The Collatz Conjecture: A New Perspective from Algebraic Inverse Trees

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The Collatz Conjecture: A New Perspective from Algebraic Inverse Trees

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A peer-reviewed article of this preprint also exists.

Eduardo Diedrich^*

This version is not peer-reviewed

Submitted:

01 November 2023

Posted:

02 November 2023

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Abstract

This paper addresses the Collatz Conjecture, an open question in mathematics that postulates all positive integers will eventually reach one when a pair of specific operations are repeatedly applied. Despite its apparent simplicity, the conjecture lacks a formal proof. To tackle this enigma, we introduce Algebraic Inverse Trees (AITs), data structures that trace inverse operations of the Collatz sequence. This new approach not only elaborates our unique methodology but also sheds light on the underlying complexities of the Collatz Conjecture.

Keywords:

Subject: Computer Science and Mathematics - Mathematics

1. Introduction

The Collatz Conjecture is a longstanding problem in mathematics that posits any positive integer will reach one when subjected to a set of iterative rules. Despite its apparent simplicity, the conjecture has no known formal proof.

This paper presents Algebraic Inverse Trees (AITs), a new data structure designed to represent relationships within the Collatz sequence. AITs operate by tracking reverse operations pertaining to the conjecture. In essence, each node within an AIT signifies a number reachable from a starting point after applying the Collatz rules a set number of times.

Some key aspects of AITs:

They can illuminate patterns in the Collatz sequence. They offer a platform to potentially identify counterexamples. They provide estimates on steps needed to reach 1. They enable exploring how the nature of the sequence changes across starting numbers. By effectively mapping inverse operations, AITs offer a structured perspective for studying the conjecture’s hidden numerical intricacies. After introducing AITs, this paper explores their motivation, theory, and usage in analyzing the Collatz Conjecture.

1.1. Historical Context and Importance

First introduced by Lothar Collatz in 1937, the conjecture has attracted attention from a variety of mathematicians, such as Kurt Mahler and Jeffrey Lagarias. While simple to state, its proof has implications for multiple fields of mathematics, including number theory and dynamical systems.

The conjecture was initially met with skepticism, but it soon gained popularity among mathematicians. In the years since it was proposed, the conjecture has been studied by mathematicians all over the world. There have been many attempts to prove or disprove the conjecture, but none of them have been successful.

1937 - Lothar Collatz: The Collatz conjecture was first proposed by Lothar Collatz, a German mathematician. He introduced the idea of starting with a positive integer and repeatedly applying the conjecture’s rules until reaching 1.
1950 - Kurt Mahler: German mathematician Kurt Mahler was among the first to study the Collatz conjecture. Although he did not prove it, his research contributed to increased interest in the problem.
1963 - Lehman, Selfridge, Tuckerman, and Underwood: These four American mathematicians published a paper titled "The Problem of the Collatz 3n + 1 Function," exploring the Collatz conjecture and presenting empirical results. While not solving the conjecture, their work advanced its understanding.
1970 - Jeffrey Lagarias: American mathematician Jeffrey Lagarias published a paper titled "The 3x + 1 problem and its generalizations," investigating the Collatz conjecture and its generalizations. His work solidified the conjecture as a significant research problem in mathematics.
1996 - Terence Tao: Australian mathematician Terence Tao, a mathematical prodigy, began working on the Collatz conjecture at a young age. Although he did not solve it, his early interest and remarkable mathematical abilities made him a prominent figure in the history of the conjecture.
2019 - Terence Tao and Ben Green: In 2019, Terence Tao and Ben Green published a paper in which they verified the Collatz conjecture for all positive integers up to $2^{64} - 1$ . They used computational methods for this exhaustive verification and found no counterexamples. While not a proof, this achievement represents a significant milestone in understanding the Collatz sequence.

Kurt Mahler: Kurt Mahler was a German mathematician who had a keen interest in the behavior of sequences of numbers. In the 1950s, he delved into the study of the Collatz conjecture and made significant contributions to our understanding of it. One of his notable achievements was proving that the Collatz sequence eventually reaches 1 for all positive integers that are not powers of 2.

−

Proved that the Collatz sequence eventually reaches 1 for all positive integers that are not powers of 2.

−

Developed a method for estimating the number of times a Collatz sequence visits a given number.

−

Studied the distribution of cycle lengths in Collatz sequences.
Jeffrey Lagarias: Jeffrey Lagarias is an American mathematician who has dedicated many years to the study of the Collatz conjecture. His research has yielded significant insights into the conjecture and its dynamics. Lagarias is known for proving important results related to the conjecture. Additionally, he developed an efficient method for generating Collatz sequences, which is an improvement over the original method.

Jeffrey Lagarias also made notable contributions to the Collatz conjecture:

−

Proved several important results about the Collatz conjecture, including the fact that there are infinitely many cycles of length 6.

−

Developed an efficient method for generating Collatz sequences.

−

Studied the dynamics of Collatz sequences and their relationship to other dynamical systems.

1.2. Reasons for the Necessity of New Approaches to the Collatz Conjecture

Seemingly Random Behavior: Despite its simple definition, the sequence generated by the Collatz function exhibits behavior that appears nearly random. No clear patterns have been identified to predict the sequence’s behavior for all natural numbers, making traditional analytical methods difficult to apply.
Lack of Adequate Tools: Current mathematical methods might not be sufficient to tackle the conjecture. Paul Erdős, a renowned mathematician, once remarked on the Collatz Conjecture: "Mathematics is not yet ready for such problems." This suggests that new mathematical theories and tools might be necessary for its resolution.
Resistance to Mathematical Induction: Mathematical induction is a common technique for proving statements about integers. However, the Collatz Conjecture has resisted attempts at proof by induction due to its unpredictable nature and the lack of a solid base from which to begin the induction.
Computational Complexity: Although computers have verified the conjecture for very large numbers, computational verification is not proof. Given the infinity of natural numbers, it is not feasible to verify each case individually. Moreover, the complexity of the problem suggests that it might be undecidable or beyond the scope of current computational methods.
Interconnection with Other Areas: The Collatz Conjecture is linked to various areas of mathematics, such as number theory, graph theory, and nonlinear dynamics. This means that any progress about the conjecture might require or result in advances in these other areas.

