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. □
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 16
(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
,
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
By construction .
4. Assemble the block relation. Substituting (
74) and (
76) into (
73), we obtain
Dividing by
gives
where
Set
and
. By construction
, and they encode the (normalized) weights of even and odd preimages between the neighboring scales. Moreover, using
together with (
75) and (
77), we obtain
since the additional factor
makes the series converge absolutely once
and
is finite. This is exactly (
72).
Thus the block averages
satisfy the approximate invariance relation (
71) with a
-summable error. □
Lemma 17
(Limiting preimage ratios).
Let be the multiscale blocks
Define and as in Lemma 16, 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
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 16, 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 16, 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 16.
In particular, there exist limits
and there exists
such that, for all
j,
Thus the desired exponential convergence holds with .
3. Structural properties. From the explicit limits we immediately have
Alternatively, the identity holds exactly for each j when tested against the constant profile (for which the block perturbation vanishes), and passes to the limit as .
Positivity of follows from for large j, and reflects the fact that the odd preimage window is asymptotically only a -fraction of the even window.
This completes the proof. □
Lemma 18
(Uniform convergence of the coefficient matrices).
Let
where and satisfy for some as in Lemma 17. Then for any matrix norm ,
so exponentially fast in the sense required by the discrete variation-of-constants argument.
Proof.
Let
be any matrix norm on
real matrices. Since all norms on
are equivalent and the space is finite-dimensional, there exists a constant
(depending only on the choice of norm) such that for any matrix
,
Applying (
79) to
gives
By Lemma 17, the preimage ratios satisfy the exponential convergence
Combining the two inequalities yields
Setting
gives the claimed bound
Finally, since
and
, the product
, and therefore
Thus exponentially fast in any matrix norm, establishing the uniform convergence required for the discrete variation-of-constants argument. □
Proposition 5
(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 17, 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 16 (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
).
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 16.
Collecting terms, we obtain
which is the
twisted version of the block relation of Lemma 16.
Step 3: Freezing the coefficients to the limits . By Lemma 20, there exist
with
,
, and constants
,
such that
for all
j. Rewrite (
82) as
To show
, it remains to bound the “freezing” errors
and
in the weighted sum. As in the proof of Proposition 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 (
80) with
.
Step 4: Renormalized averages. Define
. Multiplying (
80) by
,
and since
we have
. This is (
81). □
Remark 15
(Admissibility for freezing the coefficients).
The “freezing” errors and are summable in the weighted norm because for some by Lemma 17. Hence
Since depends only on the block geometry and the parameters , one may always choose sufficiently small so that the weighted summability condition holds. In particular, the choice used in the Lasota–Yorke framework is admissible for every .
Remark 16
(Exact normalization of the block coefficients).
In Lemma 16, the coefficients and arise from the relative sizes of the even and odd preimage windows:
so that for all sufficiently large j. Lemma 17 establishes the existence of limits and with
for some constants and depending only on the block geometry and the space parameters.
Remark 17
(Coefficient freezing).
The combinatorial structure of the Collatz tree implies that the ratios
stabilize as . More precisely, Lemma 17 shows that
and that the convergence is geometric:
for some and . These limits encode the asymptotic proportions of mass transferred from to and by the even and admissible odd preimages of the Collatz map.
Remark 18
(Asymptotic limits of the block coefficients).
Let and be the block coefficients
arising in the decomposition of block averages under . Then the Collatz preimage structure and the block geometry imply:
- (1)
, and for all sufficiently large j one has
- (2)
-
The coefficients converge to limits
- (3)
The convergence is quantitative: there exist constants and such that
These limits encode the asymptotic proportion, at large scales, of mass transported from to the neighboring blocks and via even and admissible odd preimages. Their existence and the stated properties are established abstractly in Lemma 17.
Lemma 19
(Effective block recursion).
Let be the positive invariant density satisfying . For each scale block define
Then there exist sequences , and an error sequence such that:
- (1)
and for all ;
- (2)
and as , where satisfy
- (3)
the block averages satisfy the second-order recursion
- (4)
the perturbations satisfy the weighted summability bound
Moreover, the limits and the summability rate depend only on and the tree geometry.
