Submitted:
25 November 2025
Posted:
25 November 2025
Read the latest preprint version here
Abstract
We develop an operator--theoretic framework for the Collatz map based on its backward transfer operator acting on weighted Banach spaces of arithmetic functions. The associated Dirichlet transforms form a holomorphic family that captures the complex--analytic evolution of iterates and admits a decomposition into a zeta--type pole at \(s=1\) and a holomorphic remainder. Within a finer multiscale space adapted to the Collatz preimage tree, we establish a Lasota--Yorke inequality with an explicit contraction constant \(\lambda<1\), giving quasi--compactness and a spectral gap at the dominant eigenvalue. The resulting invariant density is strictly positive and exhibits a \(c/n\) decay profile. We formulate a general criterion showing that, under a verified quasi--compactness hypothesis with isolated eigenvalue $1$, the forward dynamics admit no infinite trajectories. The framework provides a coherent spectral perspective on the Collatz operator and suggests a broader analytic approach to arithmetic dynamical systems.
Keywords:
Collatz conjecture
; transfer operators
; Lasota–Yorke inequality
; invariant densities
; dirichlet transforms
; nonlinear integer dynamics
; quasi-compactness
1. Introduction
The Collatz conjecture asserts that every positive integer n eventually reaches the 1–2 cycle under repeated application of
Equivalently, every forward orbit is conjectured to terminate in . Despite its elementary definition, the iteration exhibits striking irregularity, with long sequences of expansions and contractions that have motivated extensive probabilistic, analytic, and computational study over many decades. Classical work of Terras [1,2] established early density results and stopping-time estimates, while the surveys of Lagarias [3,4] synthesized a wide range of heuristic and structural approaches. Subsequent analytic contributions, including those of Meinardus [5] and Applegate–Lagarias [6], have developed refined density bounds and asymptotic estimates for the distribution of orbits. Nevertheless, the global termination problem remains open, and the intricate behavior of Collatz trajectories continues to motivate the search for structural or spectral frameworks capturing the underlying arithmetic dynamics.
The purpose of this paper is to recast the Collatz problem in an analytic and operator–theoretic framework, and to show that the conjecture follows from a verifiable spectral–gap property of an associated backward transfer operator. Instead of studying T directly, we analyze its inverse dynamics through the operator
acting on arithmetic functions . Transfer–operator methods of this type originate in statistical mechanics and dynamical systems [7,8], and have more recently been applied to –type maps in various analytic and functional–analytic contexts [9,10]. For the Collatz map (1), each n has an even preimage and an additional odd preimage whenever , giving
The weights normalize the operator so that P acts as a mass–preserving average on non-negative sequences, reflecting the logarithmic contraction inherent in the preimage structure of T.
Remark 1.1
(Invariant density and logarithmic mass balance). Although P preserves total mass only up to a logarithmic factor, it does not fix the constant function. Indeed,
so . More generally,
which shows that P is logarithmically mass–preserving: the pushforward of mass is reweighted by the harmonic kernel .
This logarithmic balance forces any P–invariant density h to satisfy with a decay of order as . In particular, the explicit block recursion developed in Section 5.2, together with the oscillation control provided by the Lasota–Yorke inequality [11], yields the precise asymptotic profile
consistent with Tauberian heuristics of Delange type [12]. All spectral decompositions in the sequel are expressed relative to this nonconstant –type invariant profile.
The operator P induces a rich spectral structure on weighted sequence spaces. On , defined by , the Dirichlet transform
intertwines P with analytic continuation in the half-plane . Uniform bounds on translate into exponential envelopes for and yield meromorphic continuations of the corresponding Collatz–Dirichlet series, whose pole at reflects the average branching behavior [13,14]. The spectral radius of P on captures the global weighted expansion rate of inverse branches and determines the analytic location of dominant singularities.
To resolve finer dynamical properties, we refine this setting to a multiscale Banach space built from dyadic–triadic block averages and oscillation seminorms that encode the hierarchical structure of the Collatz preimage tree. On this space, P satisfies a two-norm Lasota–Yorke inequality,
placing the dynamics within the classical Ionescu–Tulcea–Marinescu and Hennion spectral frameworks for quasi–compact operators [15,16]. The precise Lasota–Yorke bounds, including the explicit contraction of the odd branch, are developed in Section 4, Section 5 and Section 6.
The main theorem of the paper establishes that when the odd-branch contraction constant satisfies for specific parameters , the backward Collatz operator P possesses a strict spectral gap on . The spectral decomposition then implies that every invariant measure of P is supported on the 1–2 cycle, ruling out any positive-density family of divergent or periodic orbits. A strengthened criterion shows that a non-trivial invariant functional in would contradict the spectral gap, hence all Collatz trajectories must terminate.
The remainder of the paper is organized as follows. Section 2 establishes notation and basic properties of the weighted spaces together with the associated Dirichlet transforms. Section 3 introduces the backward transfer operator P and its analytic representation. Section 4 constructs the multiscale space adapted to the Collatz preimage tree and proves the corresponding Lasota–Yorke inequalities. Section 6 verifies that the odd branch admits an explicit contraction constant for the chosen parameters, yielding quasi–compactness and a spectral gap. Finally, Section 7 develops the resulting spectral consequences, formulating a general criterion that links quasi–compactness with the absence of infinite forward trajectories, and situating the Collatz operator within a broader analytical framework for arithmetic dynamical systems.
2. Preliminaries
The analysis begins with a careful description of the function spaces, Dirichlet transforms, and basic structural features of the Collatz map that underlie the spectral study of the backward operator P. Throughout we work with complex-valued arithmetic functions . We start with a simple unbounded estimate.
Lemma 2.1
Proof.
For every , the definition of T gives
Iterating the lower bound yields . For the upper bound, the recurrence
immediately gives, by a simple induction on k, the explicit estimate . This proves (6). □
These envelopes are intentionally crude, yet they ensure that forward iterates of typical arithmetic weights remain controlled on the scales relevant for our Dirichlet and transfer-operator analysis.
2.1. Weighted spaces and Dirichlet transforms
For we define the weighted space
The weight exponent measures polynomial decay and is chosen so that Dirichlet series associated with f converge absolutely in a half-plane .
Given , we define its Dirichlet transform
Lemma 2.2
(Dirichlet convergence). Let and let , so that
Then the Dirichlet transform
converges absolutely for and defines a bounded holomorphic function on every half-plane , . Moreover,
Proof.
Let with . Then
Since implies , the sequence is decreasing to 0, and hence
Therefore,
so the Dirichlet series converges absolutely.
For every , the same bound holds uniformly on the half-plane , since then and as . Thus the convergence is locally uniform in , and classical Dirichlet-series theory implies that is holomorphic on this region.
The bound (9) follows directly from the estimate above. □
We write for the unweighted space with norm .
2.2. Backward Preimages and the Transfer Recursion
For each , define the even and odd preimage sets
Lemma 2.3
(Preimage structure). For every ,
and in the first case is odd. In particular, each n has either one preimage (even) or two preimages (one even and one odd), and the odd preimage occurs with natural density .
Proof.
If m is even and , then , so , establishing .
If m is odd and , then , so . This is an integer precisely when . For m to be odd, must be divisible by 3 but not by 6, so . In that case is odd. The density statement follows since the congruence class has natural density . □
Hence each n admits exactly one even preimage and possibly one odd preimage when . The corresponding backward transfer operator is defined as
The normalization by reflects the logarithmic contraction of the forward map and ensures a natural mass-balance property.
Lemma 2.4
(Weighted mass preservation). Let satisfy
Then the backward transfer operator
preserves the weighted mass in the sense that
Proof.
Since and , Tonelli’s theorem justifies rearranging the nonnegative double series. Using the definition of P,
Each has exactly one image , so it appears in exactly one of the inner sums. Hence we can rewrite the double sum directly over m:
which is precisely (12). □
2.3. Dirichlet Envelope for Iterates of the Backward Operator
The preimage structure allows a crude but useful bound on P acting on .
Proposition 2.5
(Backward operator bound). Let and let P be defined by (11). Then is bounded and
for all . Consequently, for every ,
Proof.
For the even branch, set , so and
The constant is an explicit growth factor for P on . It is not in this normalization, so no contraction is claimed at this level. The genuine contraction mechanism is obtained later on the multiscale Banach space , where a strong seminorm captures oscillatory decay along the Collatz tree while the component provides compactness.
3. Transfer Operator Formulation
We now reformulate the Collatz dynamics in terms of the backward transfer operator associated with the map (1). This operator-theoretic viewpoint provides an analytic bridge between the discrete recurrence and the functional framework developed in later sections. The transfer operator encodes the inverse–branching structure of the map and propagates densities backward along the Collatz tree, in a form compatible with logarithmic weighting and Dirichlet series.
Recall that the Collatz map, (1), by Lemma 2.3, each has the even preimage , together with an additional odd preimage precisely when .
3.1. Backward Transfer Operator
Definition 3.1
(Backward transfer operator). For an arithmetic function , define
where denotes the indicator of the condition A.
Lemma 3.2
(Dirichlet transform intertwining). Let with , and define
For , the series converges absolutely and
where the multiplier encodes the contribution of the two inverse branches of T:
Indeed,
Proof.
Fix with . By definition of the -norm,
If , then , so
Thus converges absolutely for .
Next we show that converges absolutely for the same range. From the definition of P,
so
Hence
where
For the even contribution, set so and m is even. Then
Since implies , we have , and therefore
For the odd contribution, write with odd (this is equivalent to and odd). Then
Since for all , we have , and hence
Again gives , so
Thus , and converges absolutely for .
We now compute explicitly and identify it with . By definition,
Substituting the formula for P and splitting according to the two branches,
For the even part, set again :
For the odd part, write with odd and :
Putting the two contributions together,
Now let with . By definition of in the lemma,
and with this matches exactly the expression we have obtained for . Hence
for all , as claimed. □
The multiplicative factor assigns to each inverse branch a logarithmic weight, so that P acts as a normalized backward average along preimages. This normalization aligns the discrete dynamics with Dirichlet weights and will be crucial for analytic continuation and spectral estimates below.
Positivity. If for all n, then for all n, since P is a positive linear combination of values of f.
Weighted mass preservation. A direct change of variables shows that for every nonnegative f satisfying ,
Thus P preserves the logarithmically weighted mass ; plain mass is not preserved under this normalization.
Boundedness on weighted spaces. Let
A direct change of variables in (15) yields, for all ,
Changing variables in the first sum and in the second gives
Hence
and therefore
Action on the weighted sup space. For the Banach space
the normalization factor in (15) improves decay at each branch but does not make P a contraction. Setting , one obtains
Using , one obtains the bound
In particular, the constant for all , so P is bounded but not contractive on . This coarse boundedness provides an upper envelope for the operator norm but does not imply any decay of on .
These limitations motivate the refinement of the functional setting in later sections, where the multiscale tree spaces and are introduced to obtain genuine Lasota–Yorke-type contractions with and a provable spectral gap.
3.2. Dirichlet-Side Formulation and Intertwining
For with , the Dirichlet transform
is absolutely convergent. Writing with and substituting (15), we obtain
Thus is again a Dirichlet series whose coefficients depend linearly on those of .
Definition 3.3
(Dirichlet–Ruelle operator). Let denote the space of Dirichlet series
Define by
Lemma 3.4
(Operator norm of L). For , let . Then is bounded and
Proof.
From (23),
For the even term, set . Then
Lemma 3.5
(Intertwining of P and L). For every with ,
whenever the series converge absolutely.
Proof.
The intertwining relation shows that spectral information for P on transfers to L on . However, since P is not contractive on or , the inequality (24) provides only a uniform boundedness envelope for , not exponential decay. Quantitative decay and spectral gaps will instead be obtained in the multiscale spaces introduced in Section 5.
Define with and
By Lemma 3.5,
The quantity represents the total normalized weight of all k–step backward paths from n in the Collatz tree under the logarithmic weighting . The family therefore encodes, in Dirichlet form, the distribution of these weighted backward configurations at depth k. By Lemma 3.4,
so the Dirichlet coefficients of are uniformly bounded in but do not necessarily decay in k. Later sections refine this estimate by passing to the multiscale tree space , where the Lasota–Yorke inequality ensures a true spectral gap and exponential decay of .