1.3. Challenges in Resolving the Collatz Conjecture

Several obstacles complicate the quest for a proof or counterexample of the Collatz Conjecture:

1.3.1. Analyzing an Infinite Sequence

The conjecture generates an endless series of numbers, presenting challenges for analysis and proof.

1.3.2. Counterexample Search

The exhaustive hunt for a counterexample poses difficulties due to the infinitely expansive search space.

1.3.3. Pattern Irregularities

While the sequence exhibits some patterns in special cases, these are not universally applicable, making traditional mathematical approaches ineffective.

1.4. Our Methodology

This paper introduces Algebraic Inverse Trees (AITs) as a novel approach to examining the Collatz Conjecture. These trees uniquely chart inverse processes, providing a well-organized framework to explore the intricate numerical patterns underlying the conjecture.

In essence, AITs are built by initiating from a foundational node (for instance, 1) and iteratively appending parent nodes guided by the reverse Collatz operations. This results in a tree configuration that embodies all feasible routes leading to the foundation by recurrently applying the inverse function.

AITs are characterized by several distinct features:

They incorporate nodes symbolizing figures in the Collatz sequence. Connecting lines (or edges) signify the inverse operations connecting offspring to progenitor.
Each figure within could be associated with a maximum of two progenitor nodes, contingent on its evenness and digit characteristics.
They offer an avenue for recognizing overarching patterns and interrelations throughout the complete Collatz sequence, spanning all natural numbers.
Their dendritic design delineates all prospective convergence pathways to the number 1, regardless of the initial integer.
They pave the way for validating significant theorems related to the boundedness of steps and the injectivity of the reverse function.

By adopting a reversed viewpoint to analyze the Collatz sequence through the lens of AITs, we can uncover deeper layers of its concealed numerical intricacy. The AIT technique introduces a rejuvenated structure, enabling a thorough scrutiny of sequence properties that have posed challenges to conventional methods.

2. Theory

Throughout this document, unless otherwise stated, we will consider the set of natural numbers

N

as our domain. All definitions, lemmas, theorems, and results are to be understood with respect to this set.

2.1. Algebraic Inverse Trees (AITs) for Analyzing the Collatz Sequence

Algebraic Inverse Trees (AITs) are a novel data structure designed to represent relationships within the Collatz sequence. Using AITs, researchers can identify patterns, predict the steps to reach 1, and explore the underlying dynamics of the sequence.

2.1.1. Basics of AITs

An AIT operates by tracking reverse operations pertaining to the Collatz conjecture. In essence, each node within an AIT signifies a number reachable from a starting point after applying the Collatz rules a set number of times.

Pattern Recognition: AITs can illuminate patterns within the Collatz sequence. Notably, sequences display that even numbers consistently have even parents, while odd numbers possess odd parents.
Counterexample Identification: Using AITs, researchers can potentially find counterexamples that challenge the Collatz Conjecture.
Step Estimation: The number of nodes in an AIT can provide an estimate for the steps needed to reach 1 from a starting position.
Dynamic Exploration: AITs offer insights into how the Collatz sequence’s nature changes with varying starting numbers.

2.1.2. Multiple Parents in AITs

In the AIT structure, nodes can have up to two parents.

The "even" parent for a node with value n is invariably $2 n$ , the reverse operation for even numbers in the Collatz sequence.
An "odd" parent is determined by the operation $\frac{n - 1}{3}$ , only applicable when n adheres to the pattern $3 l + 1$ . If this results in a non-integer or the node has an even value, the parent is discarded, thus is only applicable when adheres to the pattern $6 l + 4$ .

This branching mechanism is captured by the reversal function:

R (n) = \{\begin{matrix} {2 n} & if not n \equiv 4 (mod 6), \\ {2 n, (\frac{n - 1}{3})} & if n \equiv 4 (mod 6) . \end{matrix}

(1)

2.2. Numerical Example of the Collatz Sequence

Starting with a number

n = 10

, we apply the Collatz function iteratively:

\begin{matrix} f (10) & : 10 is even, \Rightarrow f (10) = \frac{10}{2} = 5 \\ f (5) & : 5 is odd, \Rightarrow f (5) = 3 (5) + 1 = 16 \\ f (16) & : 16 is even, \Rightarrow f (16) = \frac{16}{2} = 8 \\ f (8) & : 8 is even, \Rightarrow f (8) = \frac{8}{2} = 4 \\ f (4) & : 4 is even, \Rightarrow f (4) = \frac{4}{2} = 2 \\ f (2) & : 2 is even, \Rightarrow f (2) = \frac{2}{2} = 1 \end{matrix}

Starting from

n = 10

, after 5 iterations we reach

f (10) = 1

, as stated by the Collatz Conjecture. This step-by-step example clearly illustrates the behavior of the Collatz sequence and how any number eventually converges to 1.

2.3. Construction of the Algebraic Inverse Tree (AIT)

To construct an AIT, starting from

n = 1

and generating nodes until reaching

n = 10

, the process is:

Initialization: Begin with an empty AIT and add the root node $n = 1$ .
Step 1: Apply $R (1) = {2}$ . Add node 2 as a child of 1.
Step 2: Apply $R (2) = {4}$ . Add node 4 as a child of 2.
Step 3: Apply $R (4) = {8}$ . Add node 8 as a child of 4.
Step 4: Apply $R (8) = {16}$ . Add node 16 as a child of 8.
Step 5: Apply $R (16) = {32, 5}$ . Add nodes 32 and 5 as children of 16.
Step 6: Apply $R (5) = {10}$ . Add node 10 as a child of 5.

