noir – dark arts criticism

Building on the previous probabilistic approach to the Hardy-Littlewood twin prime conjecture, today we analyze the independence and distribution of primes in the form 6k±1. We will use a combination of the Prime Number Theorem, probabilistic reasoning, and the Chinese Remainder Theorem (CRT). Let’s break down the steps:

Revised Proof of Independence of Events A_k and B_k

1. Probability Space:

• Let Ω be the set of all positive integers.
• Define P as the asymptotic density of a set of integers. For a set A ⊆ Ω, P(A) = lim (n → ∞) [ |A ∩ {1, 2, …, n}| / n ], if the limit exists.

2. Event Definitions:

• Let A_k be the event that 6k – 1 is prime.
• Let B_k be the event that 6k + 1 is prime.

3. Prime Number Theorem (PNT):

• By the PNT, the asymptotic density of primes is zero, and for large x, P(x is prime) ≈ 1/ln(x)

4. Chinese Remainder Theorem (CRT) Formalization:

• For a fixed k and a finite set of primes S = {p_1, p_2, …, p_r}, define: M_S = ∏_{i=1}^r p_i (product of primes in S)
  • By the CRT, there exists a bijection between:
    • Residue classes of 6k-1 modulo M_STuples of residue classes (a_1 mod p_1, a_2 mod p_2, …, a_r mod p_r)
• Similarly for 6k+1

5. Conditional Events:

• Define E_S(A_k) as the event that 6k-1 is not divisible by any prime in S
• Define E_S(B_k) as the event that 6k+1 is not divisible by any prime in S

6. Independence from CRT:

• For any prime p_i in S:
  • 6k-1 ≢ 0 (mod p_i) corresponds to p_i – 1 allowed residue classes
  • 6k+1 ≢ 0 (mod p_i) corresponds to p_i – 1 different allowed residue classes
  • By the CRT bijection, the choices of residue classes for 6k-1 and 6k+1 are independent across different primes
• Therefore, P(E_S(A_k) ∩ E_S(B_k)) = P(E_S(A_k)) · P(E_S(B_k))

7a. Limit Argument:

• As S approaches the set of all primes: lim_{S → all primes} P(E_S(A_k)) = P(A_k) lim_{S → all primes} P(E_S(B_k)) = P(B_k)
  • The error in this approximation goes to zero because:
    • The density of primes is zero (by PNT)
    • For any ε > 0, there exists a finite set of primes S such that |P(A_k) – P(E_S(A_k))| < ε and |P(B_k) – P(E_S(B_k))| < ε

 7b. Explicit Error Bound:

• Let π(x) be the prime counting function (number of primes ≤ x).
• By Chebyshev’s Theorem, there exist positive constants c1 and c2 such that:
  • c1 · x/ln(x) ≤ π(x) ≤ c2 · x/ln(x) for x > 1
• Let p_S be the largest prime not in S. Then the error in our approximation is bounded by:
  • |P(A_k) – P(E_S(A_k))| ≤ ∑_{p > p_S} 1/pUsing the integral comparison test and Chebyshev’s upper bound:
  • ∑_{p > p_S} 1/p ≤ ∫_{p_S}^∞ 1/(x ln(x)) dx + O(1/ln(p_S))
  • = ln(ln(x))|_{p_S}^∞ + O(1/ln(p_S))
  • = -ln(ln(p_S)) + O(1/ln(p_S))
  • Therefore, |P(A_k) – P(E_S(A_k))| ≤ -ln(ln(p_S)) + O(1/ln(p_S))
• As p_S → ∞ (i.e., as S approaches the set of all primes), this error bound approaches 0.