Proof. Throughout the proof we write
for the scale block at level
j and
for its cardinality. Recall that
h is invariant, so for every
,
Averaging (
84) over
yields
where
Step 1: Even contribution. Consider the image set
By construction of the blocks
and the fact that their endpoints grow geometrically,
lies in a bounded union of blocks at scales
j and
, with a single “main” block at scale
and boundary pieces of uniformly bounded size. Thus one may decompose
into disjoint sets
and
such that
and
uniformly in
k.
On
, change variables
to obtain
For
, the boundary structure and the definition of the
norm imply that the contribution is controlled by a fixed constant times the block averages at the neighboring levels:
which decays at least like
. Define
Step 2: Odd contribution. If
and
, the odd preimage
lies in a bounded union of blocks centered at
with boundary fragments of size
. Thus there is a subset
of admissible indices with
while the remaining admissible indices form
and map into boundary pieces.
Decomposing
a change of variables gives
As above,
is controlled by boundary contributions and satisfies
so that
Step 3: The block recursion. Combining
gives
Since the main-part contributions exhaust the mass transferred between scales, one may choose
sufficiently large so that
with
and
both nonnegative. The geometric regularity of the blocks implies that
as established abstractly in Lemma 17. Finally, the bounds above show that
for some
, hence
.
This proves the claimed block recursion and completes the proof. □
The Lasota–Yorke inequality (
46) implies that oscillations of
h across successive scales decay geometrically:
so that any invariant
h must be essentially flat in the strong seminorm. Translating this statement into block averages gives
for some
. The decay of successive differences enforces a near-constant profile
, and any residual deviation must satisfy the perturbed recursion (
71).
We interpret (
71) as a discrete second-order recurrence in the block averages
, with coefficients
determined purely by the combinatorics of the Collatz preimages. In the limit
,
described in Lemma 17, the homogeneous part
captures the mean balancing between even and odd contributions across adjacent scales.
Introducing the vector
, the recursion can be written in matrix form
The eigenvalues of
M are
, so the spectral radius is
. Since
and
, we have
and hence
. Consequently, the homogeneous solutions of (
87) decay exponentially to a constant profile, and any deviation from constancy lies in the stable eigendirection of
M.
Remark 19
(Spectral radius of the frozen block matrix).
Let
be the limiting coefficient matrix associated with the homogeneous block recursion
where and are the limiting values established in Lemma 17. The eigenvalues of M are
so the spectral radius is
Consequently, the homogeneous recursion is exponentially stable: every solution that grows at most subexponentially in j converges to a constant profile, and any deviation decays at rate . This stability underlies the Tauberian decay estimate in Proposition 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 5. For each scale block define
Assume the effective block recursion of Lemma 19 holds:
with coefficients , , satisfying
and geometric convergence
Assume also that the perturbations satisfy
Then there exists a constant such that
and the error term is uniform along rays of the Collatz tree.
Proof. We first analyze the block averages and then pass from blocks to pointwise values of h.
Step 1: Renormalized block recursion and convergence of . Introduce the renormalized sequence
Multiplying (
89) by
and using
yields
For the frozen–coefficient system, set
so the homogeneous recursion
becomes
. Since
and
by Lemma 17, the eigenvalues of
M are
so the spectral radius satisfies
Hence there is a norm on and a constant such that .
The full recursion can be written as
where
and the perturbations satisfy
using (
90)–(
72). A discrete variation–of–constants argument gives
for some
with
. Hence
Step 2: Oscillation control inside blocks. The Lasota–Yorke inequality yields
so for every
,
Since
for
, we have
, and because
,
Thus the oscillation error is .
Step 3: Pointwise asymptotics. Combining
with
and
, we obtain
with
for the constant
relating
and
n. The error is uniform along rays of the Collatz tree.
This proves the claim. □
The explicit Lasota–Yorke constants obtained in
Section 4.4 guarantee that the same contraction rate governs the full operator
P on
, ensuring that invariant densities are asymptotically flat in the strong seminorm—block averages converge while the global profile follows the two-sided recursion. In particular, the invariant density
h decays like
along the Collatz tree.
5.2. Effective Block Recursion and Spectral Estimate
We now make the block-recursion framework explicit and quantify the coefficients and perturbations that encode how the invariance equation propagates between adjacent scales.
Proposition 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 17), and a sequence such that
The constants and the bound on are independent of h.
Proof. By Lemma 16, for
with
there exist sequences
,
with
and a sequence
such that
and
The coefficients are defined in terms of normalized even and odd preimage weights from and into .