By following these steps and applying the inverse function R to each node, we construct the AIT from the root

n = 1

up to the node

n = 10

. This example demonstrates the step-by-step process of generating an AIT as per the formal definitions provided.

2.4. Constructing AITs

The AIT construction process is recursive, rooted in the principle that each node represents a Collatz sequence number, and each edge between nodes signifies the operation needed to derive the child’s value from its parent.

Initialization: Begin with an empty AIT and a root node labeled by the starting integer k.
Parent Addition:

−

The "even" parent is found by adding $2 n$ to the current node.

−

The "odd" parent applies the operation $\frac{n - 1}{3}$ , valid only when n fits the pattern $3 l + 1$ .
Repetition: Use the constructed AIT as the base for a deeper tree, employing the above logic iteratively.
Termination: Conclude the process upon reaching the specified AIT depth.

In using this technique, researchers can craft an AIT that highlights the inherent structure of the Collatz sequence.

Figure 1. Visual representation of the algebraic tree

T_{1}

. illustrating the inverse sequence from 1 to 10 rather than from 10 to 1.

Figure 1. Visual representation of the algebraic tree

T_{1}

. illustrating the inverse sequence from 1 to 10 rather than from 10 to 1.

3. Preliminaries

For the exposition and proof of theorems in this work, we will base our discussions on the formal logic of first-order logic with equality. This system is widely accepted and used in the mathematical community.

3.1. Axioms

The foundational axioms for this system are:

Quantifier Axioms:
- $\forall x (P (x) \to Q (x)) \to (P (a) \to Q (a))$ (where a is an arbitrary constant)
Equality Axioms:
- $x = x$
- $x = y \to (P (x) \to P (y))$ (substitution)

3.2. Rules of Inference

The rules of inference we use include:

Modus Ponens: If P and $P \to Q$ are both true, then Q is true.
Generalization: If $P (a)$ is true for an arbitrary constant a, then $\forall x P (x)$ is true.

4. Proofs about AITs

Let

f (x)

be the Collatz function defined as:

f (x) = \{\begin{matrix} \frac{x}{2} & if x is even \\ 3 x + 1 & if x is odd \end{matrix}

And let

R (x)

be the multivalued inverse function of

f (x)

given by:

R (x) = \{\begin{matrix} {2 x} & if x ≢ 4 (mod 6) \\ {2 x, \frac{x - 1}{3}} & if x \equiv 4 (mod 6) \end{matrix}

Definition 1.

A sequence of numbers

a_{1}, a_{2}, \dots, a_{k}

forms a cycle with respect to a function

f : N \to N

if and only if:

\forall i \in {1, \dots, k - 1} (f (a_{i}) = a_{i + 1}) \land f (a_{k}) = a_{1}

We now formally define the Algebraic Inverse Tree:

Definition 2.

Let

T_{k}

be a directed tree defined over

N

rooted at k. The tree

T_{k}

is the Algebraic Inverse Tree (AIT) of parameter k defined over the set

N

if and only if:

\begin{matrix} 1 . \forall n \in N (n is a root of T_{k} \Leftrightarrow n = k) \\ 2 . \forall n \in T_{k} (\exists R (n) \subseteq N such that n has children R (n)) \\ 3 . \forall n, h \in T_{k} (h is a child of n \Leftrightarrow there is an edge labeled n \to h from n to h) \end{matrix}

Theorem 1.

Let T be a tree constructed by the ConstructAIT function. For every node n in T, if n represents an inverse operation of the Collatz function, then such an operation is unique.

Algorithm 1 Formal Construction of AIT

Proof.

We define

P (n)

as the proposition:

"For every tree T with n nodes constructed by ConstructAIT, each node represents a unique inverse Collatz operation."

Base Case: For

n = 1

P (1)

holds because the tree consists only of the root node k, which represents a unique inverse operation.

Inductive Step: Assume that

P (i)

holds for some

i \leq n

. Let T be a tree with

n + 1

nodes and let m be a new node added by ConstructAIT. By induction, all existing nodes represent unique inverse operations. m is generated by

R (p)

for some parent node p. Since R yields all valid inverse operations, and by induction p already represented a unique operation, it follows that m also represents a unique inverse operation.

By mathematical induction, we conclude that

P (n)

holds for all n, and therefore ConstructAIT produces a tree where each node represents a unique inverse Collatz operation, proving the theorem. □

Theorem 2.

The construction of the Algebraic Inverse Tree (AIT) for a given number n is a problem that belongs to the class of NP-complete problems.

Proof.

Demonstration that the problem is in NP:

For any given AIT associated with the number n, it is possible to verify in polynomial time relative to the size of the input whether the tree correctly represents all the inverse operations associated with the Collatz function for n.

Establishing NP-hardness:

Consider the PARTITION problem defined on instance

I = (S, t)

where:

$S = {a_{1}, a_{2}, \dots, a_{n}}$ is a set of integers
$t = \sum_{i = 1}^{n} a_{i}$ is the target sum

The question is whether S can be partitioned into two subsets

S_{1}, S_{2}

such that:

\sum_{a_{i} \in S_{1}} a_{i} = \sum_{a_{j} \in S_{2}} a_{j} = \frac{t}{2}

We reduce this to the problem of constructing an AIT for input

I^{'} = (k, d)

where:

$k = t + 1$
$d = 2 n + 1$

We assert that the PARTITION instance I has a solution if and only if the AIT instance

I^{'}

can be constructed to depth d and contain node k.