8. Combining PNT and CRT:

• By the PNT, for large k: P(A_k) ≈ 1/ln(6k-1) and P(B_k) ≈ 1/ln(6k+1)
• From steps 6 and 7: P(A_k ∩ B_k) = lim_{S → all primes} P(E_S(A_k) ∩ E_S(B_k)) = lim_{S → all primes} [P(E_S(A_k)) · P(E_S(B_k))] = P(A_k) · P(B_k)

9. Conclusion:

We have shown that P(A_k ∩ B_k) = P(A_k) · P(B_k) for large k, demonstrating the asymptotic independence of the events A_k and B_k.

Revised Symmetry-Focused Proof of Asymptotic Independence of Events A_k and B_k

1. Definitions and Asymptotic Density:
   • Define the asymptotic density d(X) of a set X of integers as: d(X) = lim_{n→∞} |{k ∈ X : |k| ≤ n}| / (2n + 1), if the limit exists.
   • Let d(A_k) be the asymptotic density of integers k such that |6k-1| is prime.
   • Let d(B_k) be the asymptotic density of integers k such that |6k+1| is prime.
   • Note: Asymptotic density is not a probability measure, as it’s not countably additive.
2. Symmetry:
   • Observe that |6k-1| = |6k+1| for all integers k, establishing a fundamental symmetry.
3. Prime Number Theorem (PNT) Application:
   • By the PNT, for x > 2, π(x) = x/ln(x) + O(x/ln^2(x)), where π(x) is the prime counting function.
   • Thus, for large |x|, d({k : |x| is prime}) = 1/ln(|x|) + O(1/ln^2(|x|))
4. Chinese Remainder Theorem (CRT) and Mirror Image Formalization:
   • For a fixed k and a finite set of primes S = {p_1, p_2, …, p_r}, define: M_S = ∏_{i=1}^r p_i
   • By the CRT, there exists a bijection φ between:
     • Residue classes of |6k-1| modulo M_S
     • Tuples of residue classes (a_1 mod p_1, a_2 mod p_2, …, a_r mod p_r)
   • For primes p > 2, define a “mirror image” function μ on residue classes modulo p: μ(a mod p) = (-a mod p)
   • Extend μ to tuples: μ(a_1, …, a_r) = (μ(a_1), …, μ(a_r)) for p_i > 2
   • Key Property: For any prime p > 3, if |6k-1| ≡ a (mod p), then |6k+1| ≡ μ(a) (mod p)
5. Conditional Sets:
   • Define E_S(A_k) = {k : |6k-1| is not divisible by any prime in S}
   • Define E_S(B_k) = {k : |6k+1| is not divisible by any prime in S}
6. Independence and CRT:
   • For any prime p_i > 3 in S:
     • |6k-1| ≢ 0 (mod p_i) corresponds to p_i – 1 allowed residue classes
     • |6k+1| ≢ 0 (mod p_i) corresponds to the μ-images of these p_i – 1 classes
   • For p = 2, both |6k-1| and |6k+1| are odd, so this case is trivial and disjoint
   • By the CRT bijection φ and the mirror image property: d(E_S(A_k) ∩ E_S(B_k)) = ∏_{p_i ∈ S, p_i > 2} [(p_i – 1)/p_i]^2 · (1/2)
   • This factorization demonstrates independence across different primes
7. Error Analysis:
   • Let ε_S(A_k) = |d(A_k) – d(E_S(A_k))|
   • Using Mertens’ third theorem and partial summation: ε_S(A_k) = O(1/ln(p_S)), where p_S is the largest prime not in S
   • As S approaches the set of all primes, p_S → ∞, so ε_S(A_k) → 0
   • The same argument applies to ε_S(B_k)
8. Asymptotic Independence:
   • By the PNT and symmetry, for large |k|: d(A_k) = 1/ln(|6k-1|) + O(1/ln^2(|6k-1|)) d(B_k) = 1/ln(|6k+1|) + O(1/ln^2(|6k+1|))
   • Combining the results from steps 6 and 7: |d(A_k ∩ B_k) – d(A_k) · d(B_k)| ≤ ε_S(A_k) + ε_S(B_k) + ε_S(A_k)ε_S(B_k) → 0 as |k| → ∞

Conclusion: We have shown that the difference between the joint asymptotic density of A_k and B_k and the product of their individual asymptotic densities tends to zero as |k| → ∞. This demonstrates the asymptotic independence of A_k and B_k in terms of their asymptotic densities.