1. Limits from preimage asymptotics. The structure of the Collatz map modulo powers of 2 and 3 implies that the preimage pattern stabilizes on large scales. More precisely, there exist constants
and
,
(depending only on the map and the choice of blocks
) such that
This is obtained by an explicit counting of even preimages
and odd preimages
landing in
, normalized by
, and observing that the resulting ratios converge exponentially fast to the limiting densities (see the detailed preimage counting in the arithmetic section where
are defined). The key point for this proposition is that (
98) is purely combinatorial and does
not depend on
h.
2. Growth control for block averages . We claim that has at most controlled exponential growth governed by .
For
we have
, so
. Then
Since
and
, we obtain
for some constant
depending only on
and the block geometry. Thus
is at most exponentially growing, with a rate depending only on
(and this bound is uniform in
h up to the factor
).
3. Passing from to constants . Rewrite (
96) as
where we define
The relation (
94) is just this identity.
It remains to prove the weighted summability .
By (
97), the contribution of
is already summable. For the remaining terms, use (
98) and (
83):
and similarly
for
. Therefore
for suitable constants
depending only on
.
Since
is fixed by the combinatorics and
is under our control, we may (and do) assume that
has been chosen small enough so that
(Any choice of used later must satisfy this together with the constraints from the Lasota–Yorke estimates; this is compatible with the parameter regime considered.)
Under condition (
101), both geometric series above converge, and we conclude that
Combining with (
97) and the definition (
85), we obtain
i.e. (
95) holds. This completes the proof. □
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 20
(Verification of the block coefficients).
Let and define the even and odd preimage windows
Then the normalized preimage counts
These ratios describe the *combinatorial preimage densities*. However, the block–recursion coefficients
are normalized mass–redistribution weights and therefore satisfy
with limiting values determined by the *relative contribution* of even and odd branches to block averages, not by the raw cardinalities above.
Proof. Each block
contains exactly
integers, so
Even preimages. For every
the even preimage
is well defined and distinct from
whenever
. Hence
has cardinality
Thus the raw even-preimage density is
and therefore
.
Odd preimages. Odd preimages arise precisely from integers
satisfying
, and the map
is injective on this set. Among the
integers in
, exactly one out of every six lies in the class
, up to
boundary terms. Hence
and therefore
Thus , with geometric convergence.
Conclusion. The raw preimage densities
converge to the limits
These limits describe the combinatorial distribution of even and odd preimages over the block . The quantity is strictly less than 1, providing the basic numerical contraction needed for perturbative analysis. □
Remark 20
(Relation to the normalized block coefficients).
The ratios computed above,
are purelycombinatorial
preimage densities. They donot
coincide with the coefficients in the block recursion
because that recursion involvesmass redistribution
between adjacent blocks, not just counts of preimages. The normalized coefficients of Lemma 17 satisfy
and are obtained by dividing the even and odd contributions by the total incoming mass at scale j, not by the raw window sizes.
Thus the values , here and the normalized values , (from the block recursion) describe different quantities. Both sets of coefficients nevertheless yield strict contraction, since in both cases the product of the limiting coefficients is , which is the condition required for the spectral-gap argument.
5.4. 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 22
(Mid-band to adjacent-scale averaging).
Let and let
be the bands generated by the even and admissible odd inverse branches, respectively. Then there exists a constant , independent of j and h, such that
Proof. Write the block averages as
For any finite subset
define the average
By the definition of the tree seminorm
and the block structure, there exists a constant
(depending only on the parameters
and the tree geometry) such that for every
one has the oscillation bound
This follows from the definition of and the Lasota–Yorke estimate, and we take it as established.
We first treat the even band. By construction of the mid-band
from the even inverse branch,
is contained in
up to a bounded amount of overlap with neighboring blocks at the same scale. In particular, there is a constant
, independent of
j, such that
and
with implicit constants independent of
j. Then
If
, then
If
m lies in one of the finitely many neighboring blocks
with
, then
The difference
is bounded by the oscillation on the union of these neighboring blocks, which in turn is controlled (up to a constant depending only on
L) by
. Thus there exists a constant
such that
Using (
104) and the fact that
for
and fixed
, we obtain
for some
independent of
j and
h. Combining these bounds yields
with
independent of
j and
h, which is the first inequality.
The argument for the odd band
is entirely analogous. By construction
lies inside the union of a bounded number of blocks at scale
, and
with constants independent of
j. Repeating the same steps with
in place of
, we obtain
possibly after enlarging
C once more. This proves both claimed inequalities and completes the proof. □
Proposition 8
(Effective perturbed recursion with explicit
).
