactly the earlier Lebesgue and completion construction.
Fractional-part arithmetic gives . The same argument applies to , so the inverse is measurable for either sigma-algebra. Thus invertibility here includes measurability of the inverse.
Irrational circle orbits are dense
Statement
For irrational , the subgroup is dense in the circle. For every and integer there is an integer with . These assertions are choice-free.
Facts & Assumptions
Circle distance is distance to the nearest integer. The circle, rotations and the doubling map.
N+1 points in N intervals contain a pair in one interval. The pigeonhole principle on .
Proof
Given: For irrational , the subgroup is dense in the circle. For every and integer there is an integer with . These assertions are choice-free.
For an integer , place , , in the N half-open intervals . Two indices i<j lie in one interval. Hence for q=j-i, and ; positivity follows from irrationality. Change q to -q if needed to obtain a subgroup point .
The subgroup contains , where ; the last term is interpreted modulo one if necessary. Consecutive gaps are beta and the remaining gap to 1 is at most beta. For every x in [0,1), taking gives . Since N can be arbitrarily large, every circle neighborhood meets the subgroup.
For fixed M>=1 let . Take N with and use the positive q from step 1.1 before changing its sign. That q exceeds M and has distance less than epsilon. For M=0 any q supplied there works after taking . Only finite minima and finite pigeonhole choices occur.
Circle rotation is ergodic for Lebesgue measure exactly at irrational angles
Statement
Assume countable choice. The circle rotation is ergodic for Borel Lebesgue probability and for its completion if and only if is irrational.
Facts & Assumptions
All positive and negative powers of a rotation preserve either measure. Circle rotations preserve Lebesgue measure.
Integer powers of an irrational rotation move any center arbitrarily close to another. Irrational circle orbits are dense.
Under countable choice, a positive measurable set has density-one points. Lebesgue density theorem.
The strict invariant-set criterion is equivalent to the mod-null criterion. Equivalent invariant-set and invariant-function criteria for ergodicity.
Proof
Given: Assume countable choice. The circle rotation is ergodic for Borel Lebesgue probability and for its completion if and only if is irrational.
If with integers p and q>=1, the set is Borel, has measure , and is permuted by R_alpha. Thus and the rotation is not ergodic for either measure. This includes integral alpha with q=1.
Now let alpha be irrational and let A be a strictly invariant measurable set. Suppose both A and its complement have positive measure. Choose density-one points a in A and c in its complement, different from the cut point zero. For sufficiently small , the circle balls I=B(a,r), J=B(c,r) have length 2r and satisfy and . The ordinary density theorem applies because these small balls at the chosen points do not cross the cut.
Choose an integer m with . Strict invariance and invertibility give , and the rotated interval I has a portion outside A of measure less than r/5. Its intersection with J has length greater than : both are radius-r arcs whose centers are less than r/10 apart. Subtracting the two exceptional portions, this intersection would contain points in both A and its complement on a set of measure at least , impossible. Thus every strict invariant A has measure zero or one, proving ergodicity. Together with step 1.1 this proves both directions.
Integer-base maps and b-adic circle intervals
Definition
On the circle of The circle, rotations and the doubling map, for an integer put . For every its level-n b-adic intervals are
These intervals partition ; at level zero the only interval is the whole circle. On the branch the map is . Iterating fractional-part arithmetic gives , and on this is . Each branch maps bijectively onto with inverse . Half-open endpoints ensure that every x belongs to exactly one branch, including x=0. Multiplication by the integer b respects congruence modulo one, and the distance formula gives . Thus these are continuous circle maps. The previously defined doubling map is exactly . None of these algebraic or metric facts uses a measure or a choice axiom.
Integer-base circle maps preserve Lebesgue measure
Statement
Assume countable choice. For every integer , the circle map is continuous, surjective and non-injective, and preserves Borel Lebesgue probability and its completion.
Facts & Assumptions
The b affine branches and Lipschitz bound are explicit. Integer-base maps and b-adic circle intervals.
The finite measure generator test applies with the whole space included. Measure preservation can be checked on a generating pi-system.
Countable choice gives preservation on the completion. Compositions, iterates and completions preserve invariance.
The nonzero dilation 1/b scales interval length by 1/b. For a nonzero real , dilation by multiplies Lebesgue outer measure by , and reflection in the origin preserves it.
Proof
Given: Assume countable choice. For every integer , the circle map is continuous, surjective and non-injective, and preserves Borel Lebesgue probability and its completion.
For , , with disjoint pieces of length . Thus their total measure is c-a. The empty interval has empty inverse image. The map is Borel measurable by the Lipschitz bound from its definition.
The half-open intervals together with the empty set form a pi-system containing [0,1) and generating the circle Borel sets, as in the circle definition. Its whole-space mass is one, so the finite generator theorem gives Borel preservation; the completion theorem gives completed preservation. Countable choice is inherited by the Lebesgue, dilation and completion suppliers and is assumed here.
For every y in [0,1), the explicit preimage y/b lies in [0,1) and maps to y, proving surjectivity. The distinct points 0 and 1/b both map to 0, proving non-injectivity. Continuity is the already established inequality .
Every integer-base circle map is strongly mixing
Statement
Assume countable choice. For every integer and every pair of Borel or completed Lebesgue measurable circle sets A,B, . Thus is strongly mixing for either measure.