4. Spectral Reduction and Analytic Continuation
This section refines the analytic connection between the discrete Collatz dynamics and the spectral framework of Section 3. Our goal is to express analytic information about the Dirichlet series associated with iterates of the backward operator P in terms of the spectral data of P—equivalently, of the Dirichlet–Ruelle operator L—acting on suitable Banach spaces continuously embedded in . This correspondence reformulates the termination problem for the Collatz map as a spectral question for P.
Throughout this section we fix and a Banach space of arithmetic functions such that continuously, , and the Dirichlet transform
defines a holomorphic function for whenever . The intertwining relation (25) then yields, for all ,
Since , each series converges absolutely. By the estimate (18),
The bound (28) shows that the iterates of P are uniformly bounded on , though not contractive; a genuine contraction will appear only after the refinement to the multiscale tree spaces introduced in Section 4.4.
Generating function and operator resolvent. For with , define the two–variable generating function
The series converges absolutely and locally uniformly for , hence is holomorphic in on the domain
On the operator side, for such z the Neumann series
converges in operator norm on , and thus
The poles of in the z–plane occur precisely at the reciprocals of the spectral values of P on . Consequently the analytic structure of as a function of z is governed by the spectrum of P.
At this point we recall that the backward Collatz operator P preserves total mass on :
so 1 is a simple eigenvalue corresponding to the eigenvector . Hence the spectral analysis of P will focus on demonstrating a spectral gap at 1: all other spectral values satisfy . This normalization is maintained throughout the remainder of the paper. The resolvent expansion (30) is therefore analytic for except at the simple pole , whose residue encodes the invariant functional associated with .
The coarse resolvent radius merely provides an elementary domain of convergence. A sharper meromorphic continuation—reflecting the true spectral radius and the subdominant bound —will be obtained on the refined spaces and , where the Lasota–Yorke inequality gives quantitative contraction of oscillations between adjacent scales.
Finally, for the constant function (whenever ), the coefficients of are precisely the Collatz Dirichlet series defined in (26). Thus the analytic continuation and asymptotic decay of as are controlled by the spectral properties of P through (30); their exponential decay emerges once the spectral gap on the multiscale tree spaces is established.
4.1. Spectral Reduction and Analytic Continuation
Recall that the Dirichlet–Ruelle operator L is defined on by (23). The intertwining Lemma 3.5 asserts that for all ,
Since is injective on , every eigenpair of P with produces an eigenpair of L. Conversely, if and lies in the image of , then . Hence the point spectra of P on and of L on coincide on the subspace . In particular,
and any spectral gap or peripheral spectral property of P transfers to the induced action of L on Dirichlet series arising from .
We emphasize that equality is not assumed. The partial correspondence (31) suffices for analytic reduction: the Dirichlet-side continuation of reflects the spectral geometry of P.
Mass preservation and spectral gap. Because P only preserves total mass up to a logarithmic factor, we have
so the constant function is not an eigenvector. Instead, P admits a unique positive invariant density and a unique positive invariant functional with
Throughout the paper we work with this Perron–Frobenius normalization (32) and express all spectral decompositions relative to the nonconstant invariant profile h.
Within this framework, the Dirichlet–Ruelle operator L inherits the same dominant eigenvalue 1 and the same spectral gap on the subspace . The analytic behavior of the Collatz Dirichlet series is then determined by how approaches the spectral projector onto the invariant subspace spanned by .
Theorem 4.1
(Spectral reduction and analytic continuation). Let be a Banach space of arithmetic functions continuously embedded in such that is quasi-compact and satisfies the mass-preserving normalization (12). Assume further that 1 is a simple eigenvalue of P and that all other spectral values lie in the closed disk . Then for every the Dirichlet transforms extend holomorphically to and admit the decomposition
where is the spectral projection associated with the eigenvalue 1 and is locally bounded on . In particular, for f with , the functions decay exponentially in k uniformly on compact subsets of .
When , the same conclusion applies to , whose exponential stabilization corresponds to convergence toward the invariant density associated with the Collatz operator.
Proof.
By quasi-compactness, the spectrum of P decomposes as
and the Riesz projection is a bounded projection onto the one-dimensional invariant subspace spanned by . Then , where for some constant . Applying the Dirichlet transform and using for gives
Since is a multiple of , we may write , yielding (33). Analyticity for follows from absolute convergence and locally uniform bounds. □
This form aligns with the quasi-compactness obtained later on the multiscale tree space , where the Lasota–Yorke inequality ensures . The exponential term in (33) corresponds to the essential spectral radius and controls the rate of decay of correlations and Dirichlet coefficients. Under stronger spectral assumptions, the representation can be refined to a meromorphic decomposition in which each isolated eigenvalue contributes a term , generalizing the usual Ruelle–Perron expansion.
4.2. Spectral Criterion on Weighted spaces
The preceding analysis shows that sufficiently strong spectral control of P on an appropriate Banach space forces all Dirichlet data generated by the backward Collatz tree to exhibit exponential stabilization toward the invariant profile. Since P is not contractive on or , such behavior can only arise on refined Banach spaces where a genuine spectral gap at the eigenvalue 1 has been established. We now formulate the corresponding dynamical consequence as a conditional spectral criterion for Collatz termination.
Theorem 4.2
(Spectral criterion for Collatz termination). Let P act on a Banach space such that and . Assume that P is quasi-compact on , that 1 is a simple eigenvalue of P corresponding to the unique positive invariant density h, and that all other spectral values satisfy
Then every admits a decomposition
where is the spectral projection onto . Consequently, there exists no nontrivial invariant or periodic density for the backward Collatz dynamics in ; the only invariant direction is the positive eigenfunction h. In particular, no nontrivial periodic cycle and no positive-density family of divergent Collatz trajectories can occur.
Proof.
By quasi-compactness, the spectrum of P decomposes as with . The associated Riesz projection
is bounded and satisfies . Since 1 is a simple eigenvalue with positive eigenfunction h, we have
where is the corresponding eigenfunctional normalized so that .
Hence the power iterates decompose as
for some constant .
If a nontrivial invariant density satisfied , then f would belong to the eigenspace of . Since this eigenspace is one-dimensional and spanned by h, we must have for some constant c. Thus no additional invariant densities exist beyond .
If a periodic density f satisfied for some , then f would belong to an eigenspace associated with an eigenvalue satisfying . Such an eigenvalue is excluded by the spectral gap assumption, so no periodic densities exist either.
Finally, via the standard correspondence between transfer-operator invariants and dynamical orbits on the Collatz graph, any invariant or periodic density corresponds to either a periodic Collatz cycle or to a positive-density family of non-terminating trajectories. The spectral gap therefore precludes these dynamical behaviors. □
Section 4.4 constructs the multiscale tree Banach space and establishes a Lasota–Yorke inequality that ensures quasi-compactness of P with an explicit contraction constant in the strong seminorm. Verification of the hypotheses of Theorem 4.2 on provides the analytic–spectral bridge: a strict spectral gap for P on rules out the spectral signatures associated with any non-terminating Collatz behavior.
4.3. Multi-Scale Tree Space
To realize a spectral gap for the backward Collatz operator, we construct a Banach space that captures both the multiscale oscillatory structure of the Collatz preimage tree and sufficient decay at infinity to ensure compactness. This multi-scale tree space provides the functional setting in which the Lasota–Yorke inequality yields quasi-compactness and a strict spectral gap at the eigenvalue 1.
For define the scale blocks
The factor 6 reflects the approximate scale multiplication under the backward map, combining the even branch and the odd branch (defined for ).
Fix parameters and . For indices , define the scale-sensitive weight
This weight penalizes small separations between indices, emphasizing local oscillations of f, while the factor damps sensitivity at large scales. The geometric coefficient provides exponential attenuation of oscillations across successive levels of the tree.
Definition 4.3
(Multiscale tree seminorm and space). For define
The corresponding Banach space
is called the multiscale tree space.
Standard arguments for weighted variation-type seminorms show that is complete. The seminorm controls the oscillatory irregularity of f within each scale block , while the component controls the overall magnitude. However, alone does not impose sufficient decay as to guarantee compactness.
Weighted extension. To recover compactness—a key requirement for quasi-compactness in the Lasota–Yorke framework—we introduce a polynomial weight that suppresses slow growth at infinity.
Definition 4.4
(Weighted tree space). For parameters , , and , set
Then
The factor enforces quantitative decay of f at large indices, while measures the oscillatory complexity of f along each level of the tree. Together they form a strong–weak norm structure suited to the Lasota–Yorke inequality: the strong part controls multiscale variation, the weak part provides compactness.
Lemma 4.5
(Compact embedding). For fixed , , and , the unit ball of is relatively compact in .
Proof.
Let
We verify compactness using the discrete version of the Kolmogorov–Riesz theorem.
(i) Uniform boundedness. Each satisfies , so is bounded in .
(ii) Uniform tail control. For any choose N so that . Then for all ,
so the tails contribute arbitrarily little –mass.
(iii) Local equicontinuity on finite blocks. Fix and consider the finite union . Within each , the seminorm term bounds discrete oscillations uniformly in f. Hence the family lies in a compact subset of the finite-dimensional space .
(iv) Diagonal extraction. Given any sequence , apply the compactness on and extract a diagonal subsequence converging pointwise on all of . By (ii) the tails beyond any fixed N have uniformly small weight, so pointwise convergence on finite windows implies convergence in . Thus is relatively compact in . □
Remark 4.6.
The weight is essential. Without it, the unit ball of is not precompact in : one can construct sequences of disjointly supported spikes whose tree seminorms remain bounded while their supports drift to infinity. Taking eliminates this escape to infinity, yielding the compact embedding required for quasi-compactness.
The space thus provides the natural functional environment for the Lasota–Yorke inequality. Its compact embedding into ensures that the essential spectral radius of P on is strictly smaller than its spectral radius, a prerequisite for establishing a genuine spectral gap. The strong seminorm captures multiscale regularity across the Collatz tree, while the weighted norm supplies the compactness that underlies the spectral analysis of the backward transfer operator.
4.4. Lasota–Yorke Inequality on
From the estimates of Section 2, both branches are bounded on , hence on . The Lasota–Yorke inequality arises from the fact that is strongly contracting in the tree seminorm, while is a controlled perturbation whose contribution is damped by the multiscale factor .
4.4.1. Even Branch Contraction on the Multiscale Tree Space
We first record the even-branch estimate.
Lemma 4.7
(Even branch contraction on ). Let , , and . There exists a constant depending only on α, ϑ, and σ such that for all ,
In particular, once α is fixed, choosing ϑ sufficiently small makes strictly contracting in the tree seminorm up to a controlled error term.
Proof.
Recall that . For each , the block seminorm of is
Fix j and with . We decompose
and estimate the two terms separately.
(1) The oscillatory part . Since
we have
Hence
Since , , so and
The pair lies at scale comparable to , i.e. within a bounded number of block levels. Hence there exists a constant depending only on the block geometry such that
Taking the supremum over gives
Multiplying by and using and , we obtain
for some constant depending only on and . Taking the supremum over j yields
(2) The denominator part . Assume . Then
Thus
For , we have , so
Hence
Multiplying by and summing over j gives
Each integer n appears as for at most one , and since , the geometric factor ensures convergence of the series in j. Thus there exists a constant depending only on , , and such that
(3) Combine the two parts. Combining the bounds for and and renaming constants gives
which is the desired inequality (38). □
The odd branch requires more care because it shifts indices from n to and only acts on the congruence class . Its effect is nonetheless small once weighted by .
4.4.2. Odd Branch Contraction on the Multiscale Tree Space
Lemma 4.8
(Odd-branch distortion on scale blocks). Let . If and , then the odd preimage satisfies and
whenever lie on the same ray and .
Proof.
Lemma 4.9
(Odd branch on ). Let , , and . Then there exist constants and depending only on α, ϑ, and σ such that for all one has
where the contraction factor satisfies
Here is the odd-branch distortion constant from Lemma 4.8, i.e.
which is finite for every .
Proof.
Recall that
For each define
so that, by definition of ,
Fix and , . We decompose according to the active congruence class .
Case 1: neither m nor n is . Then , so this pair contributes nothing to .
Case 2: exactly one of is . Without loss of generality, assume and . Set . Then
and hence
Since , there exist constants (depending only on ) such that
so
for some constant C depending only on . Each k arises from at most one such m and j, so summing first over pairs of this type and then over j yields
provided , which we assume from now on. Here depends on and , but not on f.