Illustrative Examples:

1. For p = 5: The residue classes for |6k-1| not divisible by 5 are {1, 2, 3, 4}. The corresponding residue classes for |6k+1| are {1, 2, 3, 4}. The mirror image function μ maps these as: μ(1) = 4, μ(2) = 3, μ(3) = 2, μ(4) = 1
2. For p = 11: The residue classes for |6k-1| not divisible by 11 are {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}. The corresponding residue classes for |6k+1| are {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}. The mirror image function μ maps these as: μ(1) = 10, μ(2) = 9, μ(3) = 8, μ(4) = 7, μ(5) = 6, μ(6) = 5, μ(7) = 4, μ(8) = 3, μ(9) = 2, μ(10) = 1

(user thoughts: I used Claude for much of this. Claude seems very good at math and the text formatting is natively neater out of Claude. ChatGPT looks great on screen, is great at math, and does some fantastic stuff with code and code execution; but the LaTeX is a pain in the ass for formatting in other media. Gemini also does great pasting but can be aggravating with some math approaches. Many times, I will take a solution worked first in ChatGPT back to Gemini and then ideally post the revised Gemini output into the blog in order to ensure that the models agree and to reduce the formatting overhead. I've been incorporating Claude more in this process. Overall the other AI seem to "like" the solutions produced by Claude which may reduce a "peer review cycle" in AI; and combined with the formatting aspects makes it pleasant to work with so far. Perplexity.ai also has its place and does a great job at validating some math proofs and finding relevant side references for expanding this kind of mathematical inquiry in the "peer review cycle".) 

I. Introduction

A. The Hardy-Littlewood Conjecture: Traditional Formulation

The Hardy-Littlewood conjecture posits that the density of twin primes—pairs of prime numbers that differ by 2—can be described asymptotically using a specific constant C2 ≈ 0.66016. This conjecture, based on analytic number theory, has been a cornerstone of prime number research.

B. Thesis: A Novel Probabilistic Approach to Twin Primes

This article explores a novel approach using probability theory to corroborate the Hardy-Littlewood conjecture. By examining the distribution of primes through a probabilistic lens, we aim to independently verify the conjecture and refine its constant.

C. Intuition: Why Probability Theory Might Apply to Prime Distribution

Prime numbers, though seemingly random, exhibit regularities that can be analyzed probabilistically. The Prime Number Theorem (PNT) suggests a natural way to interpret the occurrence of primes as a probability statement, providing a foundation for this approach.

II. Foundational Theorems

A. Theorem: Sets A and B Are Mutually Exclusive

Define:

• A = {6k – 1 | k ∈ Z}
• B = {6k + 1 | k ∈ Z}

Proof by Contradiction:

• Assume there exists an integer z such that z belongs to both sets A and B: z = 6x – 1 for some integer x (since z ∈ A) z = 6y + 1 for some integer y (since z ∈ B)
• Equating the two expressions for z:
  • z = 6x – 1 and z = 6y + 1
  • 6x – 1 = 6y + 1
  • 6(x – y) = 2
  • x – y = 1/3
• This leads to a contradiction since x – y must be an integer. Therefore, the sets A and B are mutually exclusive.