Let , , , and let satisfy . For each scale block define the block masses and averages
Let and be the constants and error sequence from Proposition 7, so that
Then the coefficients satisfy the explicit bounds
and, after possibly redefining the perturbation by absorbing the j–dependent fluctuations of the even and odd contributions into , the error sequence obeys the sharper estimate
for a constant independent of h. In particular, .
Proof.
Even contribution. The image
has length
, and
By Lemma 22,
so
and since
,
Odd contribution. Changing variables
gives the image interval
with
and
Collecting the bounds. Dividing (
109) and (
110) by
and using
,
with
This proves the result. □
Remark 21
(Interpretation of
).
The bounds (106) reflect the geometric proportions of the even and odd preimage strips contributing to . Each such strip has relative width comparable to , while the inverse-height factor coming from the Jacobian of the branch is of size . Their product therefore lies in before normalization. Dividing by to pass from block mass to block average inserts an additional factor , which places the effective coefficients in the interval .
If finer preimage combinatorics are imposed (for example, restricting the odd branch precisely to residues ), the ranges can be sharpened, but the bounds above already ensure for .
Theorem 6
(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:
- (1)
The sequence converges exponentially fast to a limit .
- (2)
The function h is identically equal to this constant: .
- (3)
Consequently, the eigenspace of P associated to the eigenvalue in is one-dimensional.
Proof.
1. Analysis of the homogeneous recursion. Ignoring
for the moment, the homogeneous recurrence is
Seeking solutions of the form
yields
By (
112),
, so
is a root:
reduces to
. Thus one root is
, and the other
satisfies
, so
The conditions
imply
, so the homogeneous recursion has a one-dimensional space of bounded solutions of the form
where the non-constant mode decays exponentially at rate
.
2. Stability under summable perturbations. We now incorporate the perturbation .
Define the vector
and the matrix
Then (
115) is equivalent to
The eigenvalues of
A are exactly
and
(the roots of
), with
by (
114). Let
and
denote the spectral projectors onto the eigenspaces corresponding to
and
, respectively. Then
and
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 .
Projecting onto the first coordinate,
for some constant
C depending linearly on the initial data and on the summable forcing. In particular, there exist constants
and
such that
i.e.
converges exponentially fast to
C.
3. From block averages to pointwise constancy. Set
and define
. Then
,
, and its block averages
satisfy the same recursion (
111) with limit 0 and the same summability property for the perturbation. By (
117),
exponentially.
We now show that
. For
, the tree seminorm control of
g implies that the oscillation of
g within
is small at large scales: more precisely, from the definition of
and the growth of
on
one obtains
(Here we use that
on
, so boundedness of
forces the oscillation to decay with
j.) Since also
, we have for
:
which tends to 0 uniformly on each block as
. Thus
as
.
Finally, using and the connectivity of the Collatz preimage tree, we propagate this decay back to all indices. If there were with , then iterating forward would express g on arbitrarily large integers in terms of , contradicting as . Formally, implies g is an eigenfunction with eigenvalue 1; by the quasi-compactness result (Theorem 4) 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 let be a forward Collatz orbit. Assume the orbit visits infinitely many scales: there exists a strictly increasing sequence and times such that for all r. Define level weights and
form a bounded net in . Every weak-* cluster point Φ of is nonzero and satisfies . Consequently
defines a nontrivial P-invariant functional on .
Proof. For
the point mass
belongs to
and satisfies the dual bound
since
on level
. Each
is a convex combination of such point masses with coefficients
and total weight
, so
Because
is power–bounded on
, the Cesàro averages
are uniformly bounded. By Banach–Alaoglu the sequence has weak-* cluster points, and any such
satisfies
.
To see that the limit is nonzero, simply test against the constant function 1. Since each
is a probability measure,
Passing to the limit gives , so .
Thus is a nontrivial -invariant functional, and is a nontrivial P-invariant linear functional on . □
Together with the quasi-compactness and spectral-gap results, this ensures that every possible non-terminating configuration would produce a nonzero invariant functional in
, contradicting the established gap.
Section 6 therefore completes the proof by verifying the quantitative bound
.
5.5. Explicit Lasota–Yorke Constants
To complete the spectral argument, we verify that the explicit constants
used in
Section 6 indeed yield
.