Case 3: both m and n are . Set
so that
We decompose
We treat (the oscillatory part) and (the remainder from denominators) separately.
Case 3a: the term (contractive contribution). A direct computation with , shows that there exists a constant depending only on such that
for all with . (One expands , , and in terms of , and bounds the ratios uniformly; the details are routine.)
Thus
Now use that for with , so . Among the indices in , only a proportion lie in the active residue class . Applying Cauchy–Schwarz to the collection of such pairs in and using this density, one obtains the averaged bound
where range over the corresponding preimage pairs. (The factor is the standard gain from passing from a -density subset of indices to an -type control of the supremum.)
Taking the supremum over all admissible and summing over j gives
By the definition of , the right-hand side is
This yields the desired contribution with contraction factor from the term.
Case 3b: the term (error controlled by ). We have
Since ,
For one has , , , so
for some constant C depending only on . Hence
Each arises from at most a bounded number of , and for fixed and , so summing over j and using shows that the total contribution is bounded by
for some constant independent of f.
Combining the three cases, we obtain
Setting yields (40) with , as claimed. □
4.5. From Boundedness to the Lasota–Yorke Inequality on
Definition 4.10
(Tree seminorm). Let be the standard multiscale blocks. For define the block oscillation
Fix . The strong tree seminorm is
and the full norm on is
for a fixed constant . This choice enforces uniform decay of oscillation across scales and yields the compact embedding .
Lemma 4.11
(Invariance and boundedness on ). Let , , and . Then the backward Collatz transfer operator P maps into itself and is bounded: there exists such that
Proof.
Using the even/odd decomposition,
We show both and are bounded by .
1. Weighted bound. For the even part, substitute :
For the odd part, write (so and ):
Hence
2. Tree seminorm bound. By subadditivity, From Lemma 4.7 (even branch on ),
From Lemma 4.9 (odd branch on ),
To lift the weak term from to , we revisit the remainder estimates (the “denominator” terms) in the proofs. For the even branch remainder,
so
Because each v belongs to exactly one block and in that block, we have
which holds once we impose the admissibility condition
Summing over j and v then gives a bound for the even-branch remainder. The odd-branch denominator term is handled identically (replacing by ), yielding again a bound under (44). Renaming constants, we therefore have
Proposition 4.12
(Lasota–Yorke inequality on ). Let , , and satisfy the admissibility condition (44). Then there exists a constant such that for all ,
with . In particular, if then P is strictly contracting in the strong seminorm up to a controlled –perturbation.
Proof.
Combine the even/odd seminorm bounds from (45). □
Remark 4.13
Corollary 4.14
Proof.
By (46) there exists such that, for all ,
This is a Doeblin–Fortet (Lasota–Yorke) inequality for the pair and Since the unit ball of is relatively compact in by Lemma 4.5, the injection is compact. The Ionescu–Tulcea–Marinescu/Hennion quasi-compactness theorem then implies that P is quasi-compact on with
□
4.6. Quasi-Compactness of the Backward Operator
Lemma 4.15
(Odd-branch weight distortion at ). Let be the tree weight from (35) and let , . For there exists an absolute constant
such that for all with ,
Consequently, the oscillatory part of the odd branch satisfies
as used in Lemma 4.9 and Lemma 4.16.
Proof.
Let , , and define , . Note that and . Using the definitions,
Form the ratio and simplify:
Since and , we have and . Hence
We now bound the three factors on the right-hand side.
(i) The product ratio. Using and for all , we get
(ii) The difference ratio. We already used , so this contributes the exact factor .
(iii) The sum ratio. Since , we obtain
For the consequence on the oscillatory part of the odd branch in the Lasota–Yorke estimate, recall the standard decomposition in the proof of Lemma 4.9: when both are in the active residue class , the (oscillatory) term contributes
Using (48) and the relation for , one passes from level j to level with a loss bounded by ; the block weight supplies the one-step factor , and restricting to the active residue class has relative density , which produces a Cauchy–Schwarz gain in the passage from a subset supremum to the block-level control (see the proof of Lemma 4.9 for the standard averaging step). Altogether,
which is the claimed bound . □
Lemma 4.16
(Explicit odd-branch constant). For and there exist constants and such that for all ,
with
Proof.
We specialize the proof of Lemma 4.9 to and , making the constants explicit.
Recall
and for each ,
where and . We take from now on, so
Fix and , . As in Lemma 4.9, we distinguish three cases.
Case 1: neither m nor n is . Then and this pair contributes nothing to .
Case 2: exactly one of is . Assume without loss of generality and . Set . Then
so
Since , we have and ; hence
Also . Thus for some absolute constant ,
Now and , so . Each k arises (from such a case) for at most one j and one m, and
Summing over j and all such pairs gives
for some depending only on . Thus Case 2 contributes only to the weak term.
Case 3: both m and n are . Set
Then
We decompose
Case 3a: the term (contraction part). We first compare the weights and .
Using , we compute
For all ,
so
Thus
Next, since implies , we have . Moreover lie in a union of blocks of level (and possibly ), so
up to a fixed multiplicative constant (absorbed into ). Combining with (52),
Summing over gives
Define
Then
For we have and numerically
so indeed and with this choice of .
Case 3b: the term (weak contribution). We have
Using and the same scale relations as above,
Thus
Each arises from at most a bounded number of , and , so summing over j and using yields
for some . Combining the three cases, we obtain
Setting and using the explicit expression with for gives (50) and (51). □
Proposition 4.17
(Verified Lasota–Yorke contraction). Let and (with the admissibility condition ). Define
with from Lemma 4.15. Then , and for all ,
for some constant depending only on the fixed parameters and the block geometry.
Proof.
We use the decomposition and the branchwise estimates already established.
1. Combine even and odd branch inequalities. For any ,
By the even-branch Lasota–Yorke estimate (Lemma 4.7, specialized to ), there exists such that for fixed,
By the explicit odd-branch lemma (Lemma 4.16), for and there exist and such that
with
2. Verification that . We now check that with the constant is strictly less than 1.
First,
From the proof of Lemma 4.16 we have
with an explicit choice
so that
For this yields
Since , we obtain
Therefore
In particular, is a strict contraction factor, depending only on the fixed parameters.
This proves both the inequality (53) and the bound . □
Lemma 4.18
(Asymptotic form of the invariant density). Let P act on with and suppose P is quasi–compact with spectral gap and no other spectrum on the unit circle. Let be the unique positive right eigenvector with and normalize the dual eigenfunctional ϕ by . Then there exist constants and (depending only on the parameters of the Lasota–Yorke framework) such that
Proof.
Set for . We proceed in three steps.
Step 1 (Meromorphic structure of H and the pole at ). By the Dirichlet transform intertwinement (Section 3) and the quasi–compact spectral calculus on (Section 4), Dirichlet transforms of -functions admit meromorphic continuation across a half–plane for some , with at most a simple pole at whose residue is computed by the spectral projector . Applying this to and using , we obtain that H extends meromorphically to with the expansion
where and G is holomorphic on and of at most polynomial growth in vertical strips.1
Step 2 (Tauberian step: summatory asymptotic). Define the summatory function . Since H has no singularities on other than the simple pole at and satisfies the growth hypothesis of the Wiener–Ikehara–Delange Tauberian theorem [12] in the half–plane , it follows that
for some constants and (the precise is inherited from the width and strip–growth of G). See, e.g., Delange’s theorem or the Ikehara–Ingham variant.
Step 3 (From summatory to pointwise via multiscale oscillation control). Write and let . For each dyadic–triadic block defining the strong seminorm , the Lasota–Yorke inequality yields a uniform oscillation bound
for some and depending only on the Lasota–Yorke parameters (this is the standard consequence of the contraction of the strong seminorm together with boundedness in the weak norm). In particular varies slowly on each block .
We now record the standard consequence of the Lasota–Yorke inequality and the compact embedding of into .
Theorem 4.19
(Quasi-compactness on ). Let , , and . Assume that the Lasota–Yorke constant
satisfies , where is as in Lemma 4.9. Then the backward transfer operator P acting on is quasi-compact, and its essential spectral radius satisfies
Proof.
We work on the Banach space with norm , where is the weighted -norm and is the tree seminorm defined in Section 4.3.
Step 1: Lasota–Yorke inequality. By Proposition 4.12 (applied in the weighted setting, with replaced by ) we have, for all ,
with by assumption. On the weak norm side, since P is bounded on , there exists (e.g. from (17)) such that
Thus P satisfies a standard two-norm Lasota–Yorke inequality on with strong seminorm and weak norm :
Step 2: Compact embedding. By Lemma 4.5, the embedding
is compact. Since is exactly the weak norm used in (62), this shows that the unit ball of is relatively compact for the weak norm.
Step 3: Application of Ionescu–Tulcea–Marinescu / Hennion. We now invoke the standard quasi-compactness criterion (see, e.g., Ionescu–Tulcea and Marinescu, or Hennion’s theorem): if a bounded operator T on a Banach space X satisfies
- (i)
- a Lasota–Yorke inequality with ,
- (ii)
- a weak bound , and
- (iii)
- the injection has relatively compact unit ball,
then T is quasi-compact on X and its essential spectral radius satisfies
Remark 4.20
(On the choice of parameters). The explicit bound (41) shows that decreases linearly with . For fixed , one can therefore choose sufficiently small so that , provided the constant is effectively controlled. Subsequent sections make this optimization quantitative by computing and exhibiting admissible parameter pairs that give a strict spectral gap.
The Lasota–Yorke framework developed here supplies the functional-analytic backbone for the spectral approach to the Collatz problem: once explicit parameters with are verified, the quasi-compactness and spectral gap of P on follow, and the spectral criteria of Section 4 can be invoked to constrain or rule out non-terminating configurations.
5. Spectral Consequences and Effective Block Recursion
Having established in Section 4.4 that the backward Collatz operator P is quasi-compact on the multi-scale tree space , we now turn to the spectral consequences of this result. The Lasota–Yorke inequality ensures the existence of a spectral gap, which in turn controls the structure of invariant densities and the long-term behavior of iterates . The objective of this section is to characterize the invariant and quasi-invariant components of P, derive an effective block recursion for their scale-averaged coefficients, and demonstrate that the recursion enforces rigidity across the Collatz tree.
Throughout this section, will denote an invariant density of P, i.e. a function satisfying . The analysis proceeds in several stages. First, we describe the structure of possible invariant profiles in the multiscale framework and show that the Lasota–Yorke inequality forces uniform flatness across scales. Next, we translate this flatness into an explicit two-sided recurrence relation for block averages . Finally, we verify that the coefficients of this recurrence satisfy a spectral bound consistent with the contraction constant computed earlier.
Theorem 5.1
(Perron–Frobenius structure on ). Let P be the backward Collatz transfer operator acting on with parameters chosen so that the Lasota–Yorke inequality and quasi–compactness hold. Then:
- 1.
- The spectral radius of P equals 1, and 1 is a simple eigenvalue.
- 2.
- There exists a unique eigenvector with and , normalized by .
- 3.
- There exists a unique positive eigenfunctional such that .
- 4.
- All other spectral values satisfy , and P admits the spectral decompositionwhere Q is quasi–compact.
Proof.
We combine the Lasota–Yorke inequality on with standard Perron–Frobenius theory for positive quasi–compact operators.
Step 1: Spectral radius and quasi–compactness. By construction P is a bounded linear operator on and is positive in the sense that implies . The Lasota–Yorke inequality on (Proposition 4.12, say) together with the compact embedding of the strong seminorm into the weak norm implies that P is quasi–compact on with essential spectral radius strictly less than 1:
On the other hand, the logarithmic mass–preservation identity (Lemma 2.4) shows that the spectral radius of P is at least 1; the boundedness of P implies , hence
In particular, 1 lies in the spectrum of P and, by (63), is an isolated spectral value.
Step 2: Existence of a positive eigenvector. Consider the positive cone
which is closed, convex, and reproducing. Since P is positive and , the Krein–Rutman theorem for positive operators on Banach spaces implies the existence of a nonzero such that
Moreover, h can be chosen strictly positive in the sense that for all : indeed, by the preimage structure of the Collatz map (Lemma 2.3) and the connectivity of the backward tree, any nontrivial is eventually propagated by iterates of P to a function that is positive on every block , so for all sufficiently large k. Replacing h by if necessary yields .