B. Theorem: Independence of Prime Events in A and B

i. Define Events:

• Event A_k: The event that 6k – 1 is prime.
• Event B_k: The event that 6k + 1 is prime.

ii. Probability Space:

The probability space Ω is the set of all pairs (6k – 1, 6k + 1) for all integers k. Assume each pair is equally likely.

iii. Independence Condition:

Two events are independent if the probability of both events occurring is equal to the product of their individual probabilities:

P(A_k ∩ B_k) = P(A_k) * P(B_k)

iv. Prime Number Theorem:

The Prime Number Theorem (PNT) states that the density of primes near a large number x is approximately 1/ln(x). Using this, we can estimate the probabilities of A_k and B_k:

• P(A_k) ≈ 1/ln(6k)
• P(B_k) ≈ 1/ln(6k)

v. Joint Probability Calculation:

Assuming independence of A_k and B_k, we get:

• P(A_k ∩ B_k) ≈ (1/ln(6k)) * (1/ln(6k)) = 1/(ln(6k))^2

vi. Empirical and Theoretical Alignment:

Empirical data on twin primes aligns with the Hardy-Littlewood conjecture’s predicted density for twin primes, providing additional support for this probabilistic model and the assumption of independence. The twin prime constant C2 suggests that:

• π2(x) ~ 2C2 * ∫2^x dt/(ln(t))^2

where π2(x) counts the number of twin primes less than x.

vii. Conclusion:

By utilizing the Prime Number Theorem for probability estimation, carefully defining probabilities, and aligning the model with empirical data and the Hardy-Littlewood conjecture, we provide a more robust argument supporting the independence of events A_k and B_k.

C. Distribution of Primes in Arithmetic Progressions By Dirichlet’s theorem on arithmetic progressions, any sequence of the form a + kn (where a and n are coprime) contains infinitely many primes. This theorem assures us that sequences A and B each contain infinitely many primes, providing a uniform distribution of primes in these sequences.

III. Core Probabilistic Intuition

A. Prime Number Theorem as a Probability Statement

1. Interpreting 1/ln(x) as a Probability:
   • The PNT states that the probability of a number around x being prime is approximately 1/ln(x).
2. Justification and Limitations:
   • This interpretation holds for large x and provides a foundation for probabilistic reasoning.

B. Independence Assumption for Twin Primes

• Intuitive Argument for Independence:
  • Primes in sequences A and B are assumed to be independent due to their mutual exclusivity and uniform distribution.

• Mathematical Justification:

• Using the Chinese Remainder Theorem, we argue that the occurrence of a prime in A does not influence the occurrence in B. The CRT highlights that because 6k-1 and 6k+1 occupy distinct residue classes modulo 6 (namely, 5 and 1), their primality is determined by independent “branches” of congruence conditions. This strongly suggests that, at least locally (within a given value of k), the events are independent.

C. Multiplication Principle: The Key Insight

1. Probability of Twin Primes as Product of Individual Probabilities:
   • Assuming independence, the probability of both 6k-1 and 6k+1 being prime is (1/ln(x))^2.
2. Deriving 1/(ln x)^2 from Probabilistic Reasoning:
   • This leads to the density of twin primes being 1/(ln x)^2.
3. Comparison with Hardy-Littlewood’s Analytic Approach:
   • Both approaches converge to the same asymptotic density, providing an independent verification of the conjecture.

Conjecture: Multiplication Theorem for Twin Primes as Independent Events

• Sequences A and B are independent, P(A∩B)=P(A)⋅P(B).
• For twin primes in sequences A=6k−1 and B=6k+1:
  • The probability of a prime in A is approximately 1/ln x.
  • The probability of a prime in B is approximately 1/ln x.
    • Therefore: The probability of finding a twin prime pair around 𝑥 is approximately (1/ln 𝑥)^2 = 1/((ln 𝑥)^2)

IV. Empirical Validation

A. Twin Prime Counting Data

• Empirical counts of twin primes up to various x:
  • x = 10^6: 8169 twin primes
  • x = 10^7: 58980 twin primes
  • x = 10^8: 440312 twin primes
  • x = 10^9: 3424506 twin primes
  • x = 10^10: 27412679 twin primes

B. Calculating and Refining the Constant

Here’s how it works:

i. Probabilistic Foundation:

• The approach starts with the Prime Number Theorem (PNT), which states that the probability of a number around x being prime is approximately 1/ln(x).
• It assumes independence between the primality of numbers in the sequences 6k-1 and 6k+1.