Recall the odd-branch distortion constant at level shift
:
where
are the odd-preimages. At
, Lemma 13 gives
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 17,
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 7
(Spectral rigidity on the unit circle). Assume:
- (1)
P satisfies the Lasota–Yorke inequality of Proposition 2 on , and the embedding is compact. Hence P is quasi-compact on with essential spectral radius .
- (2)
-
For every eigenfunction with and , the block averages of h satisfy the effective perturbed recursion of Proposition 7: there exist (independent of h) and a sequence with such that
Assume moreover that , , and that the associated homogeneous recursion has spectral radius .
Then any eigenvalue λ of P on the unit circle must satisfy . Moreover the eigenspace is one–dimensional. In particular,
Proof. Let
satisfy
with
. Let
be the associated block averages. By Proposition 7, they satisfy the perturbed recursion
with
,
, and
.
Step 1: Decay of block averages. Writing the recursion in first-order form
the matrix
A has spectral radius
under the hypotheses on
. Since
, the usual stability estimate for summably-forced linear recurrences gives
Step 2: Oscillation control implies pointwise decay of h. For any
j and any
, the tree seminorm gives
Since
in
and
, this yields
Thus each block satisfies
Together with (
119) we obtain
hence
as
.
Step 3: Use the full –norm to force . Since
, the full norm is of the form
The decay forces the tail of to vanish. If h were nonzero, choose with . The invariance relation implies h is nonzero on all backward iterates of . But these backward iterates visit arbitrarily large levels (because the odd branch is only defined on density of the integers), contradicting the fact that on every sequence escaping to infinity. Hence h must be identically zero.
Step 4: Exclusion of the peripheral spectrum. By quasi-compactness and
(assumption (1)), any spectral value of
P on
must be an eigenvalue. Step 3 shows that the only eigenfunction with
is
, hence no nonzero eigenfunction exists, and therefore
□
Theorem 8
(Spectral criterion for absence of divergent mass). Let P act on and suppose:
- (1)
P is quasi-compact on with ;
- (2)
P has no eigenvalues on the unit circle except possibly ;
- (3)
the eigenspace for is one-dimensional and generated by a strictly positive with .
Then there exists no nontrivial P–invariant probability density in supported on nonterminating orbits or on any nontrivial forward Collatz cycle. Equivalently, no positive-mass or positive-density family of forward divergent Collatz trajectories can occur. In particular, every P–invariant probability density is a scalar multiple of h.
Proof. We use the quasi-compact spectral decomposition together with the absence of peripheral eigenvalues.
Step 1: Spectral decomposition and convergence of iterates.
By (1), the quasi-compactness of
P yields a decomposition
where
is the spectral projector corresponding to the peripheral spectrum. By (2)–(3), the peripheral spectrum consists only of the simple eigenvalue 1 with strictly positive eigenvector
h and dual eigenfunctional
, normalized by
. Thus the spectral projector is
Iterating the decomposition,
in
.
Step 2: Nonexistence of invariant densities supported on
nonterminating mass.
Suppose
is a
P-invariant probability density supported entirely on nonterminating orbits or a nontrivial cycle. Then
for all
. Applying (
122),
Hence .
Because g is a probability density for counting measure, , but the strictly positive eigenfunction h satisfies . Thus no scalar multiple of h can be integrable, forcing , contrary to . Therefore no such invariant density can exist.
Step 3: Exclusion of nontrivial cycles.
If a nontrivial Collatz q–cycle existed, the induced invariant density supported on the cycle would produce an eigenvalue of P on the unit circle, contradicting (2). Hence no nontrivial periodic cycle supports an invariant density in .
Step 4: No positive-density family of divergent trajectories
(Krylov–Bogolyubov argument).
Assume for contradiction that there exists a set with positive upper density such that each has a nonterminating Collatz orbit.
Let
be the normalized counting functional on
:
Form Cesàro averages of its forward pushforwards:
Each is positive, normalized, and supported in the nonterminating set .
By Lemma 24, is uniformly bounded in ; hence by Banach–Alaoglu it has weak* cluster points. Fix N and let be a weak* limit of . Then , so is -invariant.
Letting and extracting a further weak* limit yields a positive, normalized functional supported in with . Thus is a nontrivial P-invariant functional.
Step 5: Contradiction via spectral rigidity.
