Alphabeta Math
Pipeline-generated
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

Measure Preserving Transformations and Poincare Recurrence — Examples

1 · Prerequisites

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

ExampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-13Open item page →

An explicit invariant set for a rational rotation

Example

Assume countable choice. If α=p/q with integers p, q1 in lowest terms, then E=j=0q1[j/q,j/q+1/(2q)) is strictly invariant under Rα and has Lebesgue measure 1/2. Thus this rational rotation is not ergodic.

Facts & Assumptions

[F1]

Circle rotations preserve Lebesgue probability and have measurable inverses. Circle rotations preserve Lebesgue measure.

[F2]

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 α=p/q with integers p, q1 in lowest terms, then E=j=0q1[j/q,j/q+1/(2q)) is strictly invariant under Rα and has Lebesgue measure 1/2. Thus this rational rotation is not ergodic.

1.1

Write Ej=[j/q,j/q+1/(2q)). For x=j/q+t with 0t<1/(2q), one has Rp/qx=((j+p)modq)/q+t. The residue map jj+pmodq is a permutation, with inverse subtraction of p. Thus rotation maps the collection of Ej onto itself and, being bijective, satisfies Rp/q1E=E. The half-open convention makes the formula exact at every included left endpoint and excludes every right endpoint.

F1
2.1

The q intervals Ej are pairwise disjoint and each has length 1/(2q). Hence λ(E)=j=0q11/(2q)=1/2. It is Borel, and its complement also has measure 1/2. By [F1] the ambient system preserves the probability, so [F2] proves nonergodicity. For q=1, this is simply the identity rotation and E=[0,1/2). Countable choice is used only for the Lebesgue probability supplied by [F1].

1.1F1F2
ExampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-13Open item page →

Dyadic preimages under doubling

Example

Assume countable choice. For doubling D(x)={2x} on the circle, D1[0,1/2)=[0,1/4)[1/2,3/4), of measure 1/2. In contrast, D[0,1/2)=[0,1) has measure one.

Facts & Assumptions

[F1]

Doubling preserves Lebesgue probability by inverse images. Doubling preserves Lebesgue measure.

Verification

Given: Assume countable choice. For doubling D(x)={2x} on the circle, D1[0,1/2)=[0,1/4)[1/2,3/4), of measure 1/2. In contrast, D[0,1/2)=[0,1) has measure one.

1.1

On [0,1/2), D(x)=2x, and 02x<1/2 is equivalent to 0x<1/4. On [1/2,1), D(x)=2x1, and 02x1<1/2 is equivalent to 1/2x<3/4. These two branches exhaust the circle and their solution intervals are disjoint. Each interval has length 1/4, so their union has measure 1/2, agreeing with the preservation in [F1].

F1
2.1

For x[0,1/2), the image 2x ranges through every y[0,1), with inverse x=y/2. Thus the forward image has measure one although the source has measure 1/2. 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].

1.1F1
ExampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-13Open item page →

Base-three cylinders and their preimages

Example

Assume countable choice. For D3(x)={3x}, one has D31[0,1/3)=[0,1/9)[1/3,4/9)[2/3,7/9), of measure 1/3. With In,k=[k/3n,(k+1)/3n), D3(I2,3a+c)=I1,c for a,c{0,1,2}: applying D3 deletes the first ternary digit.

Facts & Assumptions

[F1]

On the base-three branch I1,a the map is 3xa, and the intervals use half-open endpoints. Integer-base maps and b-adic circle intervals.

[F2]

Integer-base maps preserve Lebesgue probability under countable choice. Integer-base circle maps preserve Lebesgue measure.

Verification

Given: Assume countable choice. For D3(x)={3x}, one has D31[0,1/3)=[0,1/9)[1/3,4/9)[2/3,7/9), of measure 1/3. With In,k=[k/3n,(k+1)/3n), D3(I2,3a+c)=I1,c for a,c{0,1,2}: applying D3 deletes the first ternary digit.