Facts & Assumptions
D_b preserves either probability measure. Integer-base circle maps preserve Lebesgue measure.
Strong mixing follows from correlations on a generating pi-system containing X. Mixing is checkable on a generating pi-system.
Every completed set differs from a Borel set within a Borel null set. The completion domain and proposed completed set function of a measure space.
Proof
Given: Assume countable choice. For every integer and every pair of Borel or completed Lebesgue measurable circle sets A,B, . Thus is strongly mixing for either measure.
The b-adic intervals at all depths, together with the empty set, form a pi-system: two such intervals are nested or disjoint, and depth zero is X. They generate the circle Borel sets. Indeed every ordinary open interval in (0,1) is the union of the b-adic cells whose closures lie within it; the cell containing any specified interior point has arbitrarily small diameter. The endpoint zero is the intersection of over r, so relative interval-open sets are generated as well. Conversely each cell is Borel. The countable family of cells permits these unions in the generated sigma-algebra.
Let and . For , the interval I contains exactly depth-n cells. On each such cell, the inverse image under of J is a half-open interval of length . Hence . The same equality holds when either set is empty. The generator theorem proves Borel strong mixing.
For completed A,B take Borel A_0,B_0 and Borel null sets Z_A,Z_B containing their respective symmetric differences. For every n, , a completed null set by preservation. Thus the correlation and both marginal measures agree with those for A_0,B_0. The Borel limit proves the completed limit. Countable choice is inherited from the measure and completion suppliers; only finitely many representatives are selected here.
Doubling preserves Lebesgue measure
Statement
Assume countable choice. The doubling map is a continuous, surjective, non-injective transformation preserving Borel Lebesgue probability on the circle and its completion.
Facts & Assumptions
The preservation theorem applies to every integer b>=2. Integer-base circle maps preserve Lebesgue measure.
The stable doubling map has the fractional-part formula. The circle, rotations and the doubling map.
Proof
Given: Assume countable choice. The doubling map is a continuous, surjective, non-injective transformation preserving Borel Lebesgue probability on the circle and its completion.
By the definitions, . Since 2 is an allowed integer base, the base-map theorem proves preservation on both sigma-algebras and continuity. Its countable-choice measure and completion hypothesis is the assumption here.
Explicitly for ; the two pieces have total length c-a. For each y, y/2 is a preimage, while exhibits failure of injectivity. These branch identities also show why preservation concerns inverse images.
Doubling is ergodic for Lebesgue measure
Statement
Assume countable choice. Doubling is ergodic for Borel Lebesgue probability and its completion.
Facts & Assumptions
Doubling preserves each of the two measures. Doubling preserves Lebesgue measure.
It suffices that strictly invariant measurable sets have measure zero or one. Equivalent invariant-set and invariant-function criteria for ergodicity.
A positive Lebesgue measurable set has an interior density-one point. Lebesgue density theorem.
A nonzero affine branch scales measure by its slope, with translation handled by its separate supplier. For a nonzero real , dilation by multiplies Lebesgue outer measure by , and reflection in the origin preserves it.
Translations preserve the measures of the branch sets. Lebesgue outer measure, Lebesgue measurability and Lebesgue measure are unchanged by translation.
Proof
Given: Assume countable choice. Doubling is ergodic for Borel Lebesgue probability and its completion.
Let A be strictly invariant: . Then for every n. On the map is , so . Translation and dilation give .
If , choose a density-one point . Let I_n be its unique half-open depth-n cell and put h_n=2^{-n}. This cell lies in the centered interval apart from possibly an endpoint of measure zero. Thus . But step 1.1 makes the left side identically , so . Every strict invariant set is therefore null or conull, and the invariant-set criterion proves ergodicity. Countable choice is used in the measure, scaling and density suppliers.
Doubling is strongly mixing for Lebesgue measure
Statement
Assume countable choice. Doubling is strongly mixing for Borel Lebesgue probability and for its completion: for every pair of measurable circle sets.
Facts & Assumptions
The strong-mixing theorem covers b=2 and both measure domains. Every integer-base circle map is strongly mixing.
Doubling is the base-two fractional-part map. The circle, rotations and the doubling map.
Proof
Given: Assume countable choice. Doubling is strongly mixing for Borel Lebesgue probability and for its completion: for every pair of measurable circle sets.
The definition gives D=D_2. Taking b=2 in the integer-base theorem, with exactly its countable-choice assumption, yields the stated correlation limit for every Borel pair and every completed pair.
For clarity, if A and B are dyadic intervals of depths r and s, the proof gives the exact value for every n>=r. This includes the depth-zero whole circle; an empty test set gives zero. Thus the specialization retains the explicit dyadic correlation calculation as well as the general measurable-set conclusion.
Binary-sequence cylinders and fair-coin content
Definition
Put , the set of functions from nonnegative integers to . For a finite set and a function the cylinder consists of x with for every j in F. The empty prescription gives all of Omega. Every cylinder is nonempty by filling unspecified coordinates with zero.
The cylinder algebra is the set of finite unions of cylinders, including the empty union. It is an algebra in the sense of Algebras of subsets: any finite list of prescriptions can be refined to their finite coordinate union G; the complete prescriptions on G are disjoint nonempty atoms partitioning Omega, and union, intersection and complement of unions of these atoms again are such unions.
