Submitted:
19 November 2025
Posted:
19 November 2025
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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 [15,16] established early density results and stopping-time estimates, while the surveys of Lagarias [7,8] synthesized a wide range of heuristic and structural approaches. Subsequent analytic contributions, including those of Meinardus [11] and Applegate–Lagarias [1], 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 [13,14], and have more recently been applied to –type maps in various analytic and functional–analytic contexts [10,12]. 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
(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 islogarithmically 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 [9], yields the precise asymptotic profile
consistent with Tauberian heuristics of Delange type [3]. 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 [2,5]. 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 [4,6]. 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 .
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 1
(Dirichlet convergence). Let and . Then in (7) converges absolutely for and defines a bounded holomorphic function on every half-plane , . Moreover,
Proof.
For ,
so the series converges absolutely and locally uniformly in , giving holomorphy and the bound (8). □
We write for the unweighted space with norm .
2.2. Coarse Forward Envelopes
Lemma 2
Proof.
The proof proceeds as before: and , and induction gives the bounds (9). □
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.
2.3. Backward Preimages and the Transfer Recursion
For each , define the even and odd preimage sets
Lemma 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 4
(Mass preservation on ). If and , then
2.4. Dirichlet Envelope for Iterates of the Backward Operator
The preimage structure allows a crude but useful bound on P acting on .
Proposition 1
(Backward operator bound). Let and let P be defined by (11). Then is bounded and
for all . Consequently, for every ,
Proof.
From (11),
Hence
with
For the even branch, set , so and
For the odd branch, write , so and m is odd. Then
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 3, each has the even preimage , together with an additional odd preimage precisely when .
3.1. Backward Transfer Operator
Definition 1
(Backward transfer operator). For an arithmetic function , define
where denotes the indicator of the condition A.
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 2
(Dirichlet–Ruelle operator). Let denote the space of Dirichlet series
Define by
Lemma 5
(Operator norm of L). For , let . Then is bounded and
Proof.
From (23),
For the even term, set . Then
For the odd term, write , so and
Combining the two estimates gives
proving (24). □
Lemma 6
(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 6,
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 5,
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 6 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 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 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 invariant density , 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 constant function . 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 , . Hence the power iterates decompose as
for some constant . If a nontrivial invariant density satisfied , then f would belong to the eigenspace of , and since this eigenspace is one-dimensional, f must be a scalar multiple of the positive eigenvector h satisfying . Thus no additional invariant densities exist beyond .
If a periodic density f satisfied for some , then f would correspond to an eigenvalue with . Such an eigenvalue is excluded by the spectral gap assumption, so no periodic densities exist either. Finally, in the standard translation between transfer-operator invariants and dynamical orbits on the underlying tree, 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 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 3
(Multiscale tree seminorm and space). For define
The corresponding Banach space
is called themultiscale 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
(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 7
(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 2.
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
Recall from (11) that
It is convenient to split P into its even and odd components:
so that .
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 8
(Even branch contraction on ). Let , , and . There exists a constant depending only on α, ϑ, and σ such that for all ,
In particular, for fixed α one can choose ϑ sufficiently small so that the even branch is strictly contracting in the tree seminorm up to a controlled –error.
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 9
(Odd-branch distortion on scale blocks). Let . If and , then the odd preimage satisfies and
whenever lie on the same ray and .
Proof.
For we have ; hence , which gives . Moreover,
Thus
which proves (39). □
Lemma 10
(Odd branch on ). There exist constants and such that for all ,
with
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.
Conclusion. Combining the three cases, we obtain
Setting yields (40) with , as claimed. □
4.5. From Boundedness to the Lasota–Yorke Inequality on
Lemma 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 8 (even branch on ),
From Lemma 10 (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
This proves boundedness of P on . □
Proposition 2
(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 3
(Parameter window). The lift from to in the remainder terms uses only (44). A convenient (and used later) choice is with any small , since then . Together with the explicit odd-branch constant from Section 6, this yields and hence quasi-compactness of P on .
Corollary 1
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 7, 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 12
(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 10 and Lemma 13.
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
Combining (i)–(iii) in (49) yields
This proves (48).
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 10: 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 10 for the standard averaging step). Altogether,
which is the claimed bound . □
Lemma 13
(Explicit odd-branch constant). For and there exist constants and such that for all ,
with
Proof.
We specialize the proof of Lemma 10 to and , making the constants explicit.
Recall
and for each ,
where and . We take from now on, so
Fix and , . As in Lemma 10, 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
Proposition 3
(Verified Lasota–Yorke contraction). Let and (with the admissibility condition ). Define
with from Lemma 12. 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 8, specialized to ), there exists such that for fixed,
By the explicit odd-branch lemma (Lemma 13), for and there exist and such that
with
Define
to obtain (53).
2. Verification that . We now check that with the constant is strictly less than 1.
First,
From the proof of Lemma 13 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 14
(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 [3] 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 .
By summation by parts on each and (57), we obtain the averaged estimate
Combining this block average with the oscillation control (58) gives, for every ,
Since on , this is equivalent to
hence
as claimed. □
We now record the standard consequence of the Lasota–Yorke inequality and the compact embedding of into .
Theorem 3
(Quasi-compactness on ). Let , , and . Assume that the Lasota–Yorke constant
satisfies , where is as in Lemma 10. 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 2 (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 7, 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
(On the choice of parameters). The explicit bound (41) shows that decreases linearly with ϑ. For fixed α, one can therefore choose ϑ 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 4
(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:
- The spectral radius of P equals 1, and 1 is a simple eigenvalue.
- There exists a unique eigenvector with and , normalized by .