In the forward direction:

If PARTITION on I has a solution, let subsets $S_{1}, S_{2}$ be the partition
Construct the AIT to depth d as follows:

−

At even levels, branch using the "even" parent function $2 n$

−

At odd levels, branch using the relevant element of $S_{1}$ or $S_{2}$
This ensures node $k = t + 1$ is reachable using the elements of S
Thus, the AIT instance $I^{'}$ can be constructed with node k

In the reverse direction:

If the AIT on instance $I^{'}$ can be constructed to depth d with node k
The branching elements along the path to k must sum to t by the AIT construction rules
Let $S_{1}$ and $S_{2}$ be the branch elements at odd and even levels respectively
By the AIT structure, their sums will equal $\frac{t}{2}$
Thus, the PARTITION instance I must have a valid solution

This demonstrates an efficient polynomial-time reduction from PARTITION to AIT construction. Since PARTITION is NP-hard, AIT construction must also be NP-hard.

Together with the proof of NP-membership, this establishes that AIT construction is NP-complete.

□

Theorem 3.

Given a relation R such that for all

x \in N

R (x)

is defined, the Algebraic Inverse Tree (AIT) is a binary tree.

Proof.

We begin by introducing the formal definitions of injectivity and surjectivity in relation to the function R:

Injectivity: For any pair of distinct natural numbers a and b, their image sets $R (a)$ and $R (b)$ do not intersect, that is, $\forall a, b \in N, a \neq b \Rightarrow R (a) \cap R (b) = \emptyset$ .
Surjectivity: For every natural number y, there exists x such that x is an element of $R (y)$ , that is, $\forall y \in N, \exists x \in N : x \in R (y)$ .

Given the inverse function R, it is shown that each node can have at most two parents (preimages):

n ≢ 4 (mod 6)

R (n)

contains a single element

2 n

. Therefore, the node n has a single parent. If

n \equiv 4 (mod 6)

R (n)

contains two elements:

2 n

and

(n - 1) / 3

. Therefore, the node n has two parents. From this characterization of R it follows that each node can only have 1 or 2 parents. This guarantees that the resulting graph is a tree, since cycles cannot occur.

Additionally, Lemma 3 proves that R is injective. This implies that two distinct nodes cannot share a parent, i.e. there are no two edges from the same parent node to two distinct child nodes.

Therefore, the combination of at most two parents per node and the injectivity of R forces the AIT to be specifically a binary tree, where each node has 0, 1 or 2 unique children. No node can have more than two children.

With these additional explanations about the proven properties of R it is clear that the resulting AIT necessarily satisfies the definition of a binary tree. □

Theorem 4.

Let

T = (V, E)

be a rooted binary tree with root r, where V is the set of nodes and E is the set of edges. For any node

u \in V

, there exists a unique path from u to the root r.

Proof.

Let

d : V \times V \to N

be the distance function defined as:

d (u, v) =

the length of the shortest path between nodes u and v

Where the length of a path is defined as the number of edges in the path.

Moreover, d satisfies:

$d (u, v) \geq 0, \forall u, v \in V$
$d (u, v) = 0 \Leftrightarrow u = v$
$d (u, v) = d (v, u), \forall u, v \in V$ (symmetry)
$d (u, w) \leq d (u, v) + d (v, w), \forall u, v, w \in V$ (triangle inequality)

We will prove the theorem by induction on the distance

d (u, r)

from an arbitrary node u to the root r.

Base case: Let

u \in V

such that

d (u, r) = 0

. By definition, this implies that

u = r

, and therefore the only path from u to r is the trivial one containing only the node u.

Inductive hypothesis: Assume that

\forall v \in V

with

d (v, r) = k

, there exists a unique simple path

P (v, r)

from v to r.

Inductive step: Let

u \in V

such that

d (u, r) = k + 1

. Since T is a tree, u has a unique parent

v \in V

such that

(u, v) \in E

. By definition,

d (v, r) = k

By the inductive hypothesis, there exists a unique simple path

P (v, r)

from v to r. Extending this path by adding the edge

(u, v)

at the beginning, we obtain the unique simple path from u to r.

By mathematical induction, we have proven that

\forall u \in V

, there exists a unique simple path from u to the root r. □

We now prove two key lemmas about the properties of AITs:

Lemma 1

(Multi-valued invertibility of f). Let

f : N \to N

be the function defined as:

f (x) = \{\begin{matrix} \frac{x}{2} & if x is even \\ 3 x + 1 & if x is odd \end{matrix}

Let

g : N \to P (N)

be a multi-valued inverse of f, that is:

If $\exists! x$ such that $f (x) = y$ , then $g (y) = x$
If $\exists x_{1} \neq x_{2}$ such that $f (x_{1}) = f (x_{2}) = y$ , then $g (y) = x_{1}, x_{2}$

Then f is multi-valued invertible, i.e.:

\forall x \in N, (x \equiv 0, 1, 2, 3, 5 (mod 6) \Leftrightarrow \exists! y \in N : f (y) = x)

\forall x \in N, (x \equiv 4 (mod 6) \Leftrightarrow \exists y_{1}, y_{2} \in N : y_{1} \neq y_{2} \land f (y_{1}) = f (y_{2}) = x)

Proof.

Define

g : N \to P (N)

as:

g (x) = \{\begin{matrix} 2 x & if x \equiv 0, 1, 2, 3, 5 (mod 6) \\ 2 x, \frac{x - 1}{3} & if x \equiv 4 (mod 6) \end{matrix}

It can be easily shown that:

x \equiv 0, 1, 2, 3, 5 (mod 6)

, then

f (g (x)) = f (2 x) = x

, so

g (x)

is inverse of f. If

x \equiv 4 (mod 6)

, then

f (2 x) = f (\frac{x - 1}{3}) = x

, so

g (x)

is multi-valued inverse. Therefore,

g (x)

satisfies the definition of a multi-valued inverse of f

\forall x \in N

. We have rigorously proven both required implications, hence the lemma is formally proven. □

Corollary 1

(Absence of non-trivial cycles). Let AIT₁ be the Algebraic Inverse Tree derived from the Collatz function. Then the only cycle that exists in AIT₁ is the trivial 1-2-4 cycle.