Give each G-atom mass . If A is a union of m distinct G-atoms, define its fair-coin content by . This is independent of G and its representation. Enlarging G to H splits each atom into exactly atoms, leaving its mass unchanged. Two representations agree after refining to their coordinate union; because all refined atoms are nonempty, the same subset A selects precisely the same atoms in both. Common refinement also proves finite additivity on disjoint sets. In particular , , and . All constructions here involve finite coordinate sets and are choice-free.
Binary-sequence space is compact without Tychonoff
Statement
On put and for . This is a metric whose topology is generated by cylinders; it is compact in ZF.
Facts & Assumptions
Finite prescriptions define nonempty cylinders and each prefix has two disjoint children. Binary-sequence cylinders and fair-coin content.
Compactness means every open cover has a finite subcover. Open cover, subcover, compact metric space, and compact subset of a metric space.
Proof
Given: On put and for . This is a metric whose topology is generated by cylinders; it is compact in ZF.
Positive definiteness and symmetry follow immediately from the first disagreement. If x,y agree before index r and y,z agree before index s, then x,z agree before min(r,s). Thus , with equal pairs included. A prefix cylinder fixing indices 0 through m-1 is the open ball of radius about any of its points when m>=1. Arbitrary finite-coordinate cylinders are finite unions of sufficiently long prefixes. Conversely prefixes of arbitrarily small diameter fit in every ball. Hence cylinders generate exactly the metric topology and are clopen.
Fix an open cover with no finite subcover. The empty prefix cylinder has no finite subcover. If a prefix cylinder has no finite subcover, at least one of its two children also lacks one; otherwise the union of the two finite subcovers would cover it. Choose the zero child if it lacks a finite subcover, and the one child otherwise. This is a uniquely specified recursion, producing a binary sequence x whose every prefix cylinder lacks a finite subcover.
Some member U of the cover contains x. Since U is open, it contains a prefix cylinder about x. That cylinder has the one-element subcover {U}, contradicting its construction. Therefore no open cover without a finite subcover exists, proving compactness. The recursion makes no arbitrary infinite choices; neither Tychonoff nor dependent choice is used.
Fair-coin cylinder content is a premeasure
Statement
The fair-coin content on the cylinder algebra is a finite premeasure, with . This assertion is choice-free.
Facts & Assumptions
Common refinement proves finite additivity and total mass one. Binary-sequence cylinders and fair-coin content.
Omega is compact and cylinders are clopen. Binary-sequence space is compact without Tychonoff.
Only disjoint countable unions remaining in the algebra must be additive. Premeasures on algebras of sets.
Proof
Given: The fair-coin content on the cylinder algebra is a finite premeasure, with . This assertion is choice-free.
Let with disjoint and . All these sets are clopen, being finite unions of clopen cylinders. The family consisting of and all A_n is an open cover of Omega. Compactness gives finitely many members covering Omega and hence finitely many A_n covering A. Using their least indices if the same member repeats gives a finite index set F with . This uses ambient compactness only of Omega itself, not an unstated compact-subset criterion.
For every n outside F, disjointness gives . Thus all other terms have zero content, and finite additivity gives . If A is empty every A_n is empty and the same identity is zero equals zero. Along with and , this is precisely a finite premeasure.
Fair-coin measure on binary sequences
Statement
Assume countable choice. There is a unique Borel probability on binary sequence space such that a cylinder prescribing k distinct coordinates has mass . Its completion is a complete probability measure on the completion of the Borel sigma-algebra.
Facts & Assumptions
The cylinder-algebra content is a finite premeasure. Fair-coin cylinder content is a premeasure.
Under countable choice the premeasure extends to its generated sigma-algebra. Assuming countable choice, a premeasure extends through its induced outer measure.
A finite premeasure extension is unique. A finite premeasure has at most one extension to its generated sigma-algebra.
Under countable choice the Borel probability has a complete extension on its completion domain. Assuming countable choice, every measure space has a unique complete extension to its completion.
Proof
Given: Assume countable choice. There is a unique Borel probability on binary sequence space such that a cylinder prescribing k distinct coordinates has mass . Its completion is a complete probability measure on the completion of the Borel sigma-algebra.
The prefix cylinders form a countable base: length m has exactly possible prefixes, enumerated by the binary integers from 0 to , and the pairs of length and index admit a diagonal enumeration. Every cylinder is open, and every open set is the union of the subfamily of prefix cylinders contained in it. It follows that the sigma-algebra generated by the cylinder algebra is exactly the metric Borel sigma-algebra.
Apply the extension theorem to the premeasure p_0. It gives a Borel measure p agreeing with every cylinder mass and with . Any other measure with these cylinder masses agrees on finite disjoint unions by finite additivity, hence on the entire algebra; finite-premeasure uniqueness makes it equal to p.
The completion theorem gives a complete probability extending p, since the whole-space mass remains one. Countable choice is used by the cited extension and completion constructions; the preceding finite-algebra and compactness arguments themselves were choice-free. This constructs this particular binary measure, not a general infinite product measure.
The fair-coin one-sided shift preserves measure and is mixing
Statement
Assume countable choice. The one-sided left shift , , preserves the fair-coin probability and its completion, is strongly mixing for both, and hence is ergodic.
Facts & Assumptions
A cylinder prescribing k coordinates has mass 2^-k. Fair-coin measure on binary sequences.