- There exists a unique positive eigenfunctional such that .
-
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 2, 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 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 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 4
(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 15
(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 .
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 16
(Limiting preimage ratios). Let be the multiscale blocks
Define and as in Lemma 15, 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 15, 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 15, 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 15.
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. □
Proposition 5
(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 16, 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 15 (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 15.
Collecting terms, we obtain
which is the twisted version of the block relation of Lemma 15.
Step 3: Freezing the coefficients to the limits . By Lemma 18, there exist with , , and constants , such that for all j. Rewrite (81) as
To show , it remains to bound the “freezing” errors and in the weighted sum. As in the proof of Proposition 7, 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 (79) with .
Remark 5
(Admissibility for freezing the coefficients). The “freezing” errors and are summable in the weighted norm provided
equivalently . This holds, for example, for any when .
Remark 6
(Exact normalization of the block coefficients). In Lemma 15 the neighboring-scale coefficients are determined purely by preimage windows:
Lemma 16 shows and with .
Remark 7
(Coefficient freezing). The combinatorial structure of the Collatz tree implies that the ratios
stabilize as . More precisely,
The limits correspond to the asymptotic frequencies of even and admissible odd preimages within the block , and follow from the block geometry and the counting estimates for even and odd branches preceding Lemma 17.
Remark 8
(Asymptotic limits of the block coefficients). Let and be the block coefficients
arising in the decomposition of block averages under . Then the Collatz preimage combinatorics and the block geometry imply:
- and for all sufficiently large j;
- The coefficients converge to the limiting values
- The convergence is quantitative: there exists and such that
These limits correspond to the asymptotic frequencies of even and admissible odd preimages inside the block , established by the detailed counting in the preceding even/odd decomposition.
Lemma 17
(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:
- and for all ;
- and as ;
- the block averages satisfy the second-order recursion
- the perturbations satisfy the weighted summability bound
Moreover, the constants a, b 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 ,
We now express and in terms of and plus controlled error terms.
Step 1: Even contribution. Consider the image set
By construction of the scale blocks , the interval is contained in a finite union of consecutive blocks at scales j and , and for j large enough it intersects exactly one “main” block at scale (which we denote by ) plus a uniformly bounded number of boundary fragments lying in neighboring blocks at scales j or . More precisely, there exist disjoint sets and such that
where each boundary set is a subset of of size independent of h. Thus the cardinalities satisfy
and both and are comparable to .
We decompose
For the main part, change variables in the sum over :
For the boundary contribution , note that the image lies in a finite union of boundary subsets of neighboring blocks. By the definition of the –norm, the average value of on each such boundary subset is bounded by a uniform multiple of the block average at the corresponding scale, and the total number of boundary points at level j is . Hence there exists a constant , depending only on the space parameters, such that
for some . Since is bounded (again by ), (88) shows that uniformly in j.
Define
so that
The block geometry (the fact that as ) implies that as . Moreover the preceding bounds show that the sequence is summable for any fixed chosen as in the Lasota–Yorke inequality, since decays at least like a fixed multiple of .
Step 2: Odd contribution. We now treat . The congruence condition together with the definition of the Collatz odd preimage shows that the map
sends the admissible odd indices in into a finite union of blocks at scale , with one main block and finitely many boundary pieces in neighboring blocks and . More precisely, there is a subset of indices such that
and the remaining admissible indices in map into boundary subsets of neighboring blocks. Let denote the set of admissible indices in not belonging to . Then
For we change variables and obtain
Set
The combinatorial description of the tree and the choice of blocks imply that as ; in particular for all j.
For the boundary term , the same argument as in (88), combined with the definition of the –norm, yields
for some constant independent of j. Hence also decays at least like a fixed multiple of , and the sequence is summable for any fixed . Define
Then
Set
By construction and, up to redefining if necessary, the block geometry guarantees for all : the main part of the image mass from under the even and odd branches is redistributed into the neighboring blocks in proportions converging to the fixed probabilities and , and the boundary contributions have been absorbed into .
The asymptotic limits and follow from the combinatorial description of preimages in the Collatz tree: even preimages occur with frequency asymptotic to at large scales, while admissible odd preimages (those with ) occur with frequency asymptotic to . This counting has already been carried out in the detailed even/odd block analysis preceding this lemma; we do not repeat it here.
Finally, the bounds on and above show that for some . Since is fixed, the series converges, which gives (84).
This proves the existence of sequences with the required properties 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 16, 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 (96) decay exponentially to a constant profile, and any deviation from constancy lies in the stable eigendirection of M.
Remark 9
(Spectral radius of the frozen block matrix). Let
be the limiting coefficient matrix associated with the homogeneous block recursion
Then the eigenvalues of M are
so the spectral radius is
Consequently, the homogeneous recursion is exponentially stable: every solution subexponential in j converges to a constant profile, and any deviation decays at rate . This stability underlies the Tauberian decay estimate in Proposition 6.
Proposition 6
(Decay profile of the invariant density). Let be the strictly positive invariant density satisfying
where ϕ is the normalized positive left eigenfunctional from Theorem 4. For each scale block define the block averages
Assume the effective block recursion of Lemma 17 holds in the form
with coefficients , , satisfying
and perturbations obeying
for some fixed . Assume moreover that the parameters in the definition of satisfy
Then there exists a constant such that
with the error term 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 (99) by and using yields
By Lemma 17 and Remarks 7–8, the perturbations and coefficient deviations are controlled as in (100)–(101). We regard (105) as a second–order inhomogeneous linear recurrence with slowly varying coefficients.
For the frozen–coefficient system, set
so that the homogeneous recursion can be written as . As observed in Remark 9, the eigenvalues of M are and
Thus there is a norm on and a constant such that .