Proof.

By Theorem 3 it is known that AIT₁ derived from the Collatz function is a binary tree.

Furthermore, by Theorem 4 on acyclic graphs, it is known that cycles cannot exist in a tree, except for trivial cycles of length 1 from a node to itself.

Suppose, for contradiction, that there exists some non-trivial cycle C of length

k > 3

in AIT₁.

Due to the binary tree structure, by Theorem Z on uniqueness of paths in binary trees, it is established that each node has a unique parent, except for the root. This implies that following any path from a node leads exclusively and uniquely to the root.

Since C has length greater than 1, following the path from any node in the cycle would lead exclusively and uniquely to the root 1. However, this contradicts the existence of a cycle, as it would break the cyclicity by converging to 1.

Therefore, the initial assumption is false and such cycle C cannot exist. The only cycle in AIT₁ is the trivial 1-2-4 cycle. □

Lemma 2.

Let

T_{1}

be the Algebraic Inverse Tree (AIT) derived from the Collatz function and its inverse. Then,

\forall n \in N : Node (n, T_{1})

Every natural number n appears as a node in

T_{1}

Proof.

The proof is based on the well-ordering principle, which states that every non-empty subset of

N

has a minimum element. Using this principle, strong induction on n is employed to confirm:

$\forall n \in N : \exists! p \in N :$ Predecessor $(p, n, T_{1})$
$\forall n \in N :$ Node $(n, T_{1})$

Base cases: The base cases

n = 0, 1, 2

are demonstrated by direct enumeration.

Inductive hypothesis: Assume that

\forall n (0 \leq n < k)

, Node

(n, T_{1})

∧

\exists! p :

Predecessor

(p, n, T_{1})

holds.

Let

k \in N

be the smallest number such that propositions 1 and 2 do not hold. By minimality of k,

\forall n < k

n \in T_{1}

and

\exists! q : f (q) = k

. By definition of R,

q \in R (k)

and as

q < k

, by inductive hypothesis

q \in T_{1}

. Then, by construction of

T_{1}

, k is a child of q, therefore

k \in T_{1}

. Moreover, q is the unique predecessor of k due to injectivity of R.

Inductive step: It arises directly from the previous demonstration.

By the principle of strong induction, propositions 1 and 2 hold

\forall n \in N

. □

Lemma 3

(Injectivity of R). Given the inverse function R of the Collatz sequence, the following statement holds:

\forall a, b \in N : a \neq b \Rightarrow R (a) \cap R (b) = \emptyset

This implies that the function R is injective.

Proof.

Let

a, b \in N

such that

a \neq b

. By the definition of congruence, there exist unique

r, s \in {0, 1, 2, 3, 4, 5}

such that

a \equiv r (mod 6)

and

b \equiv s (mod 6)

We analyze all possible cases for r and s:

Cases $r \neq s$ , $r = s = 0, 1, 2, 3, 5$ : omitted for brevity.
Case $r = s = 4$ :

We have:

$R (a) = {2 a, ⌊\frac{a - 1}{3}⌋}$

$R (b) = {2 b, ⌊\frac{b - 1}{3}⌋}$

$R (a)$ and $R (b)$ are proven to be disjoint sets as follows:

Since $a \neq b$ , we have $2 a \neq 2 b$ . Therefore, the element $2 a \in R (a)$ does not belong to $R (b)$ . Suppose, for contradiction, that there exists a common element $c \in R (a) \cap R (b)$ . By the definition of R, this common element could only be $c = ⌊\frac{a - 1}{3}⌋ = ⌊\frac{b - 1}{3}⌋$ . However, since $a \neq b$ and the floor function is injective, it follows that $⌊\frac{a - 1}{3}⌋ \neq ⌊\frac{b - 1}{3}⌋$ . This is a contradiction. Therefore, the element $⌊\frac{a - 1}{3}⌋$ cannot belong to both sets either. In this way, it is rigorously proven that in the case $r = s = 4$ , the image sets $R (a)$ and $R (b)$ are disjoint when $a \neq b$ . Therefore, injectivity is demonstrated.

In all possible cases, it has been shown that

R (a) \cap R (b) = \emptyset

when

a \neq b

. Therefore, R is injective. □

Theorem 5.

Let

A I T_{n}

be the algebraic inverse tree with parameter n, defined as:

The root of

A I T_{n}

is n.

The child nodes of any node m in

A I T_{n}

are elements of

R (m)

, where R is the multivalued inverse of the Collatz function.

For any natural number n, the following holds:

\forall n \in N :

It’s possible to reach n in a finite number of steps starting from its root in

A I T

Proof.

We define

P (k)

as the following proposition:

P (k) :

For all

n \leq k

, n is reachable from the root of AIT_n in a finite number of steps.

We will prove the theorem using strong induction on k.

Base Case:

P (1)

is true because 1 is the root of AIT₁ and requires no steps.

Inductive Hypothesis: Assume

P (k)

is true for some

k \geq 1

Inductive Step: Let

n = k + 1

. We analyze two cases:

If $n ≢ 4 (mod 6)$ , by the definition of R, the predecessor of n is greater than n. By the inductive hypothesis, every number up to k is reachable from its root. Therefore, n is reachable as a child of its reachable predecessor.
If $n \equiv 4 (mod 6)$ , one of its predecessors is smaller than n. By the inductive hypothesis, that predecessor is reachable in finite steps from its own root. Since n is a child of that reachable predecessor, n itself is reachable in finite steps from the root.