Finite-mass preservation may be checked on cylinders and the whole space. Measure preservation can be checked on a generating pi-system.
Cylinder correlation limits imply Borel mixing. Mixing is checkable on a generating pi-system.
Preservation extends to the completion under countable choice. Compositions, iterates and completions preserve invariance.
Strong mixing implies ergodicity for probability systems. Mixing implies weak mixing, which implies ergodicity.
Proof
Given: Assume countable choice. The one-sided left shift , , preserves the fair-coin probability and its completion, is strongly mixing for both, and hence is ergodic.
For a cylinder C prescribed on F, imposes the same values on . It is a cylinder with the same number of fixed coordinates and the same mass. Inverse images of prefix cylinders are open, so sigma is continuous and hence Borel measurable. Cylinders together with the empty set form a generating pi-system containing Omega. Since its mass is one, the preservation criterion applies; the completion clause then gives completed preservation.
If C and H prescribe finite coordinate sets F and G, then prescribes G+n. For all sufficiently large n these are disjoint from F, so their intersection is a cylinder prescribing coordinates. Its mass is . Empty sets give zero correlations. The mixing criterion now proves mixing for arbitrary Borel pairs.
For two completed sets replace each by a Borel core modulo a Borel null cover, as supplied by the completion construction. The symmetric difference of the intersection and its Borel version lies in the union of the first null cover and the nth pullback of the second. Preservation makes that union null. Correlations and marginal masses therefore agree exactly with their Borel versions for each n, proving completed mixing. Finally the mixing implication proves ergodicity for both probability spaces. Countable choice is inherited from the fair-coin extension and completion; coordinate calculations use only finite counting.
A countable dense family of continuous functions on a compact metric space
Statement
Assume the Axiom of Countable Choice. If is a nonempty compact metric space, there is a sequence in such that for every and some satisfies . One may use all rational polynomials in finitely many distance functions to an enumerated dense subset, including the rational constant functions.
Facts & Assumptions
Under , compact metric spaces have at most countable dense subsets. A compact metric space has a countable dense subset, by countable choice.
A nonempty at most countable set admits an enumeration, with repetitions. A nonempty set is at most countable iff it is a surjective image of .
The rational numbers are countably infinite. is countably infinite.
Finite products of at most countable sets are at most countable, by induction on the number of factors. A product of two at most countable sets is at most countable.
Under , a countable union of at most countable sets is at most countable. Countable unions of at most countable sets, assuming .
The uniform closure of a unital real function algebra is a lattice. The countable approximant selections in its proof are justified here by . The uniform closure of a unital real function algebra is closed under absolute value, maximum, and minimum.
A unital separating real algebra interpolates prescribed values at two distinct points. A unital separating real function algebra interpolates arbitrary values at two distinct points.
Every open cover of has a finite subcover. Open cover, subcover, compact metric space, and compact subset of a metric space.
Rational numbers are dense in the real numbers. Both and are dense in , and every nonempty open subset of is uncountable.
Proof
Given: Assume the Axiom of Countable Choice. If is a nonempty compact metric space, there is a sequence in such that for every and some satisfies . One may use all rational polynomials in finitely many distance functions to an enumerated dense subset, including the rational constant functions.
By [F1] fix a countable dense subset of . It is nonempty: otherwise no ball around a point of the nonempty space would meet it. By [F2] enumerate it as . Put . The triangle inequality gives , so each is continuous. Every continuous real function on is bounded: the open sets for positive integers cover , and a finite subcover yields a bound. Thus all supremum norms below are finite.
Let be the real algebra of finite polynomials in the and the constant function , and let be its subset with rational coefficients. These are continuous functions, since finite sums and products of continuous real functions are continuous. The set is nonempty and at most countable: monomials are coded by finite lists of natural indices (the empty list codes ), and a polynomial is coded by a finite list of pairs consisting of a rational coefficient and such a monomial. Induction using [F4], and then [F5] over list lengths, makes both coding sets countable; their evaluation images are countable by composing an enumeration and using [F2]. This uses [F3] for the rational entries. The algebra separates distinct : choose with ; then .
Write in the supremum metric. It is a real vector space: if , choose approximants within any prescribed positive errors and use , with the analogous scalar estimate. It is closed by the definition of closure. By [F6] it is closed under finite maximum and minimum. In applying that lemma, countable choice supplies its sequences of algebra approximants and polynomial approximants; the later diagonal indices can be taken least eligible integers. No arbitrary family indexed by is selected.
Fix and . For a fixed , use the entire set . The open sets , for all , cover : at , [F7] supplies one interpolant taking the values , while the constant handles . By [F8] finitely many of these open sets cover ; choose a representing function for each of these finitely many sets and form their maximum . Then , , and throughout . Only finitely many existential witnesses were needed for this fixed .
Use the entire set . The preceding step proves that the open sets , for all , cover , without selecting one for each . A finite subcover and finitely many representatives give ; their minimum satisfies pointwise, hence . Given any , take and an with . Then . This proves density of , including when is a singleton, for which constants alone interpolate.
For , where the are monomials, let . If , then . Otherwise, given , use [F9] to choose rational with . The finite sum belongs to and satisfies , even when some . Approximate by within using the preceding step, and by within . An enumeration of the nonempty countable by [F2] is the required . Countable choice has been used for the dense subset, the countable-union theorem, and the sequences in [F6]; all cover selections in the local density proof were finite.