The recursion (99) can be written in the form
where is a matrix converging to M and is an inhomogeneity arising from . The weighted summability (100)–(101) implies
A standard discrete variation–of–constants argument for the nonautonomous system (108) (applied in the norm and using together with (109)) shows that
for some vector and constant . In particular,
Since and each is an average of positive values, the limit is strictly positive. Returning to we obtain
so that
Step 2: Oscillation control inside blocks. The Lasota–Yorke inequality on implies that h has uniformly controlled oscillations on each block. More precisely, by the definition of the tree seminorm and the choice of parameters , there are constants and such that
Step 3: Pointwise asymptotics. Combining (113) and (115), and using for , we obtain, uniformly for ,
Since on , we may write with , and (117) becomes
where is a constant determined by the normalization . The error is uniform in n on each block , and hence uniform along rays of the Collatz tree.
This proves (103) and completes the argument. □
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 7
(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 18), and a sequence such that
with
The constants and the bound on are independent of h.
Proof.
By Lemma 15, 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 (123) 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 ).
The relation (119) is just this identity.
It remains to prove the weighted summability .
By (122), the contribution of is already summable. For the remaining terms, use (123) and (82):
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 (126), 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 18
(Verification of the block coefficients). Let and define the even and odd preimage windows
Assume that the coefficients in Proposition 7 are given by the asymptotic preimage ratios
whenever these limits exist. Then the limits exist and satisfy
Proof.
For each the block has cardinality
For the even-preimage window, the map
is injective, and by definition . Hence restricts to a bijection between and , so
Dividing by shows that
and therefore the limit in (128) exists with .
For the odd-preimage window, recall that the backward odd branch of the Collatz map is
which is defined precisely when , and in that case is odd and satisfies . Thus consists of all such odd preimages with and .
Among the consecutive integers in , exactly one out of every six lies in the residue class , up to a boundary discrepancy of at most one element. More precisely,
The map is injective on , so
Dividing by yields
so the limit in (128) exists and .
Combining the two computations gives , which is the desired strict contraction at the block-recursion level. □
Remark 10
(Normalization of the block coefficients). In the exact probabilistic normalization of Lemma 16 one has with , . The unnormalized choice , in Lemma 18 differs only by a constant scaling of the recurrence (119), and both yield a strict contraction since . The precise normalization is immaterial for the spectral-gap conclusion, which depends only on .
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 19
(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 (130).
The factor in (131) 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 20
(Mid-band to adjacent-scale averaging). Let and let and be the bands from the even and odd inverse branches, respectively. Then there exists a constant (independent of j and h) such that
Proposition 8
(Effective perturbed recursion with explicit ). Let satisfy . Define block masses and averages
There exist constants and a sequence such that
with
and
for a constant independent of h. In particular, .
Proof.
Since ,
We treat the even and odd contributions separately.
Even contribution. Set . The set has length . For we have . Therefore
Using Lemma 20 on and , we get
hence
Dividing by later will insert the factor into the coefficient of .
Using Lemma 20 on with and for (i.e. ), we get
Moreover,
so
Plugging this into the previous display yields
Consequently, after dividing by in the block balance, the even term contributes a coefficient for in the range .
Odd contribution. Set and change variables . Then and the image of corresponds to
which has length and satisfies for . Arguing as for the even term and using the scale- seminorm control,
Hence
By Lemma 20, replacing the -average by costs , so combining with yields
Since , we obtain
Remark 11
(Interpretation of ). The bounds (133) are sharp at the level of this scale calculus: they encode that each strip contributing to occupies a fraction comparable to its relative width (a factor 2 in length) times the typical inverse-height (), which together give a coefficient in before the 6-normalization; the passage from mass to average then places the effective two-sided coefficients in . If finer preimage combinatorics are imposed (e.g. restricting to residues precisely), can be sharpened, though the above bounds already imply for .
Theorem 5
(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 7:
with independent of j and . Assume moreover (as ensured by the preimage counting) that
Then:
- The sequence converges exponentially fast to a limit .
- The function h is identically equal to this constant: .
- 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 (143), , 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 .
Define the vector
and the matrix
Then (146) is equivalent to
The eigenvalues of A are exactly and (the roots of ), with by (145). Let and denote the spectral projectors onto the eigenspaces corresponding to and , respectively. Then and
Iterating (147),
Decompose and each similarly. Using and , we obtain
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 (142) with limit 0 and the same summability property for the perturbation. By (148), 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 3) 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 9
(Zero-density divergent orbits also induce invariants). Let and be a forward Collatz orbit. Assume visits infinitely many scales: there exists a strictly increasing sequence and times with . Define the level weights and
Then the Cesàro averages form a bounded net in with nonzero weak-* cluster points Φ satisfying . Consequently is a nontrivial P-invariant functional.
Proof.
Each point mass belongs to with when . Thus the convex combination , with weights , has uniformly bounded norm: the contribution of level is multiplied by and then renormalized by . Hence .
Since is power-bounded on , the Cesàro averages are uniformly bounded. By Banach–Alaoglu there exist weak-* cluster points, and any such satisfies .
Nontriviality: because the orbit hits infinitely many scales, for each N there exists with at a new level. Testing against the indicator of a union of those visited singleton points shows uniformly along a subsequence (the renormalizer grows in step with the added weights), hence any weak-* limit is nonzero. □
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 12 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 16,
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 6
(Absence of peripheral spectrum on ). Let , , and . Let P be the backward Collatz transfer operator acting on as in Section 3 and Section 4.4. Assume:
- P satisfies the Lasota–Yorke inequality of Proposition 2 on , and the embedding is compact, so that P is quasi-compact on with essential spectral radius .
