Goldbach Bound Test Program

Description

This paper develops a computational and analytical framework for inves-
tigating bounds on the Goldbach partition function
푅(2푚)
for even integers
2푚
. We study the inequality
17
50
휋(2푚)
2
2푚
≤ 푅(2푚) ≤
5
4
휋(2푚)
2
2푚
,
,
using empirical datasets of the prime-counting function
휋(푥)
and known
values of
푅(2푚)
.
A normalized representation of the partition function is introduced in the
form
푅(2푚) =
휋(2푚)
2
2푚 푠
,
where
acts as a scaling parameter linking additive Goldbach structure
to quadratic prime-density growth. This formulation induces a fixed con-
straint interval
4
5
≤ 푠
50
17
.
Computational analysis across multiple scales shows that
remains
tightly bounded and numerically stable, with values clustering near an
empirical constant
≈ 1.139.
Equivalently, the framework yields the reconstruction identity
휋(2푚) =
2푚 푅(2푚) 푠
,
demonstrating that the prime-counting function, Goldbach partition func-
tion, and normalization parameter are structurally coupled.
These results suggest that the Goldbach partition function behaves as a
renormalized quadratic prime-density model governed by a stable normaliza-
tion structure. The proposed framework validates the bounds and reveals an
intrinsic coupling between prime distribution and additive partition behav-
ior, providing a basis for refined asymptotic modeling and further theoretical
investigation.

Authors

DOI: 10.5281/zenodo.20696920

Publication Date: 2026-06-13

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