1.1

For x[a/3,(a+1)/3) with a=0,1,2, [F1] gives D3x=3xa. The condition 03xa<1/3 is equivalent to a/3x<a/3+1/9. Substitution of the three values of a gives exactly the three stated disjoint intervals. Their lengths add to 3(1/9)=1/3, as required by [F2].

F1F2
2.1

The interval I2,3a+c=[a/3+c/9,a/3+(c+1)/9) lies in branch a. Its affine image under 3xa is [c/3,(c+1)/3)=I1,c. Surjectivity onto that interval is explicit: for yI1,c use x=(y+a)/3, which lies in I2,3a+c. The included left and excluded right endpoints are preserved by this increasing affine map, including a=c=2 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].

1.1F1F2
ExampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-13Open item page →

Fair-coin cylinder masses and separated blocks

Example

Assume countable choice. Index binary sequences by 0,1,2,, and let [a0ar1] prescribe the first r coordinates. For fair-coin probability p, p([0])=1/2, p([01])=1/4, p([101])=1/8, and p([01]σ3[10])=1/16.

Facts & Assumptions

[F1]

A cylinder prescribing k distinct coordinates has fair-coin mass 2k. Fair-coin measure on binary sequences.

[F2]

The left shift moves coordinate j+1 into position j. The fair-coin one-sided shift preserves measure and is mixing.

Verification

Given: Assume countable choice. Index binary sequences by 0,1,2,, and let [a0ar1] prescribe the first r coordinates. For fair-coin probability p, p([0])=1/2, p([01])=1/4, p([101])=1/8, and p([01]σ3[10])=1/16.

1.1

The prefix [0] prescribes the single value x0=0, so [F1] gives 21=1/2. The prefix [01] prescribes x0=0,x1=1, so its mass is 22=1/4. The prefix [101] prescribes x0=1,x1=0,x2=1, giving 23=1/8. Repeated symbols do not reduce the number of distinct prescribed coordinates.

F1
2.1

By [F2], membership in σ3[10] prescribes x3=1,x4=0. Intersecting with [01] therefore prescribes exactly coordinates 0,1,3,4, with respective values 0,1,1,0. Coordinate 2 and all later coordinates remain free. The cylinder mass is 24=1/16 by [F1]. Equivalently this intersection is the disjoint union [01010][01110], whose masses sum to 2(1/32)=1/16. Countable choice is inherited from the measure construction in [F1], not from the finite coordinate count.

1.1F1F2
ExampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-13Open item page →

Recurrence to a dyadic interval under doubling

Example

Assume countable choice. For Lebesgue doubling and E=[0,1/4), almost every xE has DnxE for infinitely many positive integers n. The points of E returning at time one form [0,1/8), of measure 1/8.

Facts & Assumptions

[F1]

Finite measure preservation implies infinitely many positive returns for almost every point of a measurable set. Poincare recurrence for finite measure-preserving systems.

[F2]

Doubling preserves Lebesgue probability on the circle and its completion. Doubling preserves Lebesgue measure.

Verification

Given: Assume countable choice. For Lebesgue doubling and E=[0,1/4), almost every xE has DnxE for infinitely many positive integers n. The points of E returning at time one form [0,1/8), of measure 1/8.

1.1

The set E is Borel, with λ(E)=1/4, and [F2] gives a measure-preserving system of total mass one. Applying [F1] with exactly this E proves the stated almost-everywhere infinitely-many-positive-returns conclusion. Countable choice enters through [F2]; the recurrence theorem itself needs no choice axiom.

F1F2
2.1

The two inverse branches give D1E=[0,1/8)[1/2,5/8). Intersecting with E leaves [0,1/8), whose measure is 1/8. This is the first-return-one set because there is no smaller positive time. Return times need not all be one: 1/5E has successive images 2/5,4/5,3/5,1/5, 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.

1.1F2
ExampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-13Open item page →

Kac mean return to a half-circle under irrational rotation

Example

Assume countable choice. Let α be irrational, let Rα act on the Lebesgue circle, and put E=[0,1/2]. Its first positive return time satisfies ErEdλ=1. On the recurrent core E with normalized restricted probability λE, the mean return time is ErEdλE=2.