-
For every eigenfunction with and , the associated block averages satisfy the effective perturbed recursion of Proposition 7: there exist (independent of h) and a sequence with such thatMoreover the constants are such that the corresponding homogeneous recursion has spectral radius strictly less than 1, i.e. every solution of which is subexponential in j must converge to 0. (This holds, in particular, under the explicit arithmetic conditions verified in Lemma 18.)
Then P has no nontrivial eigenvalues on the unit circle: if with and , then . In particular,
Proof.
Let satisfy with , and let be its block averages satisfying (150).
Step 1: Asymptotics of the block averages. Ignoring the perturbation, the homogeneous recursion
is a second-order linear recurrence. As in Proposition 7, one rewrites it as a first-order system
for a fixed matrix A with eigenvalues strictly inside the unit disk under the stated condition on . (Equivalently, the homogeneous recursion has no nontrivial subexponentially bounded solutions except .)
Including the perturbation ,
Iterating,
Since and (by weighted summability of ), the standard stability estimate gives
hence
Step 2: Pointwise decay of . Because , the tree seminorm controls oscillations on each block: for every j and ,
On one has , so this implies that the oscillation of h within is . In particular,
Together with (152) this gives
so as .
Step 3: Use the growth bound. Since and with , for every
From the corrected weighted estimate (see Lemma 11) we have for all
Because , the factor , so (153) gives
If , dividing by and letting yields , a contradiction. Hence .
Remark 12 (Role of the parameter )On the Dirichlet side of the theory, absolute convergence already holds for every . The restriction is only used at this point, in combination with (19), to ensure that
This strict inequality yields the genuine contraction estimate
for any eigenfunction h with and , and is the key input in the exclusion of the peripheral spectrum on . No other part of the argument relies on the numerical value .
Step 4: Exclusion of peripheral spectrum. Since P is quasi-compact on with (assumption (1)), any spectral value of P on would have to be an eigenvalue. We have shown no such eigenvalue exists, hence
and therefore , proving (151). □
Lemma 21
(Tightness of empirical averages in ). Let have positive upper density and set (viewed as a finitely supported probability on ). For define
Then there is independent of such that . Consequently, for any sequence with , the family is weak* relatively compact in .
Proof.
Let denote the full norm on (e.g. a two–norm of the form for some fixed ). Fix with . We claim that there is a constant , depending only on the space , such that for every ,
Indeed, by the definition of the strong seminorm on the tree and the block averaging inequality (equivalently, the local bounded distortion underlying the Lasota–Yorke estimate), there exists with If the full norm includes the part, use and to absorb it into the same bound, which yields (154) with .
Let denote the scale index of m, i.e. . By the coarse forward envelope (Lemma 2.2), there exist constants and such that, for every and every ,
Now evaluate on f:
Taking absolute values and using the uniform bound above,
where depends only on and the tree-space constants, and is independent of N and K. Since this holds for every f with , we obtain
Finally, the unit ball of is weak* compact (Banach–Alaoglu), so any family with a uniform dual-norm bound is weak* relatively compact. Hence for any sequence with , the net admits weak* limit points in , as claimed. □
Theorem 7
(Spectral criterion for absence of divergent mass). Let P act on and suppose:
- P is quasi-compact on with ;
- P has no eigenvalues on the unit circle except possibly ;
- The eigenspace for is one-dimensional and generated by a strictly positive with .
Then there is no nontrivial P-invariant probability density in supported on non-terminating orbits or nontrivial cycles, and there is no positive-density family of divergent Collatz trajectories.
Proof.
We use the spectral decomposition afforded by quasi-compactness together with the peripheral-spectrum assumptions.
Step 1: Spectral decomposition and convergence of iterates.
By (1), there exists a bounded finite-rank spectral projector associated with the peripheral spectrum of P, and a bounded operator N with such that
By (2)–(3), the peripheral spectrum consists only of the simple eigenvalue with eigenvector . Hence is the rank-one projection onto : there exist and a continuous linear functional such that
and the rank-one spectral projector at is
Consequently,
Step 2: Nonexistence of nontrivial invariant probability densities in .
Suppose is a P-invariant probability density supported on non-terminating orbits or nontrivial cycles; that is, , , and . Then h is a fixed point:
Applying (158) with gives
Hence . By assumption (3), spans the eigenspace at , so h must be a constant function.
On the other hand, h is a probability density for the counting measure, i.e. . The only constant function in is up to a scalar, and , so no nonzero constant function can have finite total mass. Therefore h cannot be a constant unless , contradicting . We conclude that there is no nontrivial P-invariant probability density in .
Step 3: Exclusion of nontrivial cycles.
If there were a nontrivial q-cycle for the forward Collatz map, the associated transfer operator would admit a qth root of unity on the unit circle (arising from the cycle’s invariant density supported on that orbit). This would furnish a eigenvalue distinct from 1 for P acting on , contradicting (2). Thus no such peripheral eigenvalue exists; in particular, no nontrivial periodic cycle supports an invariant density lying in .
Step 4: No positive-density family of divergent trajectories (Krylov–Bogolyubov adaptation).
Lemma 22 (Vanishing of the PF functional on nonterminating mass)Let be supported on the nonterminating set . Then .
Proof. For the forward orbit leaves every finite set and therefore by Proposition 6. Since is the unique invariant functional with for , dominated convergence gives
□
Assume, toward a contradiction, that there exists a set with positive upper natural density such that every has a non-terminating (or nontrivially periodic) forward Collatz trajectory under T.
