arXiv:2605.12504cs.CCcs.AI2026-05

揭示素数间隙的计算不可约性,说明无法高效预测下一个素数。

Prime Successor Irreducibility: Turing Machine Complexity, Kolmogorov Complexity, and Weakness-Based Formulations

  • 从图灵机角度定义素数间隙不可约性,证明其运行时间下限。
  • 用科尔莫戈罗夫复杂度证明典型素数间隙在尺度上不可压缩。
  • 关联筛法与弱性参数,连接素数分布与信息熵理论。

我们提出并证明了素数序列在从一个素数过渡到下一个素数时具有计算不可约性的猜想与定理。直观上,给定素数p,除在稀疏输入集外,无法设计出比逐个测试候选数是否为素数更快的通用算法来求最小大于p的素数。研究从三个互补路径展开:首先在图灵机复杂度模型(PSI-T)中形式化素数后继不可约性,建立相对于串行基线的运行时间下界;其次提出科尔莫戈罗夫复杂度形式(PSI-K),表明典型素数间隙在其尺度上是算法不可压缩的,并在标准筛法界限下无条件证明了PSI-K(c, δ)对所有固定c<1成立;第三,发展基于弱性的形式(PSI-W和PSI-W-LE),显示小集合的间隙值无法捕获显著比例的素数,且碰撞概率衰减、逻辑熵趋近于1。这些扩展至素数构型与连续间隙向量。最后,筛法框架将局部阻碍模式与塞尔伯格弱性参数联系起来。PSI-K与弱性形式将不可约性与经典素数间隙统计问题关联。利用科尔莫戈罗夫复杂度与香农熵的关系,我们推导出在二进制区间[X,2X]中素数间隙熵的严格下界。这些形式统一提供了素数序列局部不可预测性的复杂性视角,而不假设随机性或独立性。

原文摘要 · Abstract (English)

We develop conjectures and theorems expressing the idea that the prime sequence exhibits computational irreducibility in the transition from one prime to its successor. Informally, given a prime pp p, no general algorithm can compute the least prime greater than pp p substantially faster than sequentially testing candidates for primality, except possibly on sparse input sets. Our framework proceeds along complementary lines. First, we formalize Prime Successor Irreducibility in a Turing-machine complexity model (PSI-T), asserting lower bounds on running time relative to a sequential baseline. Second, we propose a Kolmogorov-complexity formulation (PSI-K), asserting that typical prime gaps are algorithmically incompressible at their scale; we prove PSI-K(c, $δ$) unconditionally for all fixed c<1 using standard sieve bounds. Third, we develop weakness-based formulations: PSI-W (sparse-set anti-concentration) shows no small menu of gap values captures a noticeable fraction of primes, while PSI-W-LE shows collision probabilities decay and logical entropy tends to 1. These extend to prime constellations and consecutive gap vectors. Finally, a sieve-theoretic framework connects local obstruction patterns to Selberg weakness parameters. The PSI-K and weakness formulations connect irreducibility to classical statistical questions about prime gaps. Using the relationship between Kolmogorov complexity and Shannon entropy, we derive rigorous lower bounds on prime gap entropy in dyadic intervals [X,2X]. Together, these formulations provide a unified complexity-theoretic perspective on the apparent local unpredictability of the prime sequence, without asserting randomness or independence.

素数分布计算复杂性信息熵

Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。