A compact-metric probability representation using countable choice
Statement
Assume the Axiom of Countable Choice. Let be a nonempty compact metric space and let be real-linear, positive in the sense that implies , and normalized by . Then there is a Borel probability on with for every continuous real . It is outer regular on Borel sets and inner regular on open sets by compact subsets. No Dependent Choice is required.
Facts & Assumptions
Every open cover of has a finite subcover. Open cover, subcover, compact metric space, and compact subset of a metric space.
A closed subset of a compact metric space is compact. A closed subset of a compact metric space is compact.
The measurable sets of an outer measure form a sigma-algebra carrying its restriction as a complete measure. Carathéodory's theorem: measurable sets form a sigma-algebra carrying a complete measure.
The nonnegative integral is monotone and homogeneous. Monotonicity and nonnegative homogeneity of the nonnegative integral.
The Lebesgue integral is linear on integrable real functions. The Lebesgue integral is linear on .
Proof
Given: Assume the Axiom of Countable Choice. Let be a nonempty compact metric space and let be real-linear, positive in the sense that implies , and normalized by . Then there is a Borel probability on with for every continuous real . It is outer regular on Borel sets and inner regular on open sets by compact subsets. No Dependent Choice is required.
For an open set define when , and . The triangle inequality, followed by the infimum, shows that is 1-Lipschitz in the first case; it is positive at every point of because that point has a ball contained in , and it vanishes outside . If a nonempty closed lies in , the sets for positive integers cover . Adjoining and using [F1] gives a with on . Consequently equals 1 on , takes values in , and has support contained in . Here support means the closure in of the nonzero set, which is compact by [F2]. For use . Any compact subset of a metric space is closed: the empty subset is closed, and for a nonempty compact subset, if is outside it, its balls centered at of radii have a finite subcover; the minimum of these finitely many positive radii gives a ball at missing the subset. Thus these cutoffs apply also to every compact .
Write for continuous with and support contained in . Positivity and linearity give monotonicity of by applying positivity to differences, and by comparison with constants. The norm is finite: the open sets cover and a finite subcover bounds . Define and . The zero function and the open set make both families nonempty; , , and . Monotonicity immediately implies for open , and monotonicity and zero empty-set value for .
For a closed nonempty with finitely many open , put . Compactness, applied to the sets and , gives with on . Set and . Define where , and zero where . Near a zero of the formula is , proving continuity there. Each has support in , is nonnegative and at most 1, and on the open neighborhood of . For empty use all zero functions. This constructs a finite subordinate partition without any selection principle.
For open and , its closed support is covered by finitely many distinct by [F1] after adjoining . If is empty, . Otherwise the partition in step 2.1 gives , with . Hence ; taking the supremum proves open-set subadditivity. Given arbitrary and , countable choice now selects simultaneously open with . These are a specified countable family of nonempty sets of admissible opens. Thus . Letting decrease to zero proves that is an outer measure; if the sum on the right is infinite the inequality is immediate and no selection is needed.
For open and , with support . For any , the supports are disjoint, so . Therefore . Taking the supremum over gives . For arbitrary , monotonicity replaces in the two terms by ; taking the infimum over open proves . The opposite inequality is outer subadditivity. Thus every open is Carathéodory measurable, and [F3] gives a Borel measure . It satisfies and is outer regular by its defining infimum and .
For compact , one has . Indeed such is nonnegative everywhere, and for the open set contains . Every satisfies , whence , and then . Conversely for each open , step 1.1 supplies with on ; hence the displayed infimum is at most . Infimizing over gives the reverse inequality. Empty has both sides zero using . If and , then for every , so the compact formula gives . Taking the supremum over proves ; monotonicity proves equality. This is the required inner regularity on opens.
Let and . Choose a positive integer with , put , for , and . These are continuous, the are compact by [F2], , and . The compact formula gives the lower bound ; comparison with every continuous majorant of gives the upper bound . By [F4] the same bounds hold for . All these integrals are finite since and . Summing and applying [F5] locates both and in the same interval of length . Since is arbitrary they are equal. Finally proves equality for every real continuous , using positivity, linearity and [F5]. Countable choice was spent only on the admissible open supersets in step 3.1; the cutoffs and partitions are explicit metric formulas.
Probability sequences on compact metric spaces have integral-convergent subsequences
Statement
Assume countable choice. Let be Borel probabilities on a nonempty compact metric space . There are strictly increasing positive integers and a Borel probability on such that for every . The limiting probability can be taken outer regular on Borel sets and inner regular on open sets.
Facts & Assumptions
Under countable choice, has an enumerated uniformly dense family. A countable dense family of continuous functions on a compact metric space.
Every bounded real sequence has a convergent subsequence. Bolzano-Weierstrass: every bounded real sequence has a convergent subsequence.
A positive normalized real-linear functional on is represented by a regular Borel probability under countable choice. A compact-metric probability representation using countable choice.
Nonnegative integrals are monotone and homogeneous. Monotonicity and nonnegative homogeneity of the nonnegative integral.
Integrals of integrable functions are linear. The Lebesgue integral is linear on .
Proof
Given: Assume countable choice. Let be Borel probabilities on a nonempty compact metric space . There are strictly increasing positive integers and a Borel probability on such that for every . The limiting probability can be taken outer regular on Borel sets and inner regular on open sets.