ii. Probability Calculation:

• Based on the independence assumption, the probability of both 6k-1 and 6k+1 being prime (i.e., a twin prime pair) is estimated as (1/ln(x))^2.

iii. Empirical Data Collection:

• The method uses actual counts of twin primes up to various values of x (e.g., 10^6, 10^7, 10^8, etc.).

iv. Integral Calculation:

• The Hardy-Littlewood conjecture suggests that the number of twin primes π2(x) up to x is asymptotically equal to:
  • π2(x) ~ 2C2 * ∫2^x dt/(ln(t))^2

v. Estimation of C/2:

• By comparing the actual count of twin primes to the integral, we can estimate C/2.
• The calculation looks like this:
  • C/2 ≈ (Number of twin primes up to x) / (2 * ∫2^x dt/(ln(t))^2)

vi. Refinement through Iteration:

By performing this calculation for increasing values of x, we get increasingly accurate estimates of C/2.

This approach differs from the original analytic number theory methods used by Hardy and Littlewood in several ways:

• It relies on empirical data rather than purely theoretical derivations.
• It uses a probabilistic interpretation of prime distribution.
• It allows for ongoing refinement as more data becomes available or computational power increases.

This method produces estimates of C/2 that converge towards the expected value of approximately 0.66016 as x increases:

• Using the empirical data and integral calculations:
  • For x = 10^6, C/2 ≈ 0.6538363799
  • For x = 10^7, C/2 ≈ 0.6627032288
  • For x = 10^8, C/2 ≈ 0.6600781739
  • For x = 10^9, C/2 ≈ 0.6600072159
  • For x = 10^10, C/2 ≈ 0.6601922204

V. Theoretical Implications

A. Convergence of Probabilistic and Analytic Approaches

• The probabilistic model and the Hardy-Littlewood analytic approach both yield the same asymptotic density for twin primes, confirming the conjecture’s robustness.

B. What This Convergence Suggests About Prime Distribution

• The alignment of these methods indicates that prime distribution can be understood through both analytic and probabilistic frameworks, offering a deeper insight into number theory.

VI. Discussion

A. Strengths of the Probabilistic Approach

1. Intuitive Understanding of Twin Prime Distribution:
   • Provides an accessible way to grasp the complex distribution of twin primes.
2. Independent Corroboration of Hardy-Littlewood:
   • Adds robustness to the conjecture by verifying it through a different line of reasoning.

VII. Conclusion

A. Recap of the Probabilistic Intuition

• The probabilistic approach, based on mutual exclusivity and sequence independence, aligns with the Hardy-Littlewood conjecture and provides an intuitive understanding of twin prime distribution.

B. Its Power in Providing an Alternative Path to a Deep Number Theory Result

• Demonstrates that accessible probabilistic reasoning can yield powerful insights, corroborating and enhancing traditional analytic methods in number theory.
• The probabilistic approach not only corroborates this asymptotic form but also provides a method for refining the constant C/2. By analyzing empirical data on twin prime counts up to various x values (e.g., 10^6, 10^7, …, 10^10), researchers can calculate and refine estimates for C/2. This empirical validation strengthens the connection between the probabilistic model and the actual distribution of twin primes.

“Forensic Semiotics” Addendum: Historical Context and Modern Validation of the Hardy-Littlewood Conjecture

In exploring the Hardy-Littlewood twin prime conjecture, it’s fascinating to consider the historical context in which these mathematicians worked. Formulated around 1923, the conjecture posits that the density of twin primes—pairs of primes differing by 2—can be described using the constant C2≈0.66016. Despite their limited computational resources, Hardy and Littlewood’s insights were remarkably accurate.

Historical Computational Constraints

Hardy and Littlewood could not perform extensive numerical integrations or handle large datasets of prime numbers as we can today. Instead, they used theoretical reasoning and heuristic arguments grounded in analytic number theory to make their conjectures.