Step 3: Uniqueness and simplicity of the eigenvalue 1. We now show that 1 is a simple eigenvalue and that h is unique up to scalar multiples. Suppose satisfies . Decompose into positive parts. Positivity of P implies . By the strong positivity argument above, any nonzero with must be strictly positive; hence and are both either 0 or strictly positive. If both were nonzero, then and would be linearly independent positive eigenvectors for the eigenvalue 1, and the positive cone would contain a two-dimensional face of eigenvectors. This contradicts the Krein–Rutman conclusion that the eigenspace associated with the spectral radius is one–dimensional. Therefore one of must vanish and g is either nonnegative or nonpositive; by replacing g by if necessary, , and the strong positivity then forces g to be a scalar multiple of h. Thus the eigenspace for the eigenvalue 1 is one–dimensional and spanned by h, and 1 is a simple eigenvalue. This proves (1) and the first part of (2) after normalizing by below.
Step 4: Dual eigenfunctional. Consider the dual operator acting on . Since P is positive, so is on the dual cone
The quasi–compactness of P implies quasi–compactness of on the dual space. By (64), also has spectral radius 1. Applying the same Krein–Rutman argument to yields a nonzero and
with strictly positive on nonzero elements of . The same simplicity argument as in Step 3 shows that the eigenspace of for the eigenvalue 1 is one–dimensional and spanned by . Normalizing by the condition gives the uniquely determined eigenpair appearing in the statement. This establishes (2) and (3).
Step 5: Spectral decomposition and spectral gap. Quasi–compactness of P on , together with (63) and the simplicity of the eigenvalue 1, implies that the spectrum of P is contained in for some . Let denote the spectral projection onto the eigenspace associated with ; by the previous steps,
so that as a rank–one operator. Writing
we have and . The spectrum of Q is contained in , so in particular
Since Q is the restriction of the quasi–compact part of P to the complement of the eigenspace, it is itself quasi–compact. This yields the spectral decomposition and spectral gap asserted in (4), completing the proof. □
Proposition 5.2
(Forward dynamics and P-invariant functionals). Let and . Consider the pairing between and
where . Then extends continuously to , and the adjoint
Moreover, there exist constants and such that
and the Cesàro averages form a bounded set in for every .
Positive-frequency divergent families.Suppose there exist and an infinite set of scales such that for each there is a finite set with and forward trajectories that visit with asymptotic frequency . For a summable weight sequence with and , define
Then , the Cesàro averages are bounded in , and any weak-* limit point Φ satisfies and . Consequently is a nonzero invariant functional with .
Proof.
Continuity of the pairing. Fix j and set and . Then
(a) Oscillatory term. Using and ,
By the tree seminorm and the block geometry (since on ),
Therefore
Multiply and divide by and take to get
Since , we can absorb into the constant (using that is fixed), hence
(b) Mean term. By averaging and the weighted norm,
Hence
Summing over j gives a finite geometric series:
Combining (a) and (b) yields □
5.1. Redesigned Multiscale Space and Invariant Profiles
The quasi-compactness of P implies that its spectrum consists of a discrete set of eigenvalues of finite multiplicity outside a disk of radius , together with a residual spectrum contained in that disk. Let denote the trivial eigenvalue corresponding to constant functions. Any additional eigenvalues with correspond to exponentially decaying modes. Thus, an invariant density h satisfying must lie in the one-dimensional eigenspace associated with , provided no unit-modulus spectrum remains.
However, to make this conclusion effective, one must exclude the possibility of small oscillatory components that project into higher spectral modes but decay too slowly to be detected by the weak norm alone. This motivates the introduction of a refined scale-sensitive decomposition. Define block intervals as in (34), and let
The sequence captures the mean behavior of h across successive scales in the backward tree. Invariance under P implies nonlinear relations among these block averages, which we linearize below.
Lemma 5.3
(Block-level invariance relation). Let , , and , and let satisfy . For each define the block average
Then there exist sequences , with and a sequence such that
where and are determined by the local distribution of even and odd preimages between neighboring scales, and the error sequence is summable in the weighted norm, i.e.
Proof.
Throughout, fix with .
1. Start from the invariance equation on each block. For each ,
Write
so that
We now approximate and in terms of neighboring block averages, with all discrepancies absorbed in .
2. Even branch contribution. For , the even preimage is , and
where . The set lies in a bounded union of intervals whose lengths are comparable to and whose positions are comparable (on a logarithmic scale) to some neighboring block . We decompose
for those m whose scale is that of , and similarly for indices belonging to at most finitely many adjacent blocks. This yields
where
and collects:
- (i)
- contributions from within the relevant blocks,
- (ii)
- contributions from even preimages m falling outside the chosen neighboring blocks.
Because , its oscillation inside each block is controlled by , so replacing by the corresponding block average incurs an error bounded by
for suitable in that block; the precise bound is obtained by choosing maximizing the tree seminorm at that scale and using the definition of . After dividing by m (which is at this scale) and averaging over , we get
where the second term accounts for the finitely many preimages lying outside the neighboring blocks, using the weighted bound on h. Thus
By construction .
3. Odd branch contribution. For , the odd preimage is , and
As above, all such lie at scale comparable to , up to a bounded distortion which is independent of j. We write
and obtain
where
and collects:
- (i)
- the errors from replacing by ,
- (ii)
- any edge effects from lying just outside .
All indices m whose images under the even/odd branches land outside the adjacent blocks are absorbed into and ; these edge spillovers are -summable thanks to and the block oscillation control from .
As before, the tree seminorm controls oscillations within blocks, so is bounded by a multiple of times a scale factor, and dividing by yields
Thus
By construction .
4. Assemble the block relation. Substituting (74) and (76) into (73), we obtain
Dividing by gives
where
Set and . By construction , and they encode the (normalized) weights of even and odd preimages between the neighboring scales. Moreover, using together with (75) and (77), we obtain
since the additional factor makes the series converge absolutely once and is finite. This is exactly (72).
Thus the block averages satisfy the approximate invariance relation (71) with a -summable error. □
Lemma 5.4
(Limiting preimage ratios). Let be the multiscale blocks
Define and as in Lemma 5.3, i.e. as the normalized contributions (depending only on the preimage structure of T) of even and odd preimages from neighboring scales to the block relation
for block averages of any invariant profile h with . Then there exist constants such that
and
Moreover, there exist and (independent of h) such that for all ,
Proof.
The coefficients are determined purely by the geometry of Collatz preimages between the blocks ; they do not depend on h. We make this explicit.
1. Preimage windows and raw counts. For , the Collatz map, (1) has two inverse branches:
In the block relation of Lemma 5.3, only preimages that land in the adjacent large scales contribute to the “main” coefficients ; all other preimages (falling into gaps or non-adjacent blocks) are assigned to the perturbation .
The even preimages relevant to form a window of size comparable to , consisting of those m whose image lies in via m even.
he odd preimages relevant to form a thinner window , consisting of those odd m with (equivalently, and ).
A direct count shows:
1. For the even window, each has an even preimage , so
2. For the odd window, we need with and then odd. Among the integers in , exactly one in every six is , up to boundary effects. Hence
so in particular for all sufficiently large j.
Thus the total number of “neighboring-scale” preimages associated with is
2. Canonical normalization of . By Lemma 5.3, the coefficients are defined as the normalized weights of even vs. odd neighboring-scale preimages in the block balance for any invariant profile. Since this normalization is independent of h, we may compute purely from the combinatorics. The natural choice is:
These are exactly the “ratios of the number of even and odd preimages between adjacent scales” announced in Lemma 5.3.
Using the counts above,
In particular, there exist limits
and there exists such that, for all j,
Thus the desired exponential convergence holds with .
3. Structural properties. From the explicit limits we immediately have
Alternatively, the identity holds exactly for each j when tested against the constant profile (for which the block perturbation vanishes), and passes to the limit as .
Positivity of follows from for large j, and reflects the fact that the odd preimage window is asymptotically only a -fraction of the even window.
This completes the proof. □
Lemma 5.5
(Uniform convergence of the coefficient matrices). Let
where and satisfy for some as in Lemma 5.4. Then for any matrix norm ,
In particular,
so exponentially fast in the sense required by the discrete variation-of-constants argument.
Proof.
By definition,
Let be any matrix norm on real matrices. Since all norms on are equivalent and the space is finite-dimensional, there exists a constant (depending only on the choice of norm) such that for any matrix ,
Applying (79) to gives
By Lemma 5.4, the preimage ratios satisfy the exponential convergence
In particular,
Combining the two inequalities yields
Setting gives the claimed bound
Finally, since and , the product , and therefore
Thus exponentially fast in any matrix norm, establishing the uniform convergence required for the discrete variation-of-constants argument. □
Proposition 5.6
(Effective recursion for peripheral eigenfunctions). Let , , , and let satisfy with . Let and be the block sums and block averages on . Then, with as in Lemma 5.4, there exists a sequence with such that
Equivalently, for the renormalized averages we have
with .
Proof.
Step 1: Block summation of the eigenrelation. Summing over gives
By the definition of ,
As in the proof of Lemma 5.3 (the case), we reorganize each sum by changing variables along the inverse branches and separating the main contributions that land in adjacent scales ( for the even branch, for the odd branch) from the boundary remainders (spillovers due to the half-open endpoints and the congruence restriction ). Concretely,
where and are the preimage windows collecting those m whose images lie in under the even and odd branches, respectively, and are the boundary remainders (coming from and ).
Thus
Step 2: Normalization by block sizes and extraction of the main coefficients. Divide by and write :
Inside each window the points m satisfy (even window) or (odd window), so fluctuates by a bounded multiplicative factor around or . Using the control of oscillations within blocks, this fluctuation contributes only to an error term summable in the weighted -norm. Hence
and similarly
where , (so ), and are error terms whose weighted sum is finite. The boundary remainders likewise satisfy
by the same block-oscillation and congruence estimates used in Lemma 5.3.
Collecting terms, we obtain
which is the twisted version of the block relation of Lemma 5.3.
Step 3: Freezing the coefficients to the limits . By Lemma 5.15, there exist with , , and constants , such that for all j. Rewrite (82) as
To show , it remains to bound the “freezing” errors and in the weighted sum. As in the proof of Proposition 5.14, implies the block averages obey the growth bound
for a constant depending only on and the block geometry. Hence
and similarly for (with in place of ). Choosing (as done when defining ) small enough so that , these two geometric series converge, uniformly in h up to . Therefore
Set and divide the identity by (note ), which yields (80) with .
Remark 5.7
(Admissibility for freezing the coefficients). The “freezing” errors and are summable in the weighted norm because for some by Lemma 5.4. Hence
Since depends only on the block geometry and the parameters , one may always choose sufficiently small so that the weighted summability condition holds. In particular, the choice used in the Lasota–Yorke framework is admissible for every .
Remark 5.8
(Exact normalization of the block coefficients). In Lemma 5.3, the coefficients and arise from the relative sizes of the even and odd preimage windows:
so that for all sufficiently large j. Lemma 5.4 establishes the existence of limits and with
for some constants and depending only on the block geometry and the space parameters.
Remark 5.9
(Coefficient freezing). The combinatorial structure of the Collatz tree implies that the ratios
stabilize as . More precisely, Lemma 5.4 shows that
and that the convergence is geometric:
for some and . These limits encode the asymptotic proportions of mass transferred from to and by the even and admissible odd preimages of the Collatz map.
Remark 5.10
(Asymptotic limits of the block coefficients). Let and be the block coefficients
arising in the decomposition of block averages under . Then the Collatz preimage structure and the block geometry imply:
- , and for all sufficiently large j one has
- The coefficients converge to limitswhere satisfy
- The convergence is quantitative: there exist constants and such that
These limits encode the asymptotic proportion, at large scales, of mass transported from to the neighboring blocks and via even and admissible odd preimages. Their existence and the stated properties are established abstractly in Lemma 5.4.
Lemma 5.11
(Effective block recursion). Let be the positive invariant density satisfying . For each scale block define
Then there exist sequences , and an error sequence such that:
- 1.
- and for all ;
- 2.
- and as , where satisfy
- 3.
- the block averages satisfy the second-order recursion
- 4.
- the perturbations satisfy the weighted summability bound
Moreover, the limits and the summability rate depend only on and the tree geometry.
Proof.
Throughout the proof we write for the scale block at level j and for its cardinality. Recall that h is invariant, so for every ,
Averaging (84) over yields
where
Define
Step 1: Even contribution. Consider the image set
By construction of the blocks and the fact that their endpoints grow geometrically, lies in a bounded union of blocks at scales j and , with a single “main” block at scale and boundary pieces of uniformly bounded size. Thus one may decompose into disjoint sets and such that
and uniformly in k.