Fix the dense family of [F1]. Continuous real functions on are bounded, as proved there; they are Borel measurable by continuity. For every Borel probability , [F4] bounds the integral of by , so is integrable. Positivity and [F5], applied to , give . In particular is a bounded real sequence for each .
There is a deterministic convergent-subsequence rule for a bounded real sequence restricted to an infinite subset of the positive integers, with a specified bound . Start with . Bisect the current closed interval; retain its left half if infinitely many indices in have values there, and otherwise retain the right half, which must have infinitely many such indices. At stage choose the least eligible index greater than , with , whose value lies in . The indices exist because an infinite subset of the naturals is unbounded. The intervals are nested and have lengths , so the selected values are Cauchy. They converge: [F2] provides a convergent subsequence with limit , and the Cauchy estimate followed by the triangle inequality with a sufficiently late member of that subsequence gives for all sufficiently large . This also works for . Left-half precedence and least indices make every stage unique, so ordinary recursion suffices; no Dependent Choice is used.
Set . Recursively apply the rule of step 1.2 to coordinate on with , and let be its infinite output index set. Thus , and the th coordinate converges along the increasing enumeration of . Let be the th smallest member of . Since , its th member is at least the th member of , which exceeds . Thus is strictly increasing. For every fixed , all with belong to and increase without bound, so converges. All index sets and enumerations are defined uniquely by the fixed rule.
For and , choose one with . For large , step 2.1 gives ; the two uniform error bounds of step 1.1 show that is Cauchy. It is bounded, and hence converges by the Cauchy-plus-[F2] argument in step 1.2. Define to be this unique limit. Passing to limits in [F5] proves real linearity, positivity passes to limits of nonnegative real numbers, and since every is a probability. Apply [F3] with exactly these hypotheses to obtain the regular Borel probability and the asserted convergence for every . The choices used are those in [F1] and [F3], both explicitly bounded by countable choice; neither the nested extraction nor the definition of the unique limit selects an arbitrary family of witnesses.
Krylov–Bogolyubov existence of an invariant probability
Statement
Assume countable choice. Every continuous self-map of a nonempty compact metric space admits a Borel probability satisfying for every Borel . Thus is a measure-preserving probability system.
Facts & Assumptions
Under countable choice, probability sequences on nonempty compact metric spaces have subsequences converging against every real continuous test function to a Borel probability. Probability sequences on compact metric spaces have integral-convergent subsequences.
The Dirac set function at a point is a probability on any sigma-algebra. A Dirac set function is a probability measure.
Nonnegative measurable functions have increasing simple approximations. Every nonnegative measurable function is the increasing limit of simple measurable functions.
Increasing nonnegative measurable approximations have increasing integrals converging to the limit integral. Monotone convergence for the integral.
Integrals are linear on integrable real functions. The Lebesgue integral is linear on .
Finite measures agreeing on a generating pi-system and on total mass coincide. Finite measures agreeing on a generating pi-system and on the whole space are equal.
Measure preservation means equality of the measure of every measurable set and its inverse image. Measure-preserving transformations and systems.
Proof
Given: Assume countable choice. Every continuous self-map of a nonempty compact metric space admits a Borel probability satisfying for every Borel . Thus is a measure-preserving probability system.
Fix one point and, for , define on the Borel sets. By [F2], each summand is a probability; finite sums preserve countable additivity because a finite sum commutes with the increasing partial sums of a nonnegative series. Thus is a Borel probability. For indicators its integral is exactly ; the simple integral gives this for every nonnegative simple function. Applying [F3] and [F4], with finite sums of increasing limits, gives for nonnegative Borel . For bounded real , apply this to and subtract by [F5]. The starting-point choice is a single existential instantiation, not an axiom of choice.
By [F1] there are and a Borel probability such that for all continuous real . Continuity of ensures that is also continuous. Step 1.1 telescopes to , of absolute value at most . Hence for every such , by [F5] and passage to the two limits.
Define for Borel . The class of sets whose inverse images are Borel is a sigma-algebra containing the opens, since is continuous; thus is defined on all Borel sets. Inverse images commute with complements and disjoint countable unions, so is a Borel probability. For indicators, . The finite simple-integral formula, then [F3] and [F4] on both sides, prove for every nonnegative Borel , including infinite values. Applying it first to verifies integrability of whenever is -integrable; positive/negative decomposition and [F5] then prove the real signed identity. Combining it with step 2.1 gives equality of and on all continuous real integrals.
To pass from these test functions to sets without invoking a stronger-choice LCH theorem, let be a nonempty closed subset of and put for . The infimum defining is 1-Lipschitz by the triangle inequality. It is zero on and positive outside , since the complement of is open. Thus is continuous and . By [F4] and the equal continuous integrals, ; total masses one give . Empty also has equal measure zero. The closed subsets form a nonempty pi-system containing and generate the Borel sigma-algebra because their complements are exactly the opens. All hypotheses of [F6] hold, so on the Borel sets. By the definition of , this is precisely [F7]. Countable choice enters through [F1]; the orbit, metric test functions and monotone simple approximants require no further selection principle.
False: measure-preserving transformations are invertible
Statement
The assertion that every measure-preserving probability transformation is invertible, even after restriction to an invariant conull set, is false. Assuming countable choice, doubling on the Lebesgue circle is a counterexample.