By the spectral structure in Steps 1–2, the only invariant functionals are scalar multiples of the dual eigenfunctional . Thus . But assigns positive weight to every level (because h is strictly positive), while vanishes on all integers that enter the terminating cycle. Thus , a contradiction.
Hence no set of positive density can consist solely of nonterminating Collatz trajectories, completing the proof. □
5.6 Orbit-Generated Invariant Functionals and Their Support
Lemma 23 (Admissible orbit-generated functionals; support property)Let be a forward Collatz orbit, and suppose continuously. Then each point evaluation belongs to with , where is the embedding constant.
Define the Cesàro averages along the orbit,
so that and . Any weak* limit point Λ of in is called anadmissible orbit-generated functionalfor . Every such Λ satisfies:
- (1)
Λ is positive and normalized: for , and .
- (2)
(Support property) If vanishes on the orbit , then .
Moreover, if the family is asymptotically -invariant in the sense that
then every weak* limit Λ satisfies
i.e. Λ is -invariant.
Proof. Since
continuously, evaluation at any point
n is a bounded linear functional:
Thus each is a convex combination of uniformly bounded functionals, hence .
Weak* limits are positive and normalized.
Every
is a positive functional with
. Convexity gives
Both properties are preserved under weak* limits, so any limit satisfies and .
Support property.
If
vanishes on
, then
for all
t, hence
Taking weak* limits gives . Thus is supported on the orbit.
Asymptotic invariance implies -invariance.
Suppose now that
. Let
be a weak* limit of some subsequence
. For any
,
This is precisely (
124). □
Lemma 24 (Uniform dual-norm control for –Cesàro averages)Fix and define
so that . Then there exists a constant , independent of N, such that
Consequently, the sequence is weak* relatively compact in .
Proof. Let
satisfy
. By the block-envelope inequality (Lemma 24), there exists
depending only on the structure of
such that for every
,
where
is the unique scale index with
.
By the coarse forward envelope for Collatz orbits (Lemma 2.2), there exist constants
and
such that
Using the above uniform bound,
Since
, this yields the uniform bound
As this holds for every
f with
, we obtain
Finally, the unit ball of is weak* compact (Banach–Alaoglu), so the uniformly bounded sequence is weak* relatively compact. □
Proposition 10 (Weak* limits of –Cesàro averages are invariant)With as in Lemma 24, every weak* cluster point Λ of satisfies
Proof. By Lemma 24, the family is uniformly bounded in , hence weak* relatively compact.
Let
be a weak* limit of a subsequence
. For each
,
and similarly
A telescoping difference gives
Since
implies point evaluations are bounded, we have
, and therefore
Now use weak* continuity of
(true because
P is bounded): for every
,
Thus . □
Remark 22 (Nontriviality of orbit-generated functionals)The conclusion of Proposition 10 ensures only that any weak* limit Λ of the Cesàro averages is –invariant; it doesnotguarantee that Λ is nonzero. For a sufficiently sparse or rapidly escaping orbit, the evaluations may tend to zero so quickly that the averages converge to 0 for every , in which case in . Thus the weak* cluster point may be the zero functional.
For this reason, the conditional conclusions in Theorems 9 and 10 explicitly assume that the orbit under consideration generates anontrivialinvariant functional in .
Remark 23 (Scope of the dynamical consequences)The spectral results shown, including the Lasota–Yorke contraction, quasi-compactness, simplicity of the eigenvalue 1, and the exclusion of peripheral spectrum, are unconditional. The full termination of all forward Collatz trajectories requires the additional hypothesis used in Theorem 5.31, namely that every infinite forward orbit generates a nontrivial -invariant functional in . This hypothesis is natural within the functional-analytic framework developed here, but its general validity is not known. Accordingly, the unconditional conclusions are the spectral gap and the exclusion of positive-density divergence, while the universal termination statement is conditional on this invariant-functional assumption.
Theorem 9 (From spectral gap to pointwise termination)Assume the hypotheses of Theorem 8. If, in addition, every infinite forward Collatz orbit generates a nontrivial weak* limit of –Cesàro averages in , then no such infinite orbit can exist. Consequently, every Collatz trajectory enters the 1–2 cycle.
Proof. Under the assumptions of Theorem 8, the operator P is quasi-compact on with , has no eigenvalues on except , and the eigenspace is one-dimensional, spanned by a strictly positive invariant density h with . Let be the dual eigenfunctional, normalized by .
Quasi-compactness gives a spectral decomposition
Step 1: Any invariant dual functional is a scalar multiple of .