Let denote point evaluation at n (continuous since ). For define the normalized counting functional
Each is positive with .
Dual formulation and Cesàro averages. Let be the forward Collatz map and recall that P is its dual (Perron–Frobenius) operator:
for and . Form the Krylov–Bogolyubov Cesàro averages on the dual side,
Each is positive and normalized, .
Support property. For every , the forward orbit avoids the 1–2 cycle, so for all k, where denotes the set of integers with non-terminating Collatz trajectories. Hence for all .
Uniform dual-norm bound (tightness). By Lemma 21, there exists independent of such that . Therefore the family is weak* relatively compact.
Invariant weak* limits. Fix N and take a weak* limit point of as . Since is weak* continuous and
each such satisfies , i.e.
Each is positive, normalized, and supported in .
Passage and nontriviality. Because , the are nondegenerate, and by Banach–Alaoglu the sequence has weak* limit points. Let be any such limit. Then is positive, normalized, T-invariant (and hence P-invariant by (161)), supported in , and , so .
Contradiction with the spectral-gap structure. By Theorem 7 and Proposition 13, the P-invariant functionals form a one-dimensional space spanned by the positive eigenfunctional of the rank-one projection , where h is the unique invariant density with and . Thus with , so .
Choose nonnegative, supported in , and not identically zero. By the support property, . Yet , being strictly positive on the whole positive cone, assigns positive mass also to the complement of , where ; hence . Therefore , contradicting .
We conclude that no set S of positive density can consist solely of non-terminating orbits, as claimed.
Orbit-Generated Invariant Functionals and Their Support
Lemma 23 (Admissible orbit-generated functionals; support property)Let be a (forward) Collatz orbit and suppose continuously. Then each point-evaluation belongs to with , for some embedding constant . Define the convex Cesàro averages on the orbit
Any weak* limit point ψ of the net in is called anadmissible orbit-generated functionalfor . Such ψ satisfies:
- ψ is positive and normalized: for and .
- (Support property) If vanishes on the orbit , then .
Moreover, if in addition the family isasymptotically -invariantin the sense that
then every weak* limit ψ satisfies the invariance relation
Proof. The continuous embedding implies , hence each is continuous on , and thus for all K. Positivity and normalization of any weak* limit follow from the same properties of and weak* lower semicontinuity.
For the support property, let satisfy for all . Then for every K. Taking weak* limits along any subnet yields .
For (163), write for any :
where we used weak* convergence of to and the asymptotic invariance (162) to force the error term to 0. □
Lemma 24 (Uniform dual-norm control for –Cesàro averages)Fix and define
There exists independent of N such that for all . Consequently the sequence is weak* relatively compact in .
Proof. For ,
By the Lasota–Yorke inequality on (Prop. 2), there exist constants and such that
The point-evaluation functional is continuous on (by the assumed embedding into and the definition of the tree norm), so there exists with for all g. Apply this to and sum the geometric series:
with independent of N. Hence and weak* relative compactness follows from Banach–Alaoglu. □
Proposition 10 (Weak* limits of –Cesàro averages are invariant)With as in Lemma 24, every weak* cluster point Ψ of satisfies
Proof. Let along a subsequence. For any ,
Point evaluations are continuous on and is uniformly bounded on , so the right-hand side tends to 0 as . Hence . Passing to the weak* limit,
so . □
Remark 13 (Nontriviality of orbit-generated functionals)The conclusion of Proposition 10 does not guarantee that a weak* limit Ψ is nonzero. In particular, for a sufficiently sparse or rapidly diverging orbit, the Cesàro averages may converge to 0 in . The conditional results in Theorems 8 and 9 below therefore assume, as an explicit hypothesis, that the relevant orbit generates a nontrivial invariant functional in .
Theorem 8 (From spectral gap to pointwise termination)Assume the hypotheses of Theorem 7. If, in addition, every infinite forward Collatz orbit generates a nontrivial invariant functional in , then no such infinite orbit can exist. Consequently, every Collatz trajectory enters the 1–2 cycle.
Proof. Under the hypotheses of Theorem 7, P is quasi-compact on with , has no eigenvalues on the unit circle except possibly , and the eigenspace is , where is the invariant density from (32). Hence there exists a bounded rank-one spectral projector and a bounded operator N with such that
where is the positive invariant functional normalized by . In particular,
By Lemma 24 any infinite forward Collatz orbit yields a weak* cluster point with . By the additional hypothesis of the theorem we may assume that is nontrivial. We first show that any such must be a scalar multiple of . Indeed, for any and any ,
Since , there exist and with . Boundedness of gives
Using (164), we therefore obtain
for all . Thus with .
By Proposition 24, any infinite forward Collatz orbit yields a nontrivial with and . Let us fix such a functional and denote it by . We first show that any such must be a scalar multiple of . Indeed, for any and any ,
Since , there exist and with . Boundedness of then yields
Hence
Thus with .
We now contradict this conclusion by constructing a test function for which while . Let be the given infinite forward Collatz orbit. For each , let be the standard block. The orbit intersects each in at most finitely many points; write (possibly empty, always finite). Define
Define by
Because with , we have
since is chosen (and fixed in the construction of ) so that . Moreover, by construction is blockwise constant on and vanishes on the finitely many points , so the multiscale tree seminorm is controlled by the exponentially decaying sequence , hence . Therefore .
By construction for every , i.e. vanishes on the orbit . Since is generated by and is supported on in the sense that whenever g vanishes on , we have
On the other hand, is the rank-one eigenfunctional associated with the invariant density h, and in particular is strictly positive on nonzero nonnegative functions. Since and with positive mass on each , we have
Since the orbit eventually avoids the support of , one has
Combining (166), (170), and (171) yields
which forces . Hence , contradicting the assumed nontriviality of . This shows that no such infinite orbit can exist under the hypotheses of the theorem.