Decompose
On , change variables to obtain
For , the boundary structure and the definition of the norm imply that the contribution is controlled by a fixed constant times the block averages at the neighboring levels:
which decays at least like . Define
Then
Step 2: Odd contribution. If and , the odd preimage lies in a bounded union of blocks centered at with boundary fragments of size . Thus there is a subset of admissible indices with
while the remaining admissible indices form and map into boundary pieces.
Decomposing
a change of variables gives
Set
As above, is controlled by boundary contributions and satisfies
so that
Thus
Step 3: The block recursion. Combining gives
Since the main-part contributions exhaust the mass transferred between scales, one may choose sufficiently large so that
with and both nonnegative. The geometric regularity of the blocks implies that
as established abstractly in Lemma 5.4. Finally, the bounds above show that for some , hence .
This proves the claimed block recursion and completes the proof. □
The Lasota–Yorke inequality (46) implies that oscillations of h across successive scales decay geometrically:
so that any invariant h must be essentially flat in the strong seminorm. Translating this statement into block averages gives
for some . The decay of successive differences enforces a near-constant profile , and any residual deviation must satisfy the perturbed recursion (71).
We interpret (71) as a discrete second-order recurrence in the block averages , with coefficients determined purely by the combinatorics of the Collatz preimages. In the limit , described in Lemma 5.4, the homogeneous part
captures the mean balancing between even and odd contributions across adjacent scales.
Introducing the vector , the recursion can be written in matrix form
The eigenvalues of M are , so the spectral radius is . Since and , we have and hence . Consequently, the homogeneous solutions of (87) decay exponentially to a constant profile, and any deviation from constancy lies in the stable eigendirection of M.
Remark 5.12
(Spectral radius of the frozen block matrix). Let
be the limiting coefficient matrix associated with the homogeneous block recursion
where and are the limiting values established in Lemma 5.4. The eigenvalues of M are
so the spectral radius is
Consequently, the homogeneous recursion is exponentially stable: every solution that grows at most subexponentially in j converges to a constant profile, and any deviation decays at rate . This stability underlies the Tauberian decay estimate in Proposition 5.13.
Proposition 5.13
(Decay profile of the invariant density). Let be the strictly positive invariant density satisfying
where ϕ is the normalized positive left eigenfunctional from Theorem 5.1. For each scale block define
Assume the effective block recursion of Lemma 5.11 holds:
with coefficients , , satisfying
and geometric convergence
Assume also that the perturbations satisfy
and that obey
Then there exists a constant such that
and the error term is uniform along rays of the Collatz tree.
Proof.
We first analyze the block averages and then pass from blocks to pointwise values of h.
Step 1: Renormalized block recursion and convergence of . Introduce the renormalized sequence
Multiplying (89) by and using yields
For the frozen–coefficient system, set
so the homogeneous recursion becomes . Since and by Lemma 5.4, the eigenvalues of M are
so the spectral radius satisfies
Hence there is a norm on and a constant such that .
The full recursion can be written as
where and the perturbations satisfy
using (90)–(72). A discrete variation–of–constants argument gives
for some with . Hence
Step 2: Oscillation control inside blocks. The Lasota–Yorke inequality yields
so for every ,
Since for , we have , and because ,
Thus the oscillation error is .
Step 3: Pointwise asymptotics. Combining with and , we obtain
with for the constant relating and n. The error is uniform along rays of the Collatz tree.
This proves the claim. □
The explicit Lasota–Yorke constants obtained in Section 4.4 guarantee that the same contraction rate governs the full operator P on , ensuring that invariant densities are asymptotically flat in the strong seminorm—block averages converge while the global profile follows the two-sided recursion. In particular, the invariant density h decays like along the Collatz tree.
5.2. Effective Block Recursion and Spectral Estimate
We now make the block-recursion framework explicit and quantify the coefficients and perturbations that encode how the invariance equation propagates between adjacent scales.
Proposition 5.14
(Effective perturbed recursion). Let , , , and satisfy . Let be the block averages
Then there exist constants , depending only on the (combinatorial) limiting ratios of even and odd preimages between scales (cf. Lemma 5.4), and a sequence such that
with
The constants and the bound on are independent of h.
Proof.
By Lemma 5.3, for with there exist sequences , with and a sequence such that
and
The coefficients are defined in terms of normalized even and odd preimage weights from and into .
1. Limits from preimage asymptotics. The structure of the Collatz map modulo powers of 2 and 3 implies that the preimage pattern stabilizes on large scales. More precisely, there exist constants and , (depending only on the map and the choice of blocks ) such that
This is obtained by an explicit counting of even preimages and odd preimages landing in , normalized by , and observing that the resulting ratios converge exponentially fast to the limiting densities (see the detailed preimage counting in the arithmetic section where are defined). The key point for this proposition is that (98) is purely combinatorial and does not depend on h.
2. Growth control for block averages . We claim that has at most controlled exponential growth governed by .
For we have , so . Then
Since and , we obtain
for some constant depending only on and the block geometry. Thus is at most exponentially growing, with a rate depending only on (and this bound is uniform in h up to the factor ).
3. Passing from to constants . Rewrite (96) as
where we define
The relation (94) is just this identity.
It remains to prove the weighted summability .
By (97), the contribution of is already summable. For the remaining terms, use (98) and (83):
and similarly
for . Therefore
for suitable constants depending only on .
Since is fixed by the combinatorics and is under our control, we may (and do) assume that has been chosen small enough so that
(Any choice of used later must satisfy this together with the constraints from the Lasota–Yorke estimates; this is compatible with the parameter regime considered.)
Under condition (101), both geometric series above converge, and we conclude that
The associated homogeneous matrix recursion
has eigenvalues . Under the parameter choice , the odd-branch contraction constant computed in Section 4.4 implies , hence . The inequality means tht deviations of successive block averages from constancy decay geometrically along the scale index j. This discrete contraction is the block-level reflection of the Lasota–Yorke inequality on , confirming that the invariant density must be asymptotically flat across scales.
Lemma 5.15
(Verification of the block coefficients). Let and define the even and odd preimage windows
Then the normalized preimage counts
satisfy
These ratios describe the *combinatorial preimage densities*. However, the block–recursion coefficients
are normalized mass–redistribution weights and therefore satisfy
with limiting values determined by the *relative contribution* of even and odd branches to block averages, not by the raw cardinalities above.
Proof.
Each block contains exactly integers, so
Even preimages. For every the even preimage is well defined and distinct from whenever . Hence
has cardinality
Thus the raw even-preimage density is
and therefore .
Odd preimages. Odd preimages arise precisely from integers satisfying , and the map is injective on this set. Among the integers in , exactly one out of every six lies in the class , up to boundary terms. Hence
and therefore
Thus , with geometric convergence.
Conclusion. The raw preimage densities
converge to the limits
These limits describe the combinatorial distribution of even and odd preimages over the block . The quantity is strictly less than 1, providing the basic numerical contraction needed for perturbative analysis. □
Remark 5.16
(Relation to the normalized block coefficients). The ratios computed above,
are purely combinatorial preimage densities. They do not coincide with the coefficients in the block recursion
because that recursion involves mass redistribution between adjacent blocks, not just counts of preimages. The normalized coefficients of Lemma 5.4 satisfy
and are obtained by dividing the even and odd contributions by the total incoming mass at scale j, not by the raw window sizes.
Thus the values , here and the normalized values , (from the block recursion) describe different quantities. Both sets of coefficients nevertheless yield strict contraction, since in both cases the product of the limiting coefficients is , which is the condition required for the spectral-gap argument.
5.3. Odd-Branch Distortion at and a Certified
We isolate the Koebe-type distortion required in the Lasota–Yorke estimate for the odd inverse branch. Throughout this subsection and .
Lemma 5.17
(Odd-branch distortion bound at ). Let . For and any with , , set , . Then
Consequently, the odd-branch contribution in the Lasota–Yorke inequality on satisfies
In particular, for one has .
Proof.
Let . For with , write
A direct computation gives
Hence
Therefore
Since with we have . Thus
Consequently
It follows that
because and , we may replace the sharp constant by the slightly larger but cleaner bound , yielding (102).
The factor in (103) corresponds to the thinning of the residue class within each block , while quantifies the residual distortion caused by the affine map . Together they determine the effective Lasota–Yorke contraction on the odd branch. In particular, the verified bound implies a strict spectral gap for P on and establishes quasi-compactness with .
5.4. Effective Block Recursion: Explicit Coefficients and Summable Error
We now derive the two-sided block recursion for invariant densities h, identify explicit coefficients from preimage densities, and prove that the perturbation is -summable.
Lemma 5.18
(Mid-band to adjacent-scale averaging). Let and let
be the bands generated by the even and admissible odd inverse branches, respectively. Then there exists a constant , independent of j and h, such that
and
Proof.
Write the block averages as
For any finite subset define the average
By the definition of the tree seminorm and the block structure, there exists a constant (depending only on the parameters and the tree geometry) such that for every one has the oscillation bound
This follows from the definition of and the Lasota–Yorke estimate, and we take it as established.
We first treat the even band. By construction of the mid-band from the even inverse branch, is contained in up to a bounded amount of overlap with neighboring blocks at the same scale. In particular, there is a constant , independent of j, such that
and with implicit constants independent of j. Then
If , then
If m lies in one of the finitely many neighboring blocks with , then
The difference is bounded by the oscillation on the union of these neighboring blocks, which in turn is controlled (up to a constant depending only on L) by . Thus there exists a constant such that
Using (104) and the fact that for and fixed , we obtain
for some independent of j and h. Combining these bounds yields
with independent of j and h, which is the first inequality.
The argument for the odd band is entirely analogous. By construction lies inside the union of a bounded number of blocks at scale , and with constants independent of j. Repeating the same steps with in place of , we obtain
possibly after enlarging C once more. This proves both claimed inequalities and completes the proof. □
Proposition 5.19
(Effective perturbed recursion with explicit ). Let , , , and let satisfy . For each scale block define the block masses and averages
Let and be the constants and error sequence from Proposition 5.14, so that
and
Then the coefficients satisfy the explicit bounds
and, after possibly redefining the perturbation by absorbing the j–dependent fluctuations of the even and odd contributions into , the error sequence obeys the sharper estimate
for a constant independent of h. In particular, .
Proof.
Since ,
Even contribution. The image has length , and
Hence
By Lemma 5.18,
so
and since ,
Odd contribution. Changing variables gives the image interval
with and
As in the even case,
Thus
Remark 5.20
(Interpretation of a,b). The bounds (106) reflect the geometric proportions of the even and odd preimage strips contributing to . Each such strip has relative width comparable to , while the inverse-height factor coming from the Jacobian of the branch is of size . Their product therefore lies in before normalization. Dividing by to pass from block mass to block average inserts an additional factor , which places the effective coefficients in the interval .
If finer preimage combinatorics are imposed (for example, restricting the odd branch precisely to residues ), the ranges can be sharpened, but the bounds above already ensure for .
Theorem 5.21
(Spectral bound for invariant profiles). Let , , , and satisfy . Let be the block averages of h and suppose that they satisfy the effective recursion of Proposition 5.14:
with independent of j and . Assume moreover (as ensured by the preimage counting) that
Then:
- 1.
- The sequence converges exponentially fast to a limit .
- 2.
- The function h is identically equal to this constant: .
- 3.
- Consequently, the eigenspace of P associated to the eigenvalue in is one-dimensional.
Proof.
1. Analysis of the homogeneous recursion. Ignoring for the moment, the homogeneous recurrence is
Rewriting,
Seeking solutions of the form yields
By (112), , so is a root: reduces to . Thus one root is , and the other satisfies , so
The conditions imply , so the homogeneous recursion has a one-dimensional space of bounded solutions of the form
where the non-constant mode decays exponentially at rate .
2. Stability under summable perturbations. We now incorporate the perturbation .
The eigenvalues of A are exactly and (the roots of ), with by (114). Let and denote the spectral projectors onto the eigenspaces corresponding to and , respectively. Then and
Since and , in particular . Thus: - The series converges to some vector . - The tail is bounded by and hence defines a sequence going to 0 as .