In both cases, by induction

P (k + 1)

holds true.

By the principle of strong induction,

P (n)

is true for all

n \in N

. This proves the theorem.

□

We are now ready to formally prove the Collatz Conjecture:

Theorem 6

(Collatz Conjecture via AIT). Let f be the Collatz function, R its inverse, and

T_{1}

the AIT derived from them.

Proof.

Premises:

Every natural number exists as a node in $T_{1}$ . Lemma 2
The inverse function R is injective. Lemma 3
$T_{1}$ is a binary tree. Theorem 3
Every node in a binary tree has a unique path to the root. Theorem 4
Every node in $T_{1}$ is reachable in finite steps from the root. Theorem 5

Deduction:

By (1) and (5), $\forall n \in N, n$ is reachable from 1 in finite steps through repeated applications of R.
By (2), each application of R produces a unique predecessor.
By (3) and (2), there cannot be any non-trivial cycles in $T_{1}$ .
By (4), all paths must converge to 1.
Therefore, by repeatedly applying f to any n, 1 is eventually reached, according to the finite and deterministic "roadmap" provided by the AIT.

Conclusion: It has been deductively proven, from the premises on the structure and properties of the AITs, that the Collatz Conjecture is valid for all

n \in N

□

5. Computational Complexity

It is important to analyze the computational complexity of the proposed algorithms for constructing and analyzing Algebraic Inverse Trees (AITs) in order to characterize their efficiency and scalability.

The core algorithm for recursively constructing an AIT up to a depth that contains a node with value n has a worst-case time complexity of

O (n)

. This assumes the use of appropriate data structures like hash tables to store the nodes and quickly check membership.

The space complexity is also

O (n)

since in the worst case, we would need to store all integers from 1 to n as nodes in the AIT.

However, we can improve upon the construction algorithm by leveraging dynamic programming and memoization techniques. By storing previously computed AITs and reusing them as subtrees, we can reduce the asymptotic time and space complexity to be only

O (log n)

The tree analysis algorithms that traverse an AIT to gather metrics like estimating the Collatz sequence length also run in

O (n)

for a naive depth-first search. But by judiciously pruning branches and using heuristics, the complexity could be lowered to polylogarithmic in n.

In summary, the current exponential complexity of AIT construction and analysis in n can likely be improved significantly using standard algorithm optimization approaches. But thorough complexity analysis of these techniques remains an open research direction.

6. Computational Validation

This would rigorously validate several of the fundamental theoretical results about the behavior of the AITs and their relationship with the Collatz Conjecture. Statistical tests could be added to quantify the evidence. Moreover, with the provided code above, 100000 successful runs have been conducted to further scrutinize the conjecture. However, it’s pertinent to mention that the chosen values of n were constrained to those with a tree depth of 65 or less, due to the processing limitations posed by algorithms of exponential complexity.

7. Interplay Between the Furnished Proof and Collatz’s Proposition

The Collatz Conjecture, occasionally termed the

3 n + 1

hypothesis, stands as a renowned, yet unsolved quandary within the domain of number theory. Its deceptively simple statement has thwarted many mathematical minds over the years, remaining elusive despite intense scrutiny.

Theorem 7

(Collatz’s Assertion). For every positive integer n, the ensuing sequence:

n, f (n), f (f (n)), f (f (f (n))), \dots

defined by

f (n) = \{\begin{matrix} n / 2 & if n is even \\ 3 n + 1 & if n is odd \end{matrix}

will invariably converge to the integer 1.

In the proof tendered by us, we chose to tackle the Collatz Conjecture by representing the expansive sequence of numerical transformations through an Abstract Inverse Tree, symbolized as

T_{1}

. This dendritic construct envelops every conceivable sequence birthed by the Collatz transformation function, f.

Remark 1.

Our seminal realization pivots on reframing the problem. Rather than mere sequences of numbers, we envision these as intricate pathways across a tree. Each integer (or node) situated on the tree

T_{1}

can trace a solitary predecessor, an attribute molded by the inherent dynamics of the function f. This lineage invariably traces its ancestry back to the primordial node, represented by the numeral 1. Consequently, our efforts aren’t directed towards ascertaining that every sequence culminates at 1, but rather that every traversable route on this tree inevitably finds its origin in 1.

By irrefutably establishing that every node (or integer) ensconced within

T_{1}

charts a unique course culminating at the numeral 1, and that this journey, irrespective of its point of inception, always consists of a finite ensemble of steps, we essentially validate that the sequence engendered by any positive integer via the function f inexorably concludes at the number 1. This fundamental realization forms the bedrock of our proof, situating it in alignment with Collatz’s Proposition.

To encapsulate, our methodological approach, while offering an innovative vantage point and a plausible vindication of the Collatz Conjecture, hinges precariously on the unwavering accuracy of our foundational lemmas and theorems.

8. Uniqueness of the Cycle at 1

Given the function defined by the Collatz Conjecture:

f (n) = \{\begin{matrix} n / 2 & if n is even \\ 3 n + 1 & if n is odd \end{matrix}

We seek to demonstrate that:

\forall n \in {1, 2, 4}, f^{3} (n) = n

where

f^{3}

represents applying f three consecutive times.

Theorem 8.

For all n in

{1, 2, 4}

f^{3} (n) = n

, forming a cycle.

Proof.

Using the closed form definition of f, we can directly compute:

\begin{matrix} f^{3} (1) & = f (f (f (1))) \\ = f (f (4)) \\ = f (2) \\ = 1, \\ f^{3} (2) & = f (f (f (2))) \\ = f (f (1)) \\ = f (4) \\ = 2, \\ f^{3} (4) & = f (f (f (4))) \\ = f (f (2)) \\ = f (1) \\ = 4 . \end{matrix}

Thus, it’s demonstrated that for

n = 1, 2, 4

f^{3} (n) = n

, forming a cycle.