Facts & Assumptions
Doubling preserves the completed Lebesgue probability. Doubling preserves Lebesgue measure.
Invertibility requires a bijection; modulo-null invertibility requires one on an invariant measurable conull restriction. Invertible measure-preserving systems.
Translation preserves Lebesgue measurability and measure. Lebesgue outer measure, Lebesgue measurability and Lebesgue measure are unchanged by translation.
Finite unions of measurable null sets are null. Finite and countable subadditivity of measures.
Refutation
Given: The assertion that every measure-preserving probability transformation is invertible, even after restriction to an invariant conull set, is false. Assuming countable choice, doubling on the Lebesgue circle is a counterexample.
The map preserves the probability in [F1], but with . Therefore it is not injective and is not invertible in [F2]. Countable choice is the stated assumption of the Lebesgue probability supplier.
More strongly, suppose were a measurable conull subset of on which is injective, and put . For each the distinct points have equal images, so at least one belongs to . Hence . By [F3] both sets on the right are measurable and null, and [F4] makes their union null. This contradicts the interval measure on the left. There is no injective conull restriction at all, in particular none satisfying the extra invariance and inverse-measurability requirements of [F2].
False: ergodicity implies strong mixing
Statement
Assuming countable choice, the assertion that every ergodic probability-preserving transformation is strongly mixing is false: any irrational circle rotation gives a counterexample.
Facts & Assumptions
Irrational circle rotations preserve Lebesgue probability and are ergodic. Circle rotation is ergodic for Lebesgue measure exactly at irrational angles.
Irrational rotations have arbitrarily large positive iterates arbitrarily close to zero. Irrational circle orbits are dense.
Strong mixing requires every set correlation to tend to the product of measures. Strong and weak mixing on a probability space.
Refutation
Given: Assuming countable choice, the assertion that every ergodic probability-preserving transformation is strongly mixing is false: any irrational circle rotation gives a counterexample.
Fix an irrational and the ergodic Lebesgue system of [F1]. Set , of measure . By [F2], define recursively to be the least integer greater than , with , such that . The existence is [F2] and leastness gives unique choices. Thus and .
For a translation by a circle displacement with representative , the half-circle and its inverse translate overlap in length : if , the part in is , up to endpoints, and for it is . Consequently . Strong mixing in [F3] would require the full sequence, hence this subsequence, to tend to . Since , mixing fails. Countable choice is inherited only from the ergodic Lebesgue system in [F1]; the return-index recursion is canonical.
False: Poincare recurrence needs no finite total measure
Statement
Poincaré recurrence is false if the finite-total-measure hypothesis is omitted. Assuming countable choice, on preserves measure, but no point of the positive-measure set ever returns to at a positive time.
Facts & Assumptions
Under countable choice, Lebesgue measure on the real line is a measure and has infinite total mass. Assuming countable choice, is a sigma-algebra containing every elementary set and is a complete measure extending elementary volume.
The half-open interval is measurable of measure one. A box in with parameters is Lebesgue measurable of measure , whichever of its faces are included.
Translation preserves Lebesgue measurability and measure. Lebesgue outer measure, Lebesgue measurability and Lebesgue measure are unchanged by translation.
A measurable self-map preserves measure exactly when each measurable inverse image has the original measure. Measure-preserving transformations and systems.
Refutation
Given: Poincaré recurrence is false if the finite-total-measure hypothesis is omitted. Assuming countable choice, on preserves measure, but no point of the positive-measure set ever returns to at a positive time.
By [F1] this is a measure space with . For every Lebesgue measurable , one has , which is measurable and has measure by [F3]. Thus is measurable and measure preserving by [F4], even though the total measure is infinite. The set has measure one by [F2]. Countable choice is used to obtain the Lebesgue measure in [F1] and the interval value in [F2].
Induction gives for every . If and , then , so . The exceptional set for recurrence is therefore all of , of measure one, rather than a null subset. The time-zero visit does not satisfy the positive-return conclusion.
False: an ergodic invariant sigma-algebra has only two sets
Statement
Assuming countable choice, it is false that an ergodic system has only the empty set and the whole space as strictly invariant measurable sets. For Lebesgue doubling on , the dyadic rationals form a nonempty proper strictly invariant null set.
Facts & Assumptions
Doubling is ergodic for Lebesgue probability. Doubling is ergodic for Lebesgue measure.
Strict invariance means exact equality with the inverse image. Strict and mod-null invariant sigma-algebras.
Countable real sets are measurable and Lebesgue null under countable choice. Every at most countable subset of is Lebesgue null; in particular .
Countable unions of finite sets are countable under countable choice. Countable unions of at most countable sets, assuming .
Refutation
Given: Assuming countable choice, it is false that an ergodic system has only the empty set and the whole space as strictly invariant measurable sets. For Lebesgue doubling on , the dyadic rationals form a nonempty proper strictly invariant null set.
Put . Each level is finite, so [F4] and [F3] give measurability and ; it is also Borel as a countable union of finite closed subsets of the circle. It contains and is proper: , since would give , while induction gives the residue of modulo 3 as for even and for odd .
If is dyadic, then is dyadic, including when . Conversely, if , write with . Then is dyadic and belongs to . Hence exactly, as required by [F2]. By [F1] the system is ergodic, but its invariant sigma-algebra contains this nonempty proper set. Ergodicity only constrains its measure to zero or one. Countable choice is inherited from [F1], [F3] and [F4].