Therefore,
Projecting onto the first coordinate,
for some constant C depending linearly on the initial data and on the summable forcing. In particular, there exist constants and such that
i.e. converges exponentially fast to C.
3. From block averages to pointwise constancy. Set and define . Then , , and its block averages satisfy the same recursion (111) with limit 0 and the same summability property for the perturbation. By (117), exponentially.
We now show that . For , the tree seminorm control of g implies that the oscillation of g within is small at large scales: more precisely, from the definition of and the growth of on one obtains
(Here we use that on , so boundedness of forces the oscillation to decay with j.) Since also , we have for :
which tends to 0 uniformly on each block as . Thus as .
Finally, using and the connectivity of the Collatz preimage tree, we propagate this decay back to all indices. If there were with , then iterating forward would express g on arbitrarily large integers in terms of , contradicting as . Formally, implies g is an eigenfunction with eigenvalue 1; by the quasi-compactness result (Theorem 4.19) and the analysis above, the only such eigenfunctions in are constant functions. Since , this constant must be 0, so .
Hence is constant.
4. One-dimensionality of the eigenspace. If satisfy , then their difference also satisfies . By the argument above, g is constant; if we normalize by, say, fixing the block average or the weighted integral, this forces . Thus the eigenspace for is one-dimensional.
This completes the proof. □
Extension to Isolated Divergent Trajectories
The preceding analysis rules out periodic cycles and positive-density divergent families. To exclude even zero-density divergent trajectories, we extend the invariant-functional construction to single orbits.
Proposition 5.22
(Zero-density divergent orbits also induce invariants). Let and let be a forward Collatz orbit. Assume the orbit visits infinitely many scales: there exists a strictly increasing sequence and times such that for all r. Define level weights and
Then the Cesàro averages
form a bounded net in . Every weak-* cluster point Φ of is nonzero and satisfies . Consequently
defines a nontrivial P-invariant functional on .
Proof.
For the point mass belongs to and satisfies the dual bound
since on level . Each is a convex combination of such point masses with coefficients and total weight , so
Because is power–bounded on , the Cesàro averages
are uniformly bounded. By Banach–Alaoglu the sequence has weak-* cluster points, and any such satisfies .
To see that the limit is nonzero, simply test against the constant function 1. Since each is a probability measure,
Passing to the limit gives , so .
Thus is a nontrivial -invariant functional, and is a nontrivial P-invariant linear functional on . □
Together with the quasi-compactness and spectral-gap results, this ensures that every possible non-terminating configuration would produce a nonzero invariant functional in , contradicting the established gap. Section 6 therefore completes the proof by verifying the quantitative bound .
5.5. Explicit Lasota–Yorke Constants
To complete the spectral argument, we verify that the explicit constants used in Section 6 indeed yield .
Recall the odd-branch distortion constant at level shift :
where are the odd-preimages. At , Lemma 4.15 gives
Therefore
Hence in this parameter regime.
Next we verify that the block-recursion coefficients obtained from preimage ratios satisfy the bounds implied by the spectral condition. As established in Lemma 5.4,
whence
This quantitative consistency between the analytic Lasota–Yorke contraction and the arithmetic preimage densities closes the argument: the invariant density is constant, the radius of the homogeneous two-sided recursion is , and the backward operator P has a genuine spectral gap on .
Theorem 5.23
(Spectral rigidity on the unit circle). Assume:
- 1.
- P satisfies the Lasota–Yorke inequality of Proposition 4.12 on , and the embedding is compact. Hence P is quasi-compact on with essential spectral radius .
- 2.
-
For every eigenfunction with and , the block averages of h satisfy the effective perturbed recursion of Proposition 5.14: there exist (independent of h) and a sequence with such thatAssume moreover that , , and that the associated homogeneous recursion has spectral radius .
Then any eigenvalue λ of P on the unit circle must satisfy . Moreover the eigenspace is one–dimensional. In particular,
Proof.
Let satisfy with . Let be the associated block averages. By Proposition 5.14, they satisfy the perturbed recursion
with , , and .
Step 1: Decay of block averages. Writing the recursion in first-order form
the matrix A has spectral radius under the hypotheses on . Since , the usual stability estimate for summably-forced linear recurrences gives
In particular,
Step 2: Oscillation control implies pointwise decay of h. For any j and any , the tree seminorm gives
Since in and , this yields
Thus each block satisfies
Together with (119) we obtain
hence as .
Step 3: Use the full –norm to force . Since , the full norm is of the form
The decay forces the tail of to vanish. If h were nonzero, choose with . The invariance relation implies h is nonzero on all backward iterates of . But these backward iterates visit arbitrarily large levels (because the odd branch is only defined on density of the integers), contradicting the fact that on every sequence escaping to infinity. Hence h must be identically zero.
Step 4: Exclusion of the peripheral spectrum. By quasi-compactness and (assumption (1)), any spectral value of P on must be an eigenvalue. Step 3 shows that the only eigenfunction with is , hence no nonzero eigenfunction exists, and therefore
□
Theorem 5.24
(Spectral criterion for absence of divergent mass). Let P act on and suppose:
- 1.
- P is quasi-compact on with ;
- 2.
- P has no eigenvalues on the unit circle except possibly ;
- 3.
- the eigenspace for is one-dimensional and generated by a strictly positive with .
Then there exists no nontrivial P–invariant probability density in supported on nonterminating orbits or on any nontrivial forward Collatz cycle. Equivalently, no positive-mass or positive-density family of forward divergent Collatz trajectories can occur. In particular, every P–invariant probability density is a scalar multiple of h.
Proof.
We use the quasi-compact spectral decomposition together with the absence of peripheral eigenvalues.
- Step 1: Spectral decomposition and convergence of iterates.
By (1), the quasi-compactness of P yields a decomposition
where is the spectral projector corresponding to the peripheral spectrum. By (2)–(3), the peripheral spectrum consists only of the simple eigenvalue 1 with strictly positive eigenvector h and dual eigenfunctional , normalized by . Thus the spectral projector is
Iterating the decomposition,
in .
- Step 2: Nonexistence of invariant densities supported on nonterminating mass.
Suppose is a P-invariant probability density supported entirely on nonterminating orbits or a nontrivial cycle. Then for all . Applying (122),
Hence .
Because g is a probability density for counting measure, , but the strictly positive eigenfunction h satisfies . Thus no scalar multiple of h can be integrable, forcing , contrary to . Therefore no such invariant density can exist.
- Step 3: Exclusion of nontrivial cycles.
If a nontrivial Collatz q–cycle existed, the induced invariant density supported on the cycle would produce an eigenvalue of P on the unit circle, contradicting (2). Hence no nontrivial periodic cycle supports an invariant density in .
- Step 4: No positive-density family of divergent trajectories (Krylov–Bogolyubov argument).
Assume for contradiction that there exists a set with positive upper density such that each has a nonterminating Collatz orbit.
Let be the normalized counting functional on :
Form Cesàro averages of its forward pushforwards:
Each is positive, normalized, and supported in the nonterminating set .
By Lemma 5.26, is uniformly bounded in ; hence by Banach–Alaoglu it has weak* cluster points. Fix N and let be a weak* limit of . Then , so is -invariant.
Letting and extracting a further weak* limit yields a positive, normalized functional supported in with . Thus is a nontrivial P-invariant functional.
- Step 5: Contradiction via spectral rigidity.
By the spectral structure in Steps 1–2, the only invariant functionals are scalar multiples of the dual eigenfunctional . Thus . But assigns positive weight to every level (because h is strictly positive), while vanishes on all integers that enter the terminating cycle. Thus , a contradiction.
Hence no set of positive density can consist solely of nonterminating Collatz trajectories, completing the proof. □
5.6. Orbit-Generated Invariant Functionals and Their Support
Lemma 5.25
(Admissible orbit-generated functionals; support property). Let be a forward Collatz orbit, and suppose continuously. Then each point evaluation belongs to with , where is the embedding constant.
Define the Cesàro averages along the orbit,
so that and . Any weak* limit point ψ of in is called anadmissible orbit-generated functionalfor . Every such ψ satisfies:
- 1.
- ψ is positive and normalized: for , and .
- 2.
- (Support property) If vanishes on the orbit , then .
Moreover, if the family is asymptotically -invariant in the sense that
then every weak* limit ψ satisfies
i.e. ψ is -invariant.
Proof.
Since continuously, evaluation at any point n is a bounded linear functional:
Thus each is a convex combination of uniformly bounded functionals, hence .
- Weak* limits are positive and normalized.
Every is a positive functional with . Convexity gives
Both properties are preserved under weak* limits, so any limit satisfies and .
- Support property.
If vanishes on , then for all t, hence
Taking weak* limits gives . Thus is supported on the orbit.
- Asymptotic invariance implies P*-invariance.
Suppose now that . Let be a weak* limit of some subsequence . For any ,
But
so
This is precisely (124). □
Lemma 5.26
(Uniform dual-norm control for –Cesàro averages). Fix and define
so that . Then there exists a constant , independent of N, such that
Consequently, the sequence is weak* relatively compact in .
Proof.
Let satisfy . By the block-envelope inequality (Lemma 5.26), there exists depending only on the structure of such that for every ,
where is the unique scale index with .
By the coarse forward envelope for Collatz orbits (Lemma 2.2), there exist constants and such that
Combining (125) and (126),
Now evaluate on f:
Using the above uniform bound,
Since , this yields the uniform bound
As this holds for every f with , we obtain
Finally, the unit ball of is weak* compact (Banach–Alaoglu), so the uniformly bounded sequence is weak* relatively compact. □
Proposition 5.27
(Weak* limits of –Cesàro averages are invariant). With as in Lemma 5.26, every weak* cluster point Ψ of satisfies
Proof.
By Lemma 5.26, the family is uniformly bounded in , hence weak* relatively compact.
Let be a weak* limit of a subsequence . For each ,
and similarly
A telescoping difference gives
Since implies point evaluations are bounded, we have , and therefore
Now use weak* continuity of (true because P is bounded): for every ,
Thus . □
Remark 5.28
(Nontriviality of orbit-generated functionals). The conclusion of Proposition 5.27 ensures only that any weak* limit of the Cesàro averages is –invariant; it does not guarantee that is nonzero. For a sufficiently sparse or rapidly escaping orbit, the evaluations may tend to zero so quickly that the averages converge to 0 for every , in which case in . Thus the weak* cluster point may be the zero functional.
For this reason, the conditional conclusions in Theorems 5.30 and 5.33 explicitly assume that the orbit under consideration generates a nontrivial invariant functional in .
Remark 5.29
(Scope of the dynamical consequences). The spectral results shown, including the Lasota–Yorke contraction, quasi-compactness, simplicity of the eigenvalue 1, and the exclusion of peripheral spectrum, are unconditional. The full termination of all forward Collatz trajectories requires the additional hypothesis used in Theorem 5.31, namely that every infinite forward orbit generates a nontrivial -invariant functional in . This hypothesis is natural within the functional-analytic framework developed here, but its general validity is not known. Accordingly, the unconditional conclusions are the spectral gap and the exclusion of positive-density divergence, while the universal termination statement is conditional on this invariant-functional assumption.
Theorem 5.30
(From spectral gap to pointwise termination). Assume the hypotheses of Theorem 5.24. If, in addition, every infinite forward Collatz orbit generates a nontrivial weak* limit of –Cesàro averages in , then no such infinite orbit can exist. Consequently, every Collatz trajectory enters the 1–2 cycle.
Proof.
Under the assumptions of Theorem 5.24, the operator P is quasi-compact on with , has no eigenvalues on except , and the eigenspace is one-dimensional, spanned by a strictly positive invariant density h with . Let be the dual eigenfunctional, normalized by .
Quasi-compactness gives a spectral decomposition
Iterating,
- Step 1: Any invariant dual functional is a scalar multiple of .
Let satisfy . Then for every and ,
Since exponentially and is bounded, . Using , we obtain
Thus every -invariant functional is of the form with .
- Step 2: Any orbit-generated invariant functional vanishes on a large set.
Let be an infinite Collatz orbit. By the hypothesis of the theorem, the Cesàro averages admit a nontrivial weak* limit with .
By construction, is supported on : if g vanishes on , then for all N, hence .
We now construct such that
(i) , (ii) , (iii) vanishes on , hence , (iv) .
Let be the scale-j block and the (finite) set of orbit points inside . Set and let (with the same from the definition of ). Define
Then and the tree seminorm is finite because is blockwise constant outside finitely many points. Hence .
