The Paradox of Statistical Collapse in Goldbach's Conjecture: An Approach Based on the Laplace Distribution and the Dirac Delta Function

This paper presents a probabilistic framework for analyzing Goldbach’s strong conjecture, inspired by the statistical modeling proposed by Maximiliano Mozetic (2025). The central argument revolves around the so‑called paradox of statistical collapse: when modeling the frequency of Goldbach partitions through a Laplace distribution centered at , the distribution converges, in the asymptotic limit , to a Dirac delta function. This collapse concentrates all probability at the point , which leads to a structural contradiction, since for most even integers , the value  is composite. The implications of this result are discussed in relation to the validity of the conjecture and the limitations of statistical heuristics compared to the rigor of analytic number theory.