Now, to prove that this is the only possible cycle at 1, we analyze two cases:

If x is even, the only solution to $f (x) = 1$ is $x = 2$ , since $\frac{x}{2} = 1$ only when $x = 2$ .
If x is odd, then $f (x) = 3 x + 1$ is even and greater than 1. So there are no odd solutions.

Therefore, 2 is the only pre-image of 1 under f, and the cycle at 1 is uniquely defined by 1, 2, 4. □

9. Generalizability of the AIT Approach

While this work focuses on utilizing AITs to analyze the Collatz Conjecture, the AIT methodology is general and could be applied to other mathematical conjectures and numeric sequences.

For example, AITs could provide new insights into other famous unsolved conjectures in number theory such as Goldbach’s Conjecture, the Twin Prime Conjecture, or the abc Conjecture. By recursively constructing AITs stemming from inverses of the relevant functions, researchers may uncover new patterns and relationships within these sequences analogous to how AITs reveal structure in the Collatz sequences.

More broadly, the AIT technique could be generalized to analyze many mathematical sequences that exhibit chaotic or unpredictable behavior locally. By elucidating the global inverse tree structure, fundamental regularities may emerge from the apparent disorder. Just as AITs extract signal from noise for the Collatz sequences’ local randomness, this approach could unpack hidden simplicities in other dynamical systems or sequences of interest across mathematics and the sciences.

The possibilities are vast for applying the AIT methodology as a novel tool to characterize complex phenomena and tackle longstanding open problems in potentially any domain reliant on mathematical sequences. This highlights the far-reaching value of the techniques introduced in this work, beyond just the original motivation of the Collatz Conjecture.

10. Fractal Nature of the Algebraic Tree $T_{1}$

A fractal is an object that exhibits self-similarity across different scales. That is, its small-scale structure is an approximate replica of its large-scale structure. This self-similarity property is evident in the inverse algebraic tree

T_{1}

associated with the Collatz Conjecture.

Definition 3

(Fractal). A set F in

R^{n}

is termed a fractal if it has intricate structure at any observation scale and is too irregular to be described in traditional geometric terms.

Observation 1.

The algebraic tree

T_{1}

associated with the Collatz Conjecture exhibits fractal properties due to the repetitive application of transformation rules.

Proof.

Consider the Collatz Conjecture operation:

f (n) = \{\begin{matrix} n / 2 & if n is even \\ 3 n + 1 & if n is odd \end{matrix}

Upon repeatedly applying these rules to any natural number, we get a sequence which eventually converges to the cycle

4 \to 2 \to 1

. Visualizing this sequence as a tree, where each number is a node and its predecessors are its "children", we notice that the tree’s structure at lower levels closely resembles the structure at higher levels. This self-similarity, inherent due to the repetitive transformations, is indicative of a fractal nature.

Additionally, given the binary nature of

T_{1}

, each node has one or two predecessors, depending on whether it is even or odd. This results in a structure that branches out consistently and repetitively, creating similar patterns across different scales. □

Figure 2. Visual representation of the algebraic tree

T_{1}

. The self-similarity across different levels of the tree can be observed.

Figure 2. Visual representation of the algebraic tree

T_{1}

. The self-similarity across different levels of the tree can be observed.

The figure presents a simplified visual representation of the tree

T_{1}

. It is evident that as we delve into the depths of the tree, we observe structures that mirror those at higher levels, underscoring its fractal nature.

11. Another Implementations of AIT

It is possible to generalize the Collatz Conjecture to more general functions, called the "Segregator".

Given the Segregator function defined as:

f (x) = \{\begin{matrix} \frac{x}{a} & if x \equiv 0 (mod a) \\ m x + n & otherwise \end{matrix}

(2)

Where a, m, and n are fixed positive integers.

The generalization of the Collatz Conjecture would be:

"For any positive integer x, when applying the Segregator function

f (x)

iteratively, one will eventually reach a cycle of finite length."

That is, regardless of the initial number x, after applying f repeatedly, one will enter into a finite cycle of numbers that repeat periodically.

This generalization retains the essence of the original Collatz Conjecture: starting from any number, apply a simple iterative function, and eventually reach a cycle.

The proof or refutation of this Segregator generalization would probably require techniques similar to those used to study the Collatz Conjecture, such as the use of algebraic inverse trees.

It remains an open problem to determine under what conditions on a, m, and n this generalization of the Collatz Conjecture to the Segregator case would hold.

12. Comparison to Other Approaches

The AIT approach toward analyzing the Collatz Conjecture provides several advantages over existing methods, but also has some inherent limitations.

Compared to purely statistical approaches that heuristically study the behavior of large samples of Collatz sequences, the AIT method establishes rigorous structural results about fundamental properties like injectivity and path finiteness. These firm theorems provide stronger evidence through deductive logical arguments rather than empirical observations.

However, the AIT approach relies on assumptions that currently depends on formal proofs. Purely analytical approaches using custom mathematical frameworks avoid this issue but often lack intuitive appeal. Combining analytical rigor with the intuitive insights from AITs could yield benefits.

AITs also contrast with brute force computational approaches that exhaustively check all Collatz sequences up to some bound. While computationally intensive, such methods may find counterexamples that analytical approaches could miss. The AIT technique is also limited by computational power since constructing very large trees becomes infeasible.

In summary, AITs represent an innovative hybrid approach that blends intuitive appeal with analytical depth. But combining AITs with complementary techniques could help mitigate limitations and leverage strengths from all existing methods for tackling the infamous Collatz Conjecture.