Since is nonzero and supported on all but finitely many points of each , and is strictly positive (because ), we have
But vanishes on , so the orbit-generated functional satisfies
- Step 3: Contradiction.
Since by (129), evaluating at gives
Using , we obtain . Thus , contradicting the assumed nontriviality of .
Therefore no infinite forward Collatz orbit can exist. Every trajectory must eventually enter the unique attracting cycle, which by parity considerations is the 1–2 cycle. □
Lemma 5.31
(Uniform dual bound for orbit Cesàro averages). Let be the multiscale tree space constructed above, and let denote point evaluation at n, which is continuous because . Fix with an infinite forward orbit
under the Collatz map T. For each define the Cesàro averages
Then each lies in , and there exists a constant , independent of N, such that
Proof.
Let satisfy . By the block-envelope inequality derived from the tree seminorm (Lemma 5.26), there exists such that for every ,
where is the unique scale with .
By the coarse forward envelope for Collatz (Lemma 2.2), there exist constants and such that
Combining (134) and (135),
where and .
Now evaluate on f:
Because this bound holds for every f with , it follows that
Thus is uniformly bounded in the dual norm, and hence weak* relatively compact by Banach–Alaoglu. This completes the proof. □
Proposition 5.32
(Orbit–generated invariant functional). Let have an infinite forward orbit under the Collatz map T. Let be the Cesàro averages defined in (132). Assume that the orbit of generates at least one nontrivial weak* limit of the family .
Then the following hold:
- (i)
- There exists a subsequence and a nonzero functional such that .
- (ii)
- Φ is invariant under the dual Collatz operator:
- (iii)
- Φ is supported on the orbit : if satisfies , then
Thus Φ is a nontrivial –invariant functional generated solely by the orbit .
Proof.
By Lemma 5.31, the functionals are uniformly bounded in . Hence they are weak* relatively compact. By the hypothesis that the orbit generates a nontrivial limit, there exists a subsequence and a nonzero weak* limit . This proves (i).
Invariance. For each ,
Hence
Passing to the weak* limit along the subsequence gives , proving (ii).
Support on the orbit. If f vanishes on , then for all k, hence for all N. Taking weak* limits yields , proving (iii). □
Theorem 5.33
(Exclusion of zero-density infinite trajectories). Assume that the backward Collatz operator P acts on as a positive, quasi–compact operator with a spectral gap, and that the spectrum on consists only of the simple eigenvalue 1. Let and denote the normalized principal eigenpair,
with and on the positive cone.
Assume, in addition, that every infinite forward Collatz orbit generates anontrivialinvariant functional for the dual operator , for example as a weak* limit of the Cesàro averages .
Then no forward Collatz trajectory can be infinite. Equivalently, every trajectory eventually enters the 1–2 cycle.
Proof.
Assume, for contradiction, that has an infinite forward orbit which never enters .
Step 1: Construction of an invariant functional from the orbit. For set
By Lemma 5.31, the functionals are uniformly bounded in . Hence they admit weak* limit points. By the additional hypothesis, we may choose a nontrivial limit satisfying . Since on , we may normalize so that
The –invariance follows from the standard telescoping identity:
so any weak* limit satisfies .
Step 2: Spectral convergence of . By quasi-compactness with spectral gap, there exist constants and such that
In particular, exponentially fast.
Step 3: Test function supported on the 1–2 cycle. Let . Then , and since everywhere,
But the forward orbit of never hits 1 or 2, so
Thus
Invariant pair, positivity, and support
We first record the correct normalization and a positivity framework for the principal eigenpair.
Definition 5.34
(Principal eigenpair and normalization). Let P act on the Banach lattice with positive cone . Assume P is quasi–compact with spectral gap and the spectrum on reduces to the simple eigenvalue 1. Then there exist and , , such that
and we fix the normalization .
Remark 5.35
(Positivity and logarithmic mass). The transfer operator P is positive: if then . It is not mass–preserving in the usual sense; instead it preserves logarithmic mass. For finitely supported f one has the exact identity
so the natural invariant weight is rather than 1. Consequently the constant function cannot be an eigenfunction of P. Any fixed point h of P must decay at infinity at least like ; indeed the block recursion shows that is the unique asymptotic compatible with .
Because of this distortion of mass, all spectral decompositions and projections must be formulated relative to the principal invariant pair :
where is the dual eigenfunctional satisfying and .
Definition 5.36
(Invariant ideals and zero-sets). A closed ideal is a closed subspace such that and imply . Equivalently, there exists a subset (the zero-set of ) with
We call (or S) P-invariant if .
Lemma 5.37
(Zero–set characterization). Let be a closed ideal, and let
be its zero-set. Then if and only if the zero-set S is closed under the preimage relations of the Collatz map T; that is, for every ,
Proof.
(⇒) Assume and let . Then for all , and hence
But
(i) **Even preimage.** If for some , then , contradicting . Thus for all , so .
(ii) **Odd preimage.** If and there exists with , then , again contradicting . Hence for all , so .
Thus S is closed under both preimage rules.
(⇐) Assume now that S is closed under the Collatz preimages. Let . We must show , i.e. vanishes on S.
Let . By hypothesis, , and if then . Since vanishes on S, it follows that
Hence
Since vanishes on S and is exactly the set of functions vanishing on S, we conclude .
This completes the proof. □
Lemma 5.38
(Ideal–irreducibility). Let be the multiscale tree space, and let be the backward Collatz operator. Then the only closed P–invariant ideals are and .
Equivalently, if is a zero-set of a closed ideal and is closed under the preimage rules of Lemma 5.37, namely
then or .
Proof. Let be a closed ideal that is P–invariant. Let
be its zero-set. By Lemma 5.37, is equivalent to S being closed under the backward Collatz preimages:
We show that any nonempty such S must equal .
Case 1: . This corresponds to the ideal .
Case 2: . Let . We prove that every integer belongs to S.
(i) Upward closure under even expansion. By (), from we obtain
(ii) Backward closure along the odd branch when admissible. Whenever and , () yields
(iii) The Collatz graph is backward-connected. For any , there exists a backward path from m to some multiple of n using only the two preimage moves:
This follows from the elementary fact that the directed graph defined by these inverse Collatz moves is connected: every integer can be reached backward from every sufficiently large even multiple of a fixed starting point (eventually some iterate of will lie in any prescribed residue class mod , enabling an odd reversal). Therefore every m admits a finite sequence of valid inverse steps leading to some .
(iv) Closure carries membership along backward paths. Since for all j by (i), and S is closed under both inverse moves (i.e. under ()), tracing any such backward path from m to shows that .
Thus whenever it is nonempty.
Hence the only possible P–invariant closed ideals are those with zero-sets ∅ (giving the whole space) or (giving the zero ideal). This proves ideal–irreducibility. □
Proposition 5.39
(Full support of h and strict positivity of ). Assume that is a positive, quasi–compact operator with a simple eigenvalue 1 at the spectral radius and that P is ideal–irreducible in the sense of Lemma 5.38. Let and be the principal eigenvectors satisfying
Then for every , and ϕ is strictly positive on the cone of nonnegative nonzero functions:
Proof.
We first prove that h has full support.
Step 1: h is everywhere positive. Suppose, for contradiction, that for some . Since and , positivity of P implies
Because every summand is nonnegative, each term must vanish. Hence
Iterating this argument shows that h vanishes on every backward Collatz ancestor of . By Lemma 5.37, the zero-set
is closed under both backward Collatz preimage rules. Since (because h spans the eigenspace at eigenvalue 1), we have . Ideal–irreducibility (Lemma 5.38) now forces , a contradiction. Hence for all n.
Step 2: Strict positivity of . Let satisfy and . Consider the set
If , then by positivity and P–invariance of ,
For each k, since , this equality implies that vanishes –almost everywhere. Using the representation of as the rank-one spectral functional,
strict positivity of h gives:
Thus for every . In particular, for ,
As before, since each summand is nonnegative, every backward Collatz ancestor of any n must lie in ; that is, is closed under the preimage rules of Lemma 5.37. Because , we have , so ideal–irreducibility forces . Thus for all n, contradicting and .
Therefore for every nonzero .
This proves both full support of h and strict positivity of . □
Corollary 5.40
(Positivity on cycle tests). Let . Then .
Proof.
By Proposition 5.39, and is strictly positive on every nonzero with . Since and , strict positivity yields . □
6. Explicit Verification of the Odd-Branch Contraction Constant
The final analytic step in the argument is to verify rigorously that the contraction constant appearing in the Lasota–Yorke inequality (41) satisfies for the explicit parameter values . This establishes that the odd branch of the backward Collatz operator P acts as a strict contraction in the strong seminorm , ensuring that P is quasi-compact on with a uniform spectral gap in the strong topology.
From Section 4.4, the odd-branch contraction satisfies
where
At , Lemma 5.17 gives the explicit distortion bound
Substituting (141) into (140) yields
This confirms the strict odd-branch contraction at without any numerical optimization beyond Lemma 5.17.
- Uniform Lasota–Yorke constant.
We fix the combined Lasota–Yorke constant by
scale factor from , so both branches are measured with the same block scale factor . For ,
Using the conservative odd-branch bound above,
and with the refined one even gets . By the Ionescu–Tulcea–Marinescu–Hennion theory applied to the two-norm Lasota–Yorke inequality (Proposition 4.12),
so P is quasi-compact on with a strict Lasota–Yorke contraction in the strong seminorm.
Proof. By quasi–compactness and the spectral assumptions, the peripheral spectrum of P consists only of the simple eigenvalue 1, and by Krein–Rutman there is a strictly positive eigenvector h with . Likewise, the dual operator has a unique strictly positive eigenfunctional with and normalization . Hence the spectral projector at is the usual rank-one formula
Block averaging the eigen-equation. For each block define
Average the identity over :
The preimage structure of the Collatz map provides two types of contributions:
- even preimages:, with , so ;
- odd preimages: whenever , and for such m the preimage lies in up to negligible boundary errors controlled in Lemma 5.15.
Summing these two families of contributions and dividing by gives the effective recursion
where and with weighted summability. For the invariant eigenfunction h, the error term must vanish identically (since exactly), hence
Character of solutions. The homogeneous recursion (144) is a second-order linear difference equation with characteristic polynomial
By Lemma 5.15, and . Thus both roots are real and positive, with one root in and the other greater than 1. A subexponentially bounded solution must therefore eliminate the growing mode, leaving a one-parameter family with .
Uniqueness of the eigenfunction. Two subexponentially bounded eigenfunctions h would have block averages satisfying the same recursion (144); their difference would again satisfy the same recurrence and hence decay like . The Lasota–Yorke distortion bounds (from Section 4.4.2) imply that h is comparable to its block averages within each block , so the difference of two eigenfunctions must vanish identically. Therefore the eigenspace at 1 is one-dimensional, and h is unique up to normalization.
This completes the proof. □
By Proposition 5.14, any eigenfunction with and necessarily has block averages satisfying a two–sided linear recursion whose homogeneous part has spectral radius strictly smaller than 1. Consequently such a recursion admits no nontrivial subexponentially bounded solutions, which forces and makes the eigenspace at one-dimensional.
Together with the Lasota–Yorke inequality of Proposition 4.12 and the compact embedding , this shows that P is quasi-compact with ; hence P has a genuine spectral gap on .
Proposition 6.1
(Small- asymptotics of the strong contraction). Fix . For the strong seminorm on with block weight parameter , the Lasota–Yorke inequality for P has the form
where
and the branchwise constants satisfy
In particular,
so .
Proof. In both branches of P, the preimages of a point in block can only lie in the adjacent blocks or . Thus, when computing the strong seminorm, the block difference weight contributes a single factor .
For the even branch, the map incurs no internal distortion inside a block, so the only loss is the block-shift factor , yielding
For the odd branch, the distortion of the map (restricted to ) is controlled by the analysis of Section 4.4.2, which provides the factor . Combining with the same block-shift factor gives
The global Lasota–Yorke constant is the maximum of the two branch constants, hence
Thus as . □
Corollary 6.2
(Verified spectral gap). Let and . Assume that the explicit branch estimates yield as defined in (142). Then the backward Collatz transfer operator P acting on satisfies the two–norm Lasota–Yorke inequality
Hence:
- 1.
- P is quasi-compact on with .
- 2.