False: every orbit of an ergodic system is dense
Statement
Assuming countable choice, an ergodic probability-preserving continuous map need not have every orbit dense. Lebesgue doubling on the circle is ergodic, but the forward orbit of zero is the singleton .
Facts & Assumptions
Doubling is ergodic for Lebesgue probability. Doubling is ergodic for Lebesgue measure.
The circle is represented by , with doubling and the circle metric. The circle, rotations and the doubling map.
Refutation
Given: Assuming countable choice, an ergodic probability-preserving continuous map need not have every orbit dense. Lebesgue doubling on the circle is ergodic, but the forward orbit of zero is the singleton .
The map of [F2] satisfies , so induction gives for every . Its orbit is exactly . The circle ball of radius centered at is a nonempty open set disjoint from this orbit, since . Thus the orbit is not dense.
Nevertheless [F1] proves that doubling is ergodic for Lebesgue probability, so the displayed orbit refutes the every-point assertion. The countable-choice assumption is needed for that measure-theoretic supplier; the fixed-orbit and open-ball calculations in step 1.1 are choice-free.
False: constant continuous invariants characterize measure ergodicity
Statement
The assertion that a probability-preserving continuous map is measure ergodic whenever all of its everywhere invariant continuous real functions are constant is false. On the circle, doubling has only constant everywhere invariant continuous functions, but is not ergodic for . This atomic counterexample is choice-free, and therefore also holds under countable choice.
Facts & Assumptions
Use only the choice-free metric and map clauses defining the circle and . The circle, rotations and the doubling map.
A probability-preserving map is ergodic when each strictly invariant measurable set has measure zero or one. Ergodicity relative to an invariant measure.
Dirac set functions are probabilities without a choice assumption. A Dirac set function is a probability measure.
The natural numbers are cofinal in the reals. Every complete ordered field is Archimedean.
Refutation
Given: The assertion that a probability-preserving continuous map is measure ergodic whenever all of its everywhere invariant continuous real functions are constant is false. On the circle, doubling has only constant everywhere invariant continuous functions, but is not ergodic for . This atomic counterexample is choice-free, and therefore also holds under countable choice.
For from [F1], , and . The measure displayed in the statement is a Borel probability by [F3] and finite additivity of the weighted sum of measures; countable additivity follows by commuting a finite sum with increasing partial sums. For every Borel , , so it is invariant. Continuity of gives its Borel measurability.
Put . Each inverse image is Borel since is continuous and is closed, so is Borel. A point lies in exactly when it eventually maps to zero. If it does, then so does its image, since zero is fixed; conversely if its image eventually maps to zero, the point does one step later. Thus . The point zero is in , while and stay in their two-cycle and never reach zero. Therefore , which violates [F2].
Now let continuous real satisfy at every circle point. Iteration shows for , since . For any put . Then , so in the circle metric: by induction and [F4] gives . Continuity yields . Hence all the stated continuous invariants are constant while the invariant probability is nonergodic. No Lebesgue measure, countable union of countable sets, or choice principle is used; the sets and sequences are explicitly defined.
5 · Examples, counterexamples and false statements
None yet.
Sources
- E–W Theorem 2.11 p.21
- E–W Theorem 2.11 p.21; Sarig Theorem 1.1
- E–W Exercise 2.2.3 pp.22–23
- Sarig Definition 1.18 pp.28–29; domain correction
- Sarig §1.6.4 p.28
- Sarig Theorem 1.7(1), p.28
- Sarig Theorem 1.7(2), pp.28–29
- Sarig Theorem 1.7(3), pp.28–29 (specialization f=1)
- Sarig Theorem 1.7(3), pp.28–29
- E–W Examples 2.2 and 2.4 pp.14–15
- E–W Example 2.2 p.14
- E–W Proposition 2.16 p.26 and Example 2.33 p.49
- E–W Exercise 2.4.1 p.32; Proposition 2.16 conclusion
- E–W Example 2.4 pp.14–15; MT-22 binding base-b amendment
- E–W Example 2.4 pp.14–15, b-branch generalization
- Sarig Proposition 1.5 p.9, b-adic branch-count generalization
- E–W Example 2.4 pp.14–15
- Sarig Proposition 1.5 p.9, conclusion; density argument is the MT-22 prescribed local replacement
- Sarig Proposition 1.5 p.9
- E–W Examples 2.8–2.9 pp.17–18
- E–W Examples 2.8–2.9 compact metric footnote; elementary binary-tree proof
- E–W Examples 2.8–2.9; local compactness construction
- E–W Examples 2.8–2.9 with local Caratheodory route
- E–W Proposition 2.15; Exercise 2.7.9
- E–W §1.4 pp.97–98, replacing weak-star compactness with the design-required local argument
- Compact-metric adaptation of the RMK construction; Cohn, Measure Theory, 2nd ed., Chapter 7
- E–W §3.1 pp.97–98; local diagonal/RMK replacement for source weak-star compactness
- E–W Theorem 4.1 and Corollary 4.2 p.98
- E–W Example 2.4
- E–W Example 2.33
- E–W Example 2.12 pp.21–22
- E–W Proposition 2.14; doubling example specialization
- Sarig Proposition 1.5, fixed-point specialization
- E–W ergodicity definition and doubling example; explicit measure specialization