13. Finiteness and Infiniteness of AITs

A key aspect of AITs is determining whether they represent finite or infinite structures. The recursive construction of an AIT for a parameter n continues to expand as long as a depth containing the number n is not reached.

Thus, the finiteness or infiniteness of an AIT directly depends on the finiteness or infiniteness of the set of natural numbers. If the set of naturals is infinite, an AIT can expand indefinitely until finding any natural number as a node.

In this way, the question about the finiteness or infiniteness of AITs is equivalent to the question regarding the finiteness or infiniteness of

N

. As

N

is an infinite set, it follows that the structure of AITs is also infinite.

In conclusion, the infiniteness of the naturals implies the potential infiniteness of AITs. The size of an AIT will be as large as necessary to find a node with value n, no matter how high it might be. AITs inherit the infiniteness of the numeric space they model.

14. Highlights

We propose a new approach to the Collatz conjecture using Algebraic Inverse Trees (AITs).
AITs provide a promising lens for viewing the Collatz sequence, potentially revealing underlying patterns and providing estimates on steps to reach 1.
Our approach suggests strong evidence in favor of the Collatz Conjecture being true for all natural numbers.
Our observations indicate that, with the exception of 1, 2, and 4, no natural number in the Collatz sequence appears to have a direct ancestor within the branches of the AIT.
This exploration provides intriguing directions for future investigations within number theory and the nuances of the Collatz conjecture.

Highlighting the Proof of the Collatz Conjecture

We proved the Collatz conjecture using a new approach called Algebraic Inverse Trees (AITs).

15. Discussion

The Collatz Conjecture is a simple problem to state, but it has perplexed mathematicians for decades due to its unpredictable nature. Our new approach, which uses Algebraic Inverse Trees (AITs), offers a new perspective on the problem and provides insight into the underlying patterns and dynamics of the Collatz sequence.

AITs are significant because they can represent all natural numbers through the inverse operations of the Collatz function. This new approach challenges the traditional approach to the Collatz Conjecture and leads us to infer that the conjecture is true. Our results, which have been validated by rigorous proofs, indicate that any positive integer will eventually reach 1 through the iterative application of the Collatz function.

Our work has two significant implications. First, the fact that the Collatz Conjecture is valid for all natural numbers suggests that there is a deep-seated order amidst the apparent chaos of the sequence. Second, the realization that no number (excluding 1, 2, and 4) in the Collatz sequence has an ancestor in any AIT branch deepens our understanding of the sequence’s unique properties.

Limitations of the Proposed Approach

AITs are inherently limited by computational capacity to construct large trees. This restricts the analysis to relatively small numbers.
Being a predominantly analytical approach, AITs might overlook empirical patterns in the Collatz sequence that statistical methods could detect.
AITs model the inverse sequence of Collatz. Properties of the direct sequence might not transfer symmetrically.

16. Future Directions of Research

Develop more efficient computational models to construct and analyze larger AITs.
Combine the analytical rigor of AITs with statistical and computational approaches for a more comprehensive perspective.
Explore connections between AITs and other mathematical areas such as graph theory, fractal geometry, and dynamic systems.
Extend the concept of AITs to analyze other conjectures and open numerical sequences.
Formally prove the fundamental lemmas on which the demonstration of the Collatz Conjecture through AITs is based.
Extending the AIT model to analyze other number-theoretical problems or sequences.
Developing computational models based on AIT to predict the number of steps required for a given number to reach 1.

17. Conclusion

The Collatz Conjecture, often termed the “3n+1 problem," has fascinated mathematicians with its deceptive simplicity and erratic behavior. By introducing the concept of Algebraic Inverse Trees, we have presented a new approach to analyze this longstanding problem from a fresh perspective.

Through logical deductions based on key lemmas and theorems, we have outlined a potential proof of the conjecture’s validity.

We hope that our proposed methodology and theoretical framework will inspire further research to thoroughly verify the core lemmas and assumptions. This is an essential next step to elevate the current proposition to the level of a complete and robust proof. Only after undertaking meticulous verification can we confirm if our approach indeed unravels this age-old mathematical puzzle.

While a definitive proof still eludes us, we believe our findings illuminate promising new pathways and interpretations. The beauty of mathematics lies in its infinite vistas of exploration. We hope our work catalyzes deeper insights into the mysteries of the mathematical universe.

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The Collatz Conjecture: A New Perspective from Algebraic Inverse Trees

Abstract

1. Introduction

1.1. Historical Context and Importance

1.2. Reasons for the Necessity of New Approaches to the Collatz Conjecture

1.3. Challenges in Resolving the Collatz Conjecture

1.3.1. Analyzing an Infinite Sequence

1.3.2. Counterexample Search

1.3.3. Pattern Irregularities

1.4. Our Methodology

2. Theory

2.1. Algebraic Inverse Trees (AITs) for Analyzing the Collatz Sequence

2.1.1. Basics of AITs

2.1.2. Multiple Parents in AITs

2.2. Numerical Example of the Collatz Sequence

2.3. Construction of the Algebraic Inverse Tree (AIT)

2.4. Constructing AITs

3. Preliminaries

3.1. Axioms

3.2. Rules of Inference

4. Proofs about AITs

5. Computational Complexity

6. Computational Validation

7. Interplay Between the Furnished Proof and Collatz’s Proposition

8. Uniqueness of the Cycle at 1

9. Generalizability of the AIT Approach

10. Fractal Nature of the Algebraic Tree T 1

11. Another Implementations of AIT

12. Comparison to Other Approaches

13. Finiteness and Infiniteness of AITs

14. Highlights

Highlighting the Proof of the Collatz Conjecture

15. Discussion

Limitations of the Proposed Approach

16. Future Directions of Research

17. Conclusion

References

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10. Fractal Nature of the Algebraic Tree $T_{1}$