Facts & Assumptions

[F1]

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.

[F2]

Irrational rotations are ergodic for Lebesgue probability. Circle rotation is ergodic for Lebesgue measure exactly at irrational angles.

Verification

Given: Assume countable choice. Let α be irrational, let Rα act on the Lebesgue circle, and put E=[0,1/2]. Its first positive return time satisfies ErEdλ=1. On the recurrent core E with normalized restricted probability λE, the mean return time is ErEdλE=2.

1.1

The set E is Borel and is the disjoint union of [0,1/2) and {1/2}. The first has length 1/2 and the second is null by [F3], so λ(E)=1/2>0. By [F2] irrationality gives ergodicity of the Lebesgue probability system. All hypotheses of [F1] hold; applying its first conclusion yields ErEdλ=1. This uses the return time to the closed set E as stated, so no unproved comparison between return times for different endpoint conventions is involved.

F1F2F3
2.1

The recurrent core has restricted mass λ(E)=λ(E)=1/2 in [F1], and normalization divides restricted measure by 1/2. The second conclusion of [F1] therefore gives ErEdλE=1/(1/2)=2. 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].

1.1F1F2F3
CounterexampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-13Open item page →

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 E={0} satisfies λ(D1EE)=0, but D1EE.

Facts & Assumptions

[F1]

Doubling preserves Lebesgue probability. Doubling preserves Lebesgue measure.

[F2]

Strict invariance is set equality, whereas mod-null invariance is null symmetric difference. Strict and mod-null invariant sigma-algebras.

[F3]

Singletons are measurable and null under countable choice. Every at most countable subset of Rn is Lebesgue null; in particular λ1(Q)=0.

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 E={0} satisfies λ(D1EE)=0, but D1EE.

1.1

For 0x<1, the equation D(x)=0 means 2x is an integer. The only possibilities are 2x=0 or 2x=1, giving D1{0}={0,1/2}. Its symmetric difference with E={0} is exactly {1/2}, a null measurable set by [F3]. Thus E is invariant modulo null sets in the probability system of [F1], by [F2].

F1F2F3
2.1

The point 1/2 belongs to D1E and not to E, so the sets are not equal and E 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].

1.1F1F2F3
CounterexampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-13Open item page →

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 λ and for δ0, but not for μ=12δ0+14δ1/3+14δ2/3.

Facts & Assumptions

[F1]

Doubling is ergodic for Lebesgue probability under countable choice. Doubling is ergodic for Lebesgue measure.

[F2]

Ergodicity for a probability means every strict invariant measurable set has measure zero or one. Ergodicity relative to an invariant measure.

[F3]

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 λ and for δ0, but not for μ=12δ0+14δ1/3+14δ2/3.

1.1

The circle map D(x)={2x} fixes zero and exchanges 1/3 with 2/3. Thus δ0(D1E)=1E(D0)=1E(0)=δ0(E) for every Borel E. Every Borel set has δ0-measure either zero or one, so in particular every strictly invariant Borel set does; [F2] proves ergodicity for δ0. Ergodicity for λ is [F1].

F1F2F3
2.1

The finite weighted sum μ is a Borel probability by [F3] and the finite-sum interchange with nonnegative series. Its inverse-image mass is 121E(0)+141E(2/3)+141E(1/3)=μ(E), so it too is invariant. Let Z=n0(Dn)1{0}. Continuity of the iterates makes this Borel. Since zero is fixed, x eventually reaches zero exactly when Dx does; hence D1Z=Z. Zero belongs to Z and neither point of the two-cycle does, so μ(Z)=1/2. 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].

1.1F1F2F3
CounterexampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-13Open item page →

Irrational rotation is ergodic but not weakly mixing

Statement refuted

Assume countable choice. An irrational rotation Rα of the Lebesgue circle is ergodic but not weakly mixing. The single function f(x)=e2πix has mean zero, and its centered absolute self-correlation equals one at every nonnegative iterate.

Facts & Assumptions

[F1]

Irrational rotations are ergodic for Lebesgue probability. Circle rotation is ergodic for Lebesgue measure exactly at irrational angles.