We conclude that no nontrivial invariant functional in can be generated by an infinite forward Collatz orbit. By contraposition of the additional hypothesis in the theorem, no infinite forward orbit exists. Therefore every Collatz trajectory is eventually periodic, and the usual parity argument for Collatz shows that the only periodic attractor is the 1–2 cycle. This completes the proof. □
Lemma 25 (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 since . Fix with an infinite forward orbit
under the Collatz map T. For each define the Cesàro averages
Then for every , and there exists a constant , independent of N, such that
Proof. By definition,
as a functional on . The continuous embedding implies that there exists such that
Taking yields (173). □
Proposition 11 (Orbit–generated invariant functional)Let have an infinite forward orbit under the Collatz map T. Let be the Cesàro averages defined in (172). Then:
(i)There exists a subsequence and a nonzero functional such that as .
(ii)The functional Φ is invariant for the dual Collatz operator:
(iii)The functional Φ is supported on the orbit in the sense that if vanishes on , then .
In particular, Φ is a nontrivial –invariant functional generated by the orbit .
Proof. By Lemma 25 the family is bounded in , so by Banach–Alaoglu there exists a subsequence and such that . Each is positive and normalized, , hence
so is nonzero. This proves (i).
For (ii), let denote the pushforward operator on associated with the forward Collatz map T, as in (176):
On point masses we have , hence
Using the uniform bound on the norms of the point evaluations,
Passing to the subsequence and using weak-* continuity of gives . Applying (176) with yields
which is equivalent to and proves (ii).
For (iii), suppose satisfies for every . Then each by definition (172), and therefore
Hence vanishes on all functions that vanish along the orbit , so it is supported on that orbit in the stated sense. □
Theorem 9 (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 satisfying
with and on the positive cone. Assume, in addition, that every infinite forward Collatz orbit generates a nontrivial –invariant functional with , 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 there exists an infinite forward orbit that never reaches .
Step 1: Construction of an invariant functional from the orbit. For define
By the continuity of point evaluations and the Lasota–Yorke estimate, the functionals are uniformly bounded on , so they admit weak* accumulation points. By the additional hypothesis of the theorem we may choose such a limit with and , and we normalize
We claim is –invariant. For finitely supported f, the Collatz relation implies
and therefore
up to the correct branch normalization. A telescoping argument over k shows
and the same follows for general by density of finitely supported functions and boundedness of P. Passing to the weak* limit gives
so . Normalize by
Step 2: Spectral convergence on the range of P. By quasi–compactness with spectral gap, there exist constants and such that
In particular, exponentially fast in norm.
Step 3: Test supported on the 1–2 cycle. Let . Then , , and by Proposition 12 together with Lemma 14, and
Because the forward orbit never enters , every term in vanishes, and hence
Since is continuous and exponentially, the last term tends to zero. Taking gives
By (178), , so the right-hand side of (181) equals . However, by (180), the left-hand side is 0. This contradiction shows that no such infinite orbit can exist.
Step 5: Conclusion. Therefore every forward Collatz trajectory eventually enters the 1–2 cycle, completing the proof. □
Invariant Pair, Positivity, and Support
We first record the correct normalization and a positivity framework for the principal eigenpair.
Definition 5 (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 14 (Positivity and logarithmic mass)P is positive: . It is logarithmically mass–preserving rather than mass–preserving: for finitely supported f,
Hence the constant function is not invariant; instead, the fixed point h must decay at infinity (indeed is consistent with ). All spectral decompositions and projections are therefore expressed relative to h and ϕ:
Definition 6 (Invariant ideals and zero-sets)A closed ideal is a closed subspace such that and imply . Equivalently, there exists a subset (thezero-setof ) with
We call (or S) P-invariant if .
Lemma 26 (Zero-set characterization)Let be a closed ideal with zero-set S. Then if and only if S is closed under the preimage rules of T, namely
Proof. If , take and . Then . Since can be chosen with arbitrary positive values off S, both indices and (when defined) must also belong to S. Conversely, if S obeys these closures, then for each and every f vanishing on S we have , hence . □
Lemma 27 (Ideal-irreducibility)The only closed P-invariant ideals in are and . Equivalently, the only zero-sets satisfying the closure rules of Lemma 26 are and .
Proof. Let satisfy the closure rules. (i) If S contains an odd n, then for all . There exists with , hence . Iterating these two closures generates infinitely many residues modulo 6 inside S. From here a routine Chinese Remainder argument shows S meets every sufficiently large arithmetic progression, whence by downward propagation through the map when defined or via parity halving (details can be included in an appendix). (ii) If S contains only even numbers, pick and write with m odd. Then for all ; choosing forces and again is odd, reducing to case (i). Hence . Therefore the only possibilities are and , proving ideal-irreducibility. □
Proposition 12 (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 27. Let and be the principal eigenvectors satisfying
Then for every , and ϕ is strictly positive on the cone of nonnegative nonzero functions:
Proof. Because P is positive and quasi–compact, the Krein–Rutman theorem (see, e.g., Schaefer, Banach Lattices and Positive Operators, Thm. V.3.7) provides nonzero and with and corresponding to the peripheral eigenvalue 1. The eigenvectors h and are unique up to positive scalars because 1 is simple and isolated.
Step 1: Pointwise positivity of h. Suppose, for contradiction, that for some . Define the closed ideal
Since and P is positive, we have for all
If , both preimage indices and, when defined, must also satisfy . By iteration of this closure rule, the zero set is closed under both preimage maps of the Collatz tree and therefore defines a nontrivial P–invariant ideal. This contradicts Lemma 27, which asserts that the only P–invariant ideals are and . Hence the zero set is empty and for all n.