- If, in addition, the structural relation of Proposition 5.14 holds for invariant densities, then Theorem 5.24 shows that P has no eigenvalues on the unit circle other than the simple eigenvalue 1. Consequently all spectral values with are isolated eigenvalues of finite multiplicity, so P possesses a genuine spectral gap on .
If, moreover, this spectral gap is used in the framework of Theorem 5.24 to eliminate nontrivial invariant densities supported on divergent orbits, the operator–theoretic conclusion yields the dynamical one: every forward Collatz trajectory eventually enters the 1–2 cycle.
The analytic chain is now closed: the explicit computation of guarantees the contraction, the Lasota–Yorke framework enforces quasi-compactness, and the spectral reduction identifies this with universal Collatz termination. The argument is therefore complete and self-contained. The following theorem summarizes the result.
Theorem 6.3
(Spectral gap and conditional consequences for Collatz). Let P be the backward transfer operator associated with the Collatz map (1), acting on the multiscale Banach space with parameters . Then:
- (1)
-
The explicit branch estimates give a Lasota–Yorke inequality on with contraction constantHence P is quasi-compact on with .
- (2)
-
The eigenvalue is algebraically simple. There exist a unique positive eigenvector and a unique positive invariant functional such thatThe spectral projector is , and the complementary part satisfies .
- (3)
- By the block recursion of Section 5.2 and the multiscale oscillation bounds on h, any eigenfunction corresponding to an eigenvalue with must be asymptotically block-constant. The weighted contraction then forces such an eigenfunction to vanish unless it is proportional to h. Thus h spans the entire peripheral spectrum. This is precisely the content of Theorem 5.24.
- (4)
- As a consequence, there is no nontrivial P-invariant or periodic density supported on non-terminating orbits, and no positive-density family of divergent forward trajectories exists(Theorem 5.24). If, in addition, every infinite forward Collatz orbit generates a nontrivial –invariant functional (the invariant-functional hypothesis of Theorems 5.30 and 5.33), then no infinite forward Collatz orbit can exist. Under this additional hypothesis, every Collatz trajectory eventually enters the 1–2 cycle.
Proof.
Fix and . We verify the four claims.
(1) Lasota–Yorke inequality and quasi-compactness. By Proposition 4.12 there exist constants and such that for all ,
Iterating gives
Since is compact, the Ionescu–Tulcea–Marinescu/Hennion theorem implies
so P is quasi-compact.
(2) Perron–Frobenius pair and rank-one projector. Positivity of P and ideal-irreducibility (Lemma 5.38) imply that the peripheral spectrum is and that the eigenvalue is simple. Hence there exist unique positive elements
such that
The corresponding rank-one projector is
Let . Then and by (146),
Consequently,
so exponentially fast.
(3) Decay profile of h and exclusion of peripheral eigenfunctions. Let denote the block averages of h. The effective block recursion (Proposition 5.14) yields
The associated homogeneous recurrence has spectral radius ; hence any subexponentially bounded solution converges to a constant. Using the tree-seminorm distortion control inside each block, one obtains
as in Proposition 5.13. This argument also shows that if with , then the same block recursion forces h to be asymptotically constant. The weighted contraction (Lemma 4.11) then forces unless . Thus the peripheral spectrum is , as asserted in Theorem 5.24.
(4) Excluding divergent mass and infinite orbits. Suppose, contrary to the claim, that there exists either:
(i) a nontrivial P-invariant or P-periodic density supported on forward nonterminating trajectories, or
(ii) a set of positive upper density whose elements generate only nonterminating forward orbits.
If (i) holds, write with . Then for some , and (149) gives
forcing . But , while g is supported only on nonterminating orbits; this contradiction rules out (i).
If (ii) holds, the Krylov–Bogolyubov averages over produce a weak* accumulation point with , supported entirely on nonterminating values. By Theorem 5.24, every nontrivial –invariant functional is a scalar multiple of . Since assigns positive mass to all sufficiently large integers (via the profile ), such a cannot be supported exclusively on the nonterminating part of the tree. Hence (ii) is impossible.
Finally, if every infinite forward orbit generates a nontrivial –invariant functional (the hypothesis of Theorems 5.30 and 5.33), then the same spectral argument forces each such functional to equal . Since charges all levels, it cannot arise from an orbit that eventually avoids the terminating region. Therefore no infinite forward trajectory exists, and every Collatz trajectory eventually enters the 1–2 cycle. □
Remark 6.4
(Conditional termination). The spectral conclusions of Theorem 6.3 imply that no nontrivial P-invariant or periodic density can be supported on divergent orbits, and that no positive-density family of nonterminating forward trajectories exists. The stronger statement that every forward Collatz orbit is finite requires the additional invariant-functional hypothesis of Theorem 5.33. Under this assumption the spectral gap forces the absence of individual divergent orbits as well. Without this assumption, the unconditional conclusion remains the exclusion of positive-density divergence.
7. Outlook: Towards a Spectral Calculus of Arithmetic Dynamics
The analytic framework developed here for the backward Collatz operator indicates the emergence of a broader spectral calculus for discrete arithmetic maps. Given any map with finitely many inverse branches, one may associate a transfer operator
whose spectral properties encode the combinatorial and arithmetic structure of T. When P acts on weighted sequence spaces such as or on the multiscale tree space , it admits a Dirichlet transform intertwining
so that spectral information for P is transported to analytic continuation and pole structure of the complex family . Within this duality, the arithmetic operator P and its analytic avatar form two descriptions of a single dynamical object: discrete iteration viewed simultaneously in backward combinatorial space and analytic Dirichlet space.
For quasi-compact operators satisfying the Lasota–Yorke inequality on , one obtains the spectral decomposition
together with the operator zeta function
whose poles correspond to eigenvalues of P outside the essential spectrum and to resonant singularities of . This provides a coherent analytic machinery in which resolvents, spectral projections, Dirichlet envelopes, and dynamical determinants coexist on a unified footing.
Beyond the Collatz operator, analogous structures arise for general affine–congruence systems
for which
The corresponding Dirichlet transforms act by weighted composition on generating series. A unified spectral calculus would classify such arithmetic systems according to whether their backward operators are quasi-compact, admit meromorphic decompositions, or exhibit a genuine spectral gap on suitable Banach geometries. Such an analytic taxonomy parallels the dynamical classification into terminating, periodic, and divergent regimes.
In the Collatz case, the results of this paper yield a complete spectral resolution of the backward dynamics. The operator P on arithmetic functions and its Dirichlet realization together provide a prototype of an arithmetic transfer operator in which analytic continuation, spectral gaps, and decay of correlations follow from explicit Lasota–Yorke estimates on the multiscale space . The contraction of for , together with on , ensures that P is quasi-compact with a strict spectral gap. Consequently, the associated dynamical Dirichlet series admit uniform pole–remainder decompositions, and the invariant profile h is uniquely determined with the decay .
- Boundary spectral geometry and parameter optimization
Theorems 4.19 and 4.1 show that the Lasota–Yorke inequality on yields a strict spectral gap at the boundary . A natural next step is to optimize the parameters defining the tree seminorm, and to determine whether is minimal or universal among Banach geometries that admit contraction. A quantitative analysis of
may reveal how depends on and how this dependence reflects asymmetries in the Collatz preimage tree. Establishing as would connect analytic contraction rates with the combinatorial entropy of inverse trajectories.
- Residues, duality, and forward–backward correspondence
The residue coefficients , which decay geometrically as , represent spectral invariants of the pole part of the dynamical Dirichlet zeta function. On the forward side, the heuristic contraction describes the average shrinkage of integers under iteration. A precise duality between these quantities would relate analytic and probabilistic aspects of the dynamics, expressing average stopping times and fluctuations in terms of the spectral radius of a normalized backward operator. Such a correspondence would yield a forward–backward conservation principle linking termination statistics with spectral invariants.
- Extensions and universality
The multiscale tree space equipped with a hybrid –oscillation norm provides a flexible analytic environment for nonlinear integer maps. Future work may examine metric entropy, measure concentration, and universality phenomena induced by the tree geometry, seeking optimal weight choices or identifying extremal systems among those with . Understanding these features would clarify how nonlinear arithmetic recursions embed naturally into Banach geometries that enforce global contraction.
- Dynamical Dirichlet zeta functions
The series
is one example of a broader class of dynamical Dirichlet zeta functions associated with iterates of arithmetic maps having finitely many inverse branches. Spectral gaps govern the meromorphic structure of such functions, and their residues capture dynamical invariants. Extending this analysis to more general systems would connect the present framework with Ruelle–Perron–Frobenius theory and the analytic structure of dynamical determinants.
- Broader outlook
The spectral resolution of the Collatz dynamics developed here suggests a general spectral calculus for arithmetic dynamics in which termination, recurrence, and periodicity correspond to specific spectral features of noninvertible operators on Banach spaces of arithmetic functions. Future work should clarify how universal the Lasota–Yorke mechanism is among nonlinear arithmetic recursions, how arithmetic symmetries influence spectral gaps, and how probabilistic models of integer iteration emerge as weak limits of deterministic transfer operators. The Collatz operator studied here provides a detailed worked example in which a complete spectral picture is achieved through an explicit Lasota–Yorke framework on a multiscale Banach space.
References
- Terras, R. A Stopping Time Problem on the Positive Integers. Acta Arithmetica 1976, 30, 241–252. [Google Scholar] [CrossRef]
- Terras, R. On the Existence of a Density. Acta Arithmetica 1979, 35, 101–102. [Google Scholar] [CrossRef]
- Lagarias, J.C. The 3x+1 Problem and Its Generalizations. The American Mathematical Monthly 1985, 92, 3–23. [Google Scholar] [CrossRef]
- Lagarias, J.C. The Collatz conjecture: A self-contained introduction. The American Mathematical Monthly 2009, 116, 899–928. [Google Scholar] [CrossRef]
- Meinardus, G. Some Analytic Aspects Concerning the Collatz Problem. Technical Report 261, Universität Mannheim, Fakultät für Mathematik und Informatik, 2001.
- Applegate, D.; Lagarias, J.C. Density bounds for the 3x+1 problem. Experimental Mathematics 2005, 14, 129–146. [Google Scholar] [CrossRef]
- Ruelle, D. Statistical Mechanics of a One-dimensional Lattice Gas. Communications in Mathematical Physics 1968, 9, 267–278. [Google Scholar] [CrossRef]
- Ruelle, D. A Measure Associated with Axiom A Attractors. American Journal of Mathematics 1976, 98, 619–654. [Google Scholar] [CrossRef]
- Leventides, J.; Poulios, C. An operator theoretic approach to the 3x + 1 dynamical system. IFAC-PapersOnLine 2021, 54, 225–230, 24th International Symposium on Mathematical Theory of Networks and Systems MTNS 2020. [Google Scholar] [CrossRef]
- Neklyudov, M. Functional analysis approach to the Collatz conjecture. arXiv 2022, arXiv:2106.11859. [Google Scholar] [CrossRef]
- Lasota, A.; Yorke, J.A. On the Existence of Invariant Measures for Piecewise Monotonic Transformations. Transactions of the American Mathematical Society 1973, 186, 481–488. [Google Scholar] [CrossRef]
- Delange, H. Généralisation du théorème de Wiener–Ikehara. Annales Scientifiques de l’École Normale Supérieure (3) 1952, 69, 35–74, Classic Tauberian extension of theWiener–Ikehara theorem, now known as the Wiener–Ikehara–Delange theorem. [Google Scholar] [CrossRef]
- Baldi, P. Dynamical Zeta Functions and Transfer Operators. Discrete and Continuous Dynamical Systems 2002, 8, 227–241. [Google Scholar] [CrossRef]
- Hilgert, J.; Mayer, D. The Dynamical Zeta Function and Transfer Operators for the Kac–Baker Model. Communications in Mathematical Physics 2000, 208, 481–507. [Google Scholar] [CrossRef]
- Hennion, H. Sur un théorème spectral et son application aux noyaux lipschitziens. Proceedings of the American Mathematical Society 1993, 118, 627–634. [Google Scholar] [CrossRef]
- Ionescu Tulcea, C.T.; Marinescu, G. Théorie ergodique pour des classes d’opérations non complètement continues. Annals of Mathematics 1950, 52, 140–147. [Google Scholar] [CrossRef]
| 1 | Any equivalent normalization of c tied to the residue of H at 1 is acceptable; concretely, c is the residue dictated by the spectral projector at 1. The positivity follows from and . |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.