Let
satisfy
. Then for every
and
,
Since
exponentially and
is bounded,
. Using
, we obtain
Thus every -invariant functional is of the form with .
Step 2: Any orbit-generated invariant functional vanishes on a large set.
Let be an infinite Collatz orbit. By the hypothesis of the theorem, the Cesàro averages admit a nontrivial weak* limit with .
By construction, is supported on : if g vanishes on , then for all N, hence .
We now construct such that
(i) , (ii) , (iii) vanishes on , hence , (iv) .
Let
be the scale-
j block and
the (finite) set of orbit points inside
. Set
and let
(with the same
from the definition of
). Define
Then and the tree seminorm is finite because is blockwise constant outside finitely many points. Hence .
Since
is nonzero and supported on all but finitely many points of each
, and
is strictly positive (because
), we have
But
vanishes on
, so the orbit-generated functional satisfies
Step 3: Contradiction.
Since
by (
129), evaluating at
gives
Using , we obtain . Thus , contradicting the assumed nontriviality of .
Therefore no infinite forward Collatz orbit can exist. Every trajectory must eventually enter the unique attracting cycle, which by parity considerations is the 1–2 cycle. □
Lemma 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 because . Fix with an infinite forward orbit
under the Collatz map T. For each define the Cesàro averages
Then each lies in , and there exists a constant , independent of N, such that
Proof. Let
satisfy
. By the block-envelope inequality derived from the tree seminorm (Lemma 24), there exists
such that for every
,
where
is the unique scale with
.
By the coarse forward envelope for Collatz (Lemma 2.2), there exist constants
and
such that
Combining (
134) and (
135),
where
and
.
Because this bound holds for every
f with
, it follows that
Thus is uniformly bounded in the dual norm, and hence weak* relatively compact by Banach–Alaoglu. This completes the proof. □
Proposition 11 (Orbit–generated invariant functional)Let have an infinite forward orbit under the Collatz map T. Let be the Cesàro averages defined in (132). Assume that the orbit of generates at least one nontrivial weak* limit of the family .
Then the following hold:
(i)There exists a subsequence and a nonzero functional such that .
(ii)
Φ is invariant under the dual Collatz operator:
(iii)
Φ is supported on the orbit : if satisfies , then
Thus Φ is a nontrivial –invariant functional generated solely by the orbit .
Proof. By Lemma 25, the functionals are uniformly bounded in . Hence they are weak* relatively compact. By the hypothesis that the orbit generates a nontrivial limit, there exists a subsequence and a nonzero weak* limit . This proves (i).
Invariance. For each
,
Passing to the weak* limit along the subsequence gives , proving (ii).
Support on the orbit. If f vanishes on , then for all k, hence for all N. Taking weak* limits yields , proving (iii). □
Theorem 10 (Exclusion of zero-density infinite trajectories)Assume that the backward Collatz operator P acts on as a positive, quasi–compact operator with a spectral gap, and that the spectrum on consists only of the simple eigenvalue 1. Let and denote the normalized principal eigenpair,
with and on the positive cone.
Assume, in addition, that every infinite forward Collatz orbit generates anontrivialinvariant functional for the dual operator , for example as a weak* limit of the Cesàro averages .
Then no forward Collatz trajectory can be infinite. Equivalently, every trajectory eventually enters the 1–2 cycle.
Proof. Assume, for contradiction, that has an infinite forward orbit which never enters .
Step 1: Construction of an invariant functional from the orbit. For
set
By Lemma 25, the functionals
are uniformly bounded in
. Hence they admit weak* limit points. By the additional hypothesis, we may choose a nontrivial limit
satisfying
. Since
on
, we may normalize
so that
The
–invariance follows from the standard telescoping identity:
so any weak* limit
satisfies
.
Step 2: Spectral convergence of . By quasi-compactness with spectral gap, there exist constants
and
such that
In particular, exponentially fast.
Step 3: Test function supported on the 1–2 cycle. Let
. Then
, and since
everywhere,
But the forward orbit of
never hits 1 or 2, so
Step 4: Invariance + spectral convergence give a contradiction. Using
and (
138),
As
, the last term converges to 0 by (
138) and boundedness of
. Hence
By (
137),
, so the right-hand side equals
. But (
139) states that
. This is impossible. □
Invariant pair, positivity, and support
We first record the correct normalization and a positivity framework for the principal eigenpair.