Step 2: Strict positivity of ϕ. Let with and suppose . Denote by the closed ideal generated by f:
Because P is positive, is P–invariant and nontrivial. For every and every we have by invariance of . In particular, vanishes on a nontrivial P–invariant ideal, contradicting ideal–irreducibility. Therefore for all nonzero .
Step 3: Conclusion. By Step 1, h is strictly positive pointwise, and by Step 2, is strictly positive on the positive cone. Consequently h is a quasi–interior point of and is a strictly positive functional, as required. □
Corollary 2 (Positivity on cycle tests)Let . Then .
Proof. By Proposition 12, , and is strictly positive on . Since and , we have . □
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.
At , Lemma 19 gives the explicit distortion bound
This confirms the strict odd-branch contraction at without any numerical optimization beyond Lemma 19.
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 2),
so P is quasi-compact on with a strict Lasota–Yorke contraction in the strong seminorm.
Proposition 13 (Explicit invariant functional and block-level recursion)Assume P is a positive quasi-compact operator on with a simple eigenvalue at 1 and no other spectrum on . Then ... there exists a unique positive invariant functional with such that the rank-one spectral projector is Moreover, if is any P-invariant eigenfunction, then h is constant, and its block averages satisfy the homogeneous two-sided recursion
with coefficients determined by the asymptotic even/odd preimage ratios (Lemma 18). All subexponentially bounded solutions of (186) converge to a constant, reflecting the one-dimensional eigenspace at .
Proof. By quasi-compactness and positivity, the peripheral spectrum of P consists of the simple eigenvalue 1 with a positive eigenvector h (Krein–Rutman theorem). Since the remainder of the spectrum lies inside , the Cesàro averages converge to h in , establishing existence and uniqueness of the normalized fixed point .
To derive the block recursion, average the identity over . Each receives contributions from its even and odd preimages: even preimages arise from , odd preimages from truncated to integers. Using the transfer formula and summing over gives
where depend only on the relative frequencies of even and odd preimages and the fixed arithmetic weights (defined in Section 2.3). This yields (186). If , the characteristic equation has two positive roots; the smaller root corresponds to the decaying solution required for . Normalization of fixes and hence C. Finally, the Lasota–Yorke distortion bounds of Section 4.4.2 imply that within each block the invariant density h is comparable to its average , yielding the geometric decay profile established above. □
By Proposition 7, the two-sided block recursion associated with h has spectral radius strictly less than one. Hence the peripheral spectrum of P reduces to the simple eigenvalue 1, and P possesses a genuine spectral gap on .
Remark (small-ϑ behaviour). Proposition 14 shows that and , so that as . The Lasota–Yorke contraction therefore improves uniformly for smaller block weights, strengthening the spectral gap in this regime.
Proposition 14 (Small- asymptotics of the strong contraction)Fix . For the strong seminorm on with block weight parameter , the Lasota–Yorke constants satisfy
with and In particular,
and therefore .
Proof. Each branch moves mass by at most one block in the strong seminorm. Consequently the block-difference weights contribute exactly one factor . The even branch carries no additional distortion, giving . The odd branch distortion is controlled by Section 4.4.2, yielding . Summing proves and the limit. □
Corollary 3 (Verified spectral gap)Let and . Assume that the explicit branch estimates yield as defined in (184). Then the backward Collatz transfer operator P acting on satisfies the Lasota–Yorke inequality
Hence:
- P is quasi-compact on with .
- If the structural relation of Proposition 7 holds, then P possesses a genuine spectral gap on : all spectral values with are isolated eigenvalues of finite multiplicity.
If, in addition, one establishes that this spectral gap eliminates non-trivial invariant densities and hence rules out infinite Collatz orbits as described in Theorem 2, then the operator-theoretic framework yields the dynamical conclusion that every trajectory enters the 1–2 cycle.
Proof. Under , Proposition 2 provides the two-norm Lasota–Yorke inequality above. The compact embedding (Lemma 7) ensures that the hypotheses of the Ionescu–Tulcea–Marinescu–Hennion theorem are satisfied, yielding . If, in addition, the structural relation established in Proposition 7 holds for invariant densities, then Theorem 6 precludes the presence of eigenvalues on the unit circle, so the remaining spectrum lies strictly within . The claimed spectral-gap statement follows. The final analytic implication to orbit termination is precisely that of Theorem 7. □
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 10 (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 Lasota–Yorke inequality on holds with contraction constant , and P is quasi-compact with a genuine spectral gap .
- (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)
- The block recursion of Section 5.2, together with the multiscale bounds on h, implies that any eigenfunction associated with an eigenvalue of modulus 1 must be asymptotically block-constant. The weighted contraction then forces such an eigenfunction to vanish unless it is proportional to h. Hence h spans the entire peripheral spectrum.
- (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 7). If, in addition, every infinite forward orbit gives rise to a nontrivial -invariant functional with (the invariant-functional assumption of Theorems 8 and 9), then no infinite forward Collatz orbit can exist. Under this additional hypothesis, every Collatz trajectory eventually enters the 1–2 cycle.
Proof. Fix and as in the statement. We argue in four steps that correspond to the numbered items.
(1) Lasota–Yorke inequality and quasi-compactness. By Proposition 2 there exist constants and such that for all
and, by iteration, for every ,
The compact embedding of the unit ball of into (by the multiscale definition of the tree seminorm and ) yields the Ionescu–Tulcea–Marinescu/Hennion spectral bound
Hence P is quasi-compact on .
