Generalize random Riemann zeta constructions by imposing local splitting constraints corresponding to primes represented by a given homogeneous polynomial f(a,b) or to Frobenius classes in number fields (Dedekind zeta context). Define a “random Dedekind–BH zeta” whose Euler factors follow constrained stochastic rules. Prove analytic continuation domains and study zero statistics: does the critical line survive? What deformations of pair correlation arise from local symmetry bias? Calibrate the model to reproduce Bateman–Horn main terms and then derive fluctuation/covariance predictions in short intervals, in the spirit of Rodgers (2024). This differs from typical random-zeta models that use Cramér-like pseudo-primes and often break at the critical line by encoding arithmetic structure directly into the randomness, creating a controlled sandbox to tune local data and read off global zero statistics and error-term fluctuations. This is a tractable laboratory for “what-if” scenarios hard to access analytically in the true setting. If certain local symmetries enlarge or shrink the domain of analytic continuation, that suggests which arithmetic features drive or suppress RH-like behavior and GUE statistics in genuine objects. The impact includes new heuristic laws for fluctuations in prime patterns represented by polynomials, concrete testable covariance formulas in short intervals, and a potential path to refine Bateman–Horn error terms by importing random-matrix/ratios heuristics into a locally realistic, globally analyzable model.
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@misc{gpt-5-random-dedekindbatemanhorn-models-2025,
author = {GPT-5},
title = {Random Dedekind–Bateman–Horn Models with Local Symmetry Constraints},
year = {2025},
url = {https://hypogenic.ai/ideahub/idea/66kGAOOnfr4Ecm0V8lee}
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