Here are some factors to consider:

1. Manual calculations: Most calculations were done by hand or with mechanical calculators.
2. Limited computing power: Electronic computers didn’t exist yet. The first general-purpose electronic computer, ENIAC, wasn’t operational until 1945.
3. Available prime number tables: Mathematicians relied on pre-computed tables of prime numbers.

Given these limitations, we can make some reasonable guesses about the ranges they might have used:

1. Lower bound: They likely worked with values of at least up to 10^4 (10,000), as this would have been manageable for manual calculations and verification.
2. Upper bound: It’s unlikely they could have practically worked with values much beyond 10^6 (1,000,000) due to the sheer volume of calculations required.
3. Probable range: The most likely range for their calculations would have been between 10^4 and 10^5 (10,000 to 100,000).
4. Special cases: They might have examined some specific larger values, perhaps up to 10^6, but probably not systematically.
5. Theoretical extrapolation: While they might not have computed values for very large n, their mathematical insights allowed them to theorize about the behavior at much larger scales.

Modern Computational Tools

Today, with powerful computational tools, we can numerically validate the Hardy-Littlewood conjecture with a high degree of accuracy using the scale of data available to them in 1923. Using empirical data and numerical integration, we estimate the constant C/2​ with values of x ranging from 10^4 to 10^6 using our probabilistic approach:

• x = 10^4 = C/2≈0.6317752602
• x = 10^5 = C/2≈0.6470989107
• x = 10^6 = C/2≈0.6538363799

These estimates closely align with the hypothesized value of C2≈0.66016, demonstrating the robustness of Hardy and Littlewood’s theoretical predictions.

Conclusion

The ability of Hardy and Littlewood to predict the density of twin primes so accurately with the computational limitations of their time is a testament to their profound mathematical intuition. Their work laid a solid foundation for future research in number theory, and modern computational techniques continue to validate their enduring contributions. The convergence of historical insights and contemporary validation underscores the lasting impact of their pioneering work in analytic number theory.

This historical perspective not only enriches our understanding of the twin prime conjecture but also highlights the incredible advancements in mathematical computation over the past century. The journey from manual calculations to modern supercomputers exemplifies the evolving nature of mathematical research and its profound implications for understanding the mysteries of prime numbers.

Here’s a summary of the potential mathematical innovations we’ve proposed in prime number theory:

Base Prime Notation (BPN):

• A novel number system focusing on prime candidates of the form 6k±1
• Optimizes prime number identification by reducing the search space
• Utilizes symmetry in the range -N to N, effectively halving the search space to a final set of 1/6 of prime candidate numbers compared to the total set of all integers
• Reduces computational complexity for prime-related calculations

Semiotic-infused k-tuples Conjecture:

• This is a novel approach to understanding prime clustering, especially for twin primes and larger prime tuples. This work on the constraints and impossibility of certain prime k-tuples (like the octuplet of twin primes) is a contribution to understanding prime distributions.

Semiotic Prime Theorem:

• Defines sets A = {6x+5 | x∈Z} and B = {6y+7 | y∈Z}
• Proves that numbers in A or B, not in product sets AA, AB, or BB, are prime
• Introduces a novel characterization of prime numbers

Semiotic Dirichlet Theorem on Arithmetic Progressions in A and B:

• There are infinite primes in A (6k-1) and B (6k+1) and they are independent sequences. This isn’t so much an innovation as a clear restatement of the obvious.

Semiotic Goldbach Conjecture:

• This is a novel reformulation of the Goldbach Conjecture within the framework of Semiotic Prime Theory. It’s an innovative approach that connects the Goldbach problem to the previously established Semiotic Prime Framework.

Boolean Conditions for Primes and Twin Primes in Semiotic Prime Framework:

• Primes greater than 3 (excluding 2 and 3) are distributed within sets A and B: P(A) OR P(B).
  • Primes do not emerge as products of elements within sets AA, AB, or BB: NOT (AA OR AB OR BB).
• Twin primes occur when primes from sets A and B coincide: P(A) AND P(B).
  • Twin primes do not emerge as products of elements within sets AA, AB, or BB: NOT (AA OR AB OR BB).