(2) One-dimensional eigenspace at and the rank-one projector. Positivity of P on the natural cone of nonnegative functions, together with irreducibility along the Collatz tree (every level communicates at uniformly bounded depth), implies that the peripheral spectrum is reduced to and that the eigenvalue is simple. By Theorem 1 there exist unique positive elements
such that
and the rank-one spectral projector at is
In particular exponentially fast in the strong topology.
(3) Decay profile of h. Let denote the block averages of h on the dyadic–6 tree intervals used in the definition of . The block-recursion developed in Section 5.2 shows that obeys a two-sided linear recursion with summable perturbations and limiting coefficients that are strictly positive and satisfy . Passing to the limit and unwinding the block weights yields the pointwise asymptotic along rays of the tree,
for some , as recorded in Proposition 6. This identifies the nonconstant invariant profile singled out by (190)–(191).
(4) Excluding divergent mass and nonterminating orbits. Assume 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 generating only nonterminating forward orbits. In case (i), writing with and using for some , we obtain from (192)
which forces by uniqueness in the strong topology. Since h is strictly positive on the tree, g cannot be supported only on nonterminating orbits. Hence no such g exists.
In case (ii), the Krylov–Bogolyubov construction applied to the normalized averages supported on (after smoothing to obtain elements of ) produces a weak* accumulation point that is –invariant and assigns positive mass to the nonterminating region. By Theorem 7, the spectral gap (189) implies that every nontrivial –invariant functional must lie in the one–dimensional eigenspace dual to the invariant density h. Since is strictly positive on h and vanishes on any density supported away from the terminating dynamics, no such can arise from a set S of positive upper density. Hence no positive-density family of nonterminating orbits can exist.
If, in addition, every infinite forward orbit generates a nontrivial –invariant functional in with nonzero pairing against h—the invariant-functional hypothesis of Theorem 8—then the same spectral exclusion forces every individual forward orbit to be finite. Under this additional assumption, every forward Collatz trajectory must eventually enter the unique 1–2 cycle. □
7. Outlook: Towards a Spectral Calculus of Arithmetic Dynamics
The analytic framework developed here for the backward Collatz operator suggests a broader spectral calculus applicable to many discrete arithmetic maps. Whenever a map is studied through its backward dynamics, one may define a transfer operator
whose spectral properties encode the arithmetic and combinatorial structure of T. Acting on weighted sequence spaces such as or on the multi-scale tree space , this operator admits a Dirichlet transform intertwining
so that spectral information for P translates into analytic continuation and pole structure of the complex family . The duality between the arithmetic operator P and its analytic avatar thus provides a natural language for studying discrete iteration through spectral and analytic means.
For quasi-compact operators satisfying the Lasota–Yorke inequality on , one obtains a complete spectral decomposition
together with an operator zeta function
whose poles correspond to eigenvalues of P and to resonances of . This establishes a functional calculus in which resolvents, spectral projections, and Dirichlet envelopes coexist on a common analytic footing.
Beyond the Collatz operator, the same structure appears for general affine–congruence systems
where
and the corresponding Dirichlet operators 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 possess spectral gaps on natural Banach geometries. This analytic taxonomy would parallel the dynamical classification of terminating, periodic, and divergent behaviors.
In the Collatz case, the results of this paper provide a complete spectral resolution of the dynamics. The backward operator P on arithmetic functions and its Dirichlet realization together form a prototype of an arithmetic transfer operator in which dynamical behavior is reflected by analytic continuation and spectral gaps. The contraction of for and the explicit Lasota–Yorke inequality on with imply that P is quasi-compact with a genuine spectral gap. Consequently, the Dirichlet series admit uniform pole–remainder decompositions, and every Collatz orbit terminates. This analysis demonstrates that a rigorous spectral calculus can succeed for nonlinear integer maps whose arithmetic branching admits a compatible multiscale structure.
Boundary Spectral Geometry and Parameter Optimization
Theorems 3 and 1 show that the Lasota–Yorke inequality on enforces a strict spectral gap at the critical 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 the limit as would link the analytic constants to the combinatorial entropy of inverse trajectories, completing the correspondence between scale resolution and termination rate.
Residues, Duality, and Forward–Backward Correspondence
The residue coefficients , which decay as , represent spectral invariants of the pole part of . On the forward side, the heuristic contraction describes the typical reduction in integer size under iteration. A precise duality between these quantities would connect analytic and probabilistic aspects of the problem, expressing average stopping times and their fluctuations in terms of the spectral radius of a normalized backward operator. Such a correspondence would yield a forward–backward conservation law linking termination statistics with spectral invariants.
Extensions and Universality
The redesigned multiscale tree space, equipped with a hybrid –oscillation norm, closes the analytic loop and removes all remaining conditionality. Further work may examine the metric entropy and measure concentration properties induced by the tree metric, seeking universal scaling laws for optimal weights or identifying extremal systems among those with . Understanding these universality features would clarify how nonlinear arithmetic recursions embed naturally into Banach geometries that enforce total contraction.
Dynamical Dirichlet Zeta Functions
The series
is one instance 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 reflect dynamical invariants. Extending this analysis to other arithmetic systems could link the present framework with the Ruelle–Perron–Frobenius theory and the analytic study of dynamical determinants, providing a spectral signature of termination, periodicity, or growth.
Broader Outlook
The spectral resolution of the Collatz dynamics establishes a new bridge between number theory and dynamical systems. It points toward 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 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 here serves as a detailed worked example in which a complete spectral resolution is obtained through an explicit Lasota–Yorke framework on a multiscale Banach space.
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| 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 . |
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