[F2]

Weak mixing requires absolute Cesaro convergence to zero of every centered complex L2 correlation. Mixing correlations extend to L2 functions.

[F5]

Sine and cosine are differentiable, hence continuous on the real line. The derivatives of sine and cosine are cosine and minus sine.

[F6]

Rotation by 1/2 preserves the same Lebesgue probability. Circle rotations preserve Lebesgue measure.

[F7]

Integrable complex functions have unchanged integrals under measure-preserving composition. Integral invariance under measure-preserving maps.

Counterexample

Given: Assume countable choice. An irrational rotation Rα of the Lebesgue circle is ergodic but not weakly mixing. The single function f(x)=e2πix has mean zero, and its centered absolute self-correlation equals one at every nonnegative iterate.

1.1

By [F3] and [F4], e2πi=(eπi)2=1, and the same holds for every integer multiple of 2πi by multiplication and inversion. Thus f(x)=e2πix is well defined across the circle cut. By the Cartesian formula [F4], it equals cos(2πx)+isin(2πx) and is continuous by [F5] (the limit from below at 1 equals its value at 0), has f=1 by [F4], and belongs to both L1(λ) and L2(λ) because the circle has mass one. The addition law gives fR1/2=f. By [F6] and [F7], if m=fdλ then m=fR1/2dλ=m, so m=0.

F3F4F5F6F7
2.1

For every n0, the addition law and integer-period identity give f(Rαnx)=e2πinαf(x). Hence (fRαn)fdλ=e2πinαf2dλ=e2πinα. The centered correlation of [F2] is the same because the mean is zero. Its modulus is one by [F4], so for every N1, N1n=0N1Cn(f,f)=1. 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 L2 correlation averages in [F2] is needed. No Fourier-series completeness or spectral theorem is used.

1.1F1F2F3F4F6
CounterexampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-13Open item page →

Kac normalization needs ergodicity

Statement refuted

Assume countable choice. Removing ergodicity from Kac’s probability normalization is invalid. For the identity T on ([0,1],B([0,1]),λ) and E=[0,1/2], every point of E has rE=1, but ErEdλ=1/2, not one. The normalized return mean is one, not 1/λ(E)=2.

Facts & Assumptions

[F1]

The return time is the least positive return time, with infinity when there is none. First-return times and induced transformations.

[F2]

For an ergodic probability-preserving system and a positive-measure set E, Kac's theorem gives ErEdμ=1 and normalized mean 1/μ(E). Kac return-time formula without invertibility.

[F4]

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 T on ([0,1],B([0,1]),λ) and E=[0,1/2], every point of E has rE=1, but ErEdλ=1/2, not one. The normalized return mean is one, not 1/λ(E)=2.

1.1

By [F3] the restricted Lebesgue measure has λ([0,1])=1 and λ(E)=1/2. The identity is measurable and satisfies T1A=A for every Borel A, so it preserves this probability. In particular E is strictly invariant of measure 1/2, and [F4] shows that the system is not ergodic. Countable choice is inherited from the Lebesgue measure in [F3].

F3F4
2.1

For each xE and each positive integer n, Tnx=xE. Thus the least positive return time in [F1] is 1 and the infinitely-returning core is all of E. The integral of the constant one over E is λ(E)=1/2. 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 1/(1/2)=2 afterwards. All endpoints return as well, so no exceptional-point convention is involved.

1.1F1F2
ExampleConstruction: AI-adaptedVerification: AI-adaptedjudge pass (gpt-5.6-terra)audited 2026-09-13Open item page →

The Gauss map preserves Gauss measure

Example

Assume countable choice. On X=[0,1) put G(0)=0 and G(x)={1/x} for x>0. The Borel probability μ with density h(x)=1/[log(2)(1+x)] relative to Lebesgue measure is G-invariant. The same map preserves its completion. This example proves measure preservation only.

Facts & Assumptions

[F1]

A nonnegative measurable density defines a measure by integration over sets. The indefinite integral of a nonnegative measurable function is a measure.