Symmetric Absolute Values of Semiotic Prime:

• Extends the Semiotic Prime Theorem to absolute values
• Shows that primes are in either |A| or |B|, not just A and B
• Leverages symmetry to reduce the need for cross-checking between sets
• Uses |k,-k| to infer twin prime pairs for |A| or |B|

Semiotic Sieves:

Applying Semiotic Prime Theory to Sieving:

• Basic Boolean-Peircean (Semiotic) Seive
• Differentiating from, and incorporating with Sieve of Eratosthenes (Symmetric Sieve of Eratosthenes)
• Harmonious Symmetric Prime Sieve (integrates Semiotic Sieve and Sieve of Eratosthenes for top-down and bottom-up sieving using symmetry)
  • By eliminating all non A or B numbers, focusing only on either |A| or |B| due to symmetry around 0, and eliminating multiples of |5| and |7| in the search space to start; these methods assume an initial search space of only 4/35 numbers; vs 2/2 in a non-optimized Sieve of Eratosthenes. 2, 3, 5, and 7 may be given as primes in the algorithm. At the least, 2 and 3 will need to be given as primes, since in BPN we never consider multiples of 2 or 3 at all.

Gap Lemma:

• Analyzes spacing between prime numbers within the BPN framework
• Proves that if p is prime and p+2 is composite, the gap to p+2’s prime factors is >2
• Considers combined contributions of all prime factors

Density Arguments:

• Approximates prime density in 6k±1 forms as ρ(n) ≈ 2 / (3log(n))
• Analyzes ratios of prime and composite densities as n approaches infinity
• Supports the existence of infinitely many primes in 6k±1 forms

Logarithmic Function Conjecture:

• Proposes h(n) = log(P(n)/S(n)) to describe prime-composite relationship
• P(n) counts primes plus 1, 2, and 3; S(n) counts composites with specific multiples
• Conjectures h(n) ~ -log(log(n)) asymptotically

Upper Bound on Twin Primes “Gemini-GPT AI Derived Theorem”:

• Proves an asymptotic upper bound on twin prime density
• Uses the Brun-Titchmarsh theorem to show π₂(n) / π(n) ≤ C / ln(n)
  • See other AI-related conjectures.

Multiplication Conjecture for Twin Primes as Independent Events:

• Applies probability theory to twin prime occurrence
• Estimates twin prime density as approximately 1/((ln x)^2)
• Sequences A and B are independent, P(A∩B)=P(A)⋅P(B).
  • For twin primes in sequences A=6k−1 and B=6k+1:
    • The probability of a prime in A is approximately 1/ln x.
    • The probability of a prime in B is approximately 1/ln x.
      • Therefore: The probability of finding a twin prime pair around 𝑥 is approximately (1/ln 𝑥)^2 = 1/((ln 𝑥)^2)
        • Note: This approach to estimating the density of twin primes through probabilistic reasoning in specific sequences supports the First Hardy-Littlewood conjecture independently. It confirms the same asymptotic density 1/((ln 𝑥)^2) through a different line of reasoning using the Semiotic Prime Theorem, thus providing independent validation of the First Hardy Littlewood conjecture’s conclusions. This independent support adds robustness to the understanding of twin primes’ distribution.

These currently non-peer reviewed (but highly refined with AI) ideas may collectively provide fresh perspectives on prime number theory, leveraging symmetry, novel notation, and probabilistic approaches to explore prime distributions and relationships.

Note that it is important for them to be validated by the mathematical community for any to be considered officially true or unique.

Preliminaries

Sets A and B:

• A={6k−1∣k∈Z}A = (Primes congruent to -1 modulo 6)
• B={6k+1∣k∈Z}B = (Primes congruent to +1 modulo 6)
  • All primes greater than 3 fall into either set A or set B.