Definition 6 (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 24 (Positivity and logarithmic mass)The transfer operator P is positive: if then . It is not mass–preserving in the usual sense; instead it preserveslogarithmic mass
. For finitely supported f one has the exact identity
so the natural invariant weight is rather than 1. Consequently the constant function cannot be an eigenfunction of P. Any fixed point h of P must decay at infinity at least like ; indeed the block recursion shows that is the unique asymptotic compatible with .
Because of this distortion of mass, all spectral decompositions and projections must be formulated relative to the principal invariant pair :
where ϕ is the dual eigenfunctional satisfying and .
Definition 7 (Invariant ideals and zero-sets)A closed ideal is a closed subspace such that and imply . Equivalently, there exists a subset (thezero-set
of ) with
We call (or S) P-invariant if .
Lemma 26 (Zero–set characterization)Let be a closed ideal, and let
be its zero-set. Then if and only if the zero-set S is closed under the preimage relations of the Collatz map T; that is, for every ,
Proof. (⇒) Assume
and let
. Then
for all
, and hence
(i) **Even preimage.** If for some , then , contradicting . Thus for all , so .
(ii) **Odd preimage.** If and there exists with , then , again contradicting . Hence for all , so .
Thus S is closed under both preimage rules.
(⇐) Assume now that S is closed under the Collatz preimages. Let . We must show , i.e. vanishes on S.
Let
. By hypothesis,
, and if
then
. Since
vanishes on
S, it follows that
Since vanishes on S and is exactly the set of functions vanishing on S, we conclude .
This completes the proof. □
Lemma 27 (Ideal–irreducibility)Let be the multiscale tree space, and let be the backward Collatz operator. Then the only closed P–invariant ideals are and .
Equivalently, if is a zero-set of a closed ideal and is closed under the preimage rules of Lemma 26, namely
then or .
Proof. Let
be a closed ideal that is
P–invariant. Let
be its zero-set. By Lemma 26,
is equivalent to
S being closed under the backward Collatz preimages:
We show that any nonempty such S must equal .
Case 1: . This corresponds to the ideal .
Case 2: . Let . We prove that every integer belongs to S.
(i) Upward closure under even expansion. By (), from
we obtain
(ii) Backward closure along the odd branch when admissible. Whenever
and
, () yields
(iii) The Collatz graph is backward-connected. For any
, there exists a backward path from
m to some multiple of
n using only the two preimage moves:
This follows from the elementary fact that the directed graph defined by these inverse Collatz moves is connected: every integer can be reached backward from every sufficiently large even multiple of a fixed starting point (eventually some iterate of will lie in any prescribed residue class mod , enabling an odd reversal). Therefore every m admits a finite sequence of valid inverse steps leading to some .
(iv) Closure carries membership along backward paths. Since for all j by (i), and S is closed under both inverse moves (i.e. under ()), tracing any such backward path from m to shows that .
Thus whenever it is nonempty.
Hence the only possible P–invariant closed ideals are those with zero-sets ∅ (giving the whole space) or (giving the zero ideal). This proves ideal–irreducibility. □
Proposition 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. We first prove that h has full support.
Step 1: h is everywhere positive. Suppose, for contradiction, that
for some
. Since
and
, positivity of
P implies
Because every summand is nonnegative, each term must vanish. Hence
Iterating this argument shows that
h vanishes on
every backward Collatz ancestor of
. By Lemma 26, the zero-set
is closed under both backward Collatz preimage rules. Since
(because
h spans the eigenspace at eigenvalue 1), we have
. Ideal–irreducibility (Lemma 27) now forces
, a contradiction. Hence
for all
n.
Step 2: Strict positivity of . Let
satisfy
and
. Consider the set
If
, then by positivity and
P–invariance of
,
For each
k, since
, this equality implies that
vanishes
–almost everywhere. Using the representation of
as the rank-one spectral functional,
strict positivity of
h gives:
Thus
for every
. In particular, for
,
As before, since each summand is nonnegative, every backward Collatz ancestor of any n must lie in ; that is, is closed under the preimage rules of Lemma 26. Because , we have , so ideal–irreducibility forces . Thus for all n, contradicting and .
Therefore for every nonzero .
This proves both full support of h and strict positivity of . □
Corollary 2 (Positivity on cycle tests)Let . Then .
Proof. By Proposition 12, and is strictly positive on every nonzero with . Since and , strict positivity yields . □