[F2]

The logarithm has derivative 1/x on the positive reals. The natural logarithm has derivative 1/x and equals the integral from 1 to x of 1/t.

[F3]

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.

[F4]

Continuous functions on closed bounded intervals are bounded and Riemann integrable. A continuous function on [a,b] is Riemann integrable, by Heine-Cantor and Riemann's criterion.

[F5]

The Riemann integral of an integrable derivative is the primitive difference, including one-sided endpoint derivatives. The second fundamental theorem: if G is differentiable on [a,b] with G=f and f is integrable, then abf=G(b)G(a).

[F6]

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.

[F7]

At most countable sets are Lebesgue measurable and null under countable choice. Every at most countable subset of Rn is Lebesgue null; in particular λ1(Q)=0.

[F8]

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.

[F9]

A measure-preserving transformation extends to the completed measure space. Compositions, iterates and completions preserve invariance.

[F11]

The rationals are countable. Q is countably infinite.

Verification

Given: Assume countable choice. On X=[0,1) put G(0)=0 and G(x)={1/x} for x>0. The Borel probability μ with density h(x)=1/[log(2)(1+x)] relative to Lebesgue measure is G-invariant. The same map preserves its completion. This example proves measure preservation only.

1.1

By [F3], log2>log1=0, so h is positive, bounded by 1/log2, and continuous on [0,1]. By [F4] it is Riemann integrable on every closed subinterval. The derivative of log(1+x) is 1/(1+x) by [F2], using the translated difference quotient, also one-sided at subinterval endpoints. Thus [F5] and [F6] yield [a,b]hdλ=[log(1+b)log(1+a)]/log2 for 0a<b1. Singletons and countable sets have zero density integral because they are null by [F7] and h is bounded. Consequently endpoints do not change this interval value. By [F1] the density defines a Borel measure, and the value with a=0,b=1 is one; removing the endpoint 1 does not change it.

F1F2F3F4F5F6F7
1.2

The Borel sets Jn=(1/(n+1),1/n]X, n1, partition (0,1). On Jn, G(x)=1/xn, and on the singleton {0} it is zero. Each branch is the restriction of a continuous real function and takes values in [0,1), so for every open subset of X its inverse image is a countable union of Borel branch inverse images and possibly {0}. This proves Borel measurability. For 0<s<1, the exact inverse image is G1[0,s]={0}n1([1/(n+s),1/n]X). The displayed intervals are pairwise disjoint because 1/(n+s)>1/(n+1). The only endpoint outside X is 1 when n=1.

1.1
2.1

Using the interval integral of step 1.1 and countable additivity, μ(G1[0,s]) is 1/log2 times the sum over n1 of log(1+1/n)log(1+1/(n+s)). The quotient law [F3] and the identity (1+1/n)/(1+1/(n+s))=(1+s/n)/(1+s/(n+1)) rewrite the partial sum through M as log(1+s)log(1+s/(M+1)). All original summands are nonnegative. Continuity of log at 1 gives the limit log(1+s), so μ(G1[0,s])=log(1+s)/log2=μ([0,s]). For s=0, the preimage is {0}{1/n:n2}, an explicitly enumerated countable null set, and both masses are zero. The full space X also has equal inverse-image mass one.

1.11.2F3F7
3.1

The family consisting of X, the empty set, and all [0,s] with 0s<1 is a pi-system. It generates the Borel sets of X: complements give (s,1), and increasing unions of initial closed intervals give [0,b); 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 G 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].

1.11.22.1F6F7F8F9F10F11
4.1

The corresponding inverse-branch density calculation can also be seen directly. On 0<y<1, the inverse branch is ηn(y)=1/(n+y), with ηn(y)=1/(n+y)2. Hence h(ηn(y))ηn(y)=1/[log2(n+y)(n+y+1)]. The algebraic identity 1/[(n+y)(n+y+1)]=1/(n+y)1/(n+y+1) gives the partial sum [1/(1+y)1/(M+1+y)]/log2, tending to h(y). 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 y=0.

1.11.22.13.1

Sources