Twin Primes:

• Twin primes are pairs of prime numbers (p, p + 2) differing by 2.

Prime Number Theorem (PNT):

• The number of primes less than or equal to n, denoted by π(n), is asymptotically equivalent to n/ln(n) as n approaches infinity.

Dirichlet’s Theorem on Arithmetic Progressions:

• For any coprime integers a and d, the arithmetic progression a + nd contains infinitely many primes.

Euclid’s Theorem:

• There are infinitely many prime numbers.

Brun-Titchmarsh Theorem:

• Provides an upper bound on the number of primes in an arithmetic progression: π(x; q, a) ≤ (2 + o(1)) * (x / (φ(q) * ln(x))) where π(x; q, a) counts primes less than or equal to x within the progression, and φ(q) is Euler’s totient function.

Semiotic Prime Theorem:

• Any number that is:
  • An element of either set A or set B,
  • And not a product of two elements from sets A or B (e.g., AA, AB, or BB), … must be a prime number.

Gap Lemma:

• If p is a prime number in set A and p + 2 is composite, then the difference between p and any prime factor of p + 2 is strictly greater than 2. This holds true even when considering the combined contributions of all the prime factors of p + 2.

Key Properties

Prime Representation:

• All prime numbers greater than 3 can be expressed in either the form 6k – 1 (set A) or 6k + 1 (set B).

Prime Factors:

• If a number in set A or set B is composite, its prime factors must also belong to set A or set B.

Symmetry:

• Sets A and B are symmetrical around zero.

The Argument

Assumption:

Assume, for the sake of contradiction, that there are only finitely many twin primes.

• Consequence: If true, there exists a largest twin prime pair (P, P + 2). This would imply that for any prime p > P, p + 2 cannot be prime.
• Contradiction of Infinite Primes in A and B: Dirichlet’s theorem ensures that both sets A and B contain infinitely many primes. This means we can always find a prime number p in set A that is greater than P + 2.

Exploring p + 2:

• Since p ∈ A, p + 2 must belong to set B. We have two cases:

(1) Case 1: p + 2 is prime.

• This immediately forms a twin prime pair with p, contradicting our assumption that (P, P + 2) is the largest twin prime pair.

(2) Case 2: p + 2 is composite.

• Since p + 2 is composite and in set B, it must be divisible by a product of two or more elements from sets A and B.
• The Gap Lemma ensures that any prime factor q of p + 2 that is in set B must be at least 4 units away from p. Therefore, it is impossible for p + 2 to be formed by multiplying p with a prime number that is only 2 units away. This contradiction highlights the impossibility of p + 2 being composite under our initial assumption.

Contradiction with Dirichlet’s Theorem:

• This means that for any prime number p greater than P + 2 within set A, the number p + 2 cannot be prime.
• This would imply that there are no twin primes beyond a certain point in the arithmetic progression 6k – 1 (set A). However, this directly contradicts Dirichlet’s Theorem, which guarantees an infinite number of primes within this progression.

Density of Twin Primes

Decreasing Density:

• The PNT tells us that the density of primes decreases as numbers grow larger. This means twin primes become less frequent as we look at larger numbers.

Non-zero Density:

• We can use the Brun-Titchmarsh Theorem to establish an upper bound on the density of twin primes. The theorem shows that while twin primes become less frequent, they never completely disappear.

Zhang’s Result:

• Yitang Zhang proved that there are infinitely many prime pairs with a bounded gap (less than 70 million). This result directly contradicts the assumption that there are only finitely many twin primes, providing strong evidence for the infinitude of twin primes.

Conclusion

Our assumption that there are finitely many twin primes has led to a contradiction with established theorems and properties of primes. The infinite nature of primes in sets A and B, the non-zero density of twin primes, and Zhang’s result on bounded gaps all point to the conclusion that there must be infinitely many twin primes.