H2E: Hilbert-to-Expert Geometric Governance: Grounding Autonomous AI Safety in the Riemann Hypothesis and Hilbert-Pólya Conjecture

We present H2E (Hilbert-to-Expert), a mathematical AI governance framework that embeds the spectral structure of the Riemann Hypothesis (RH) and the Hilbert-Pólya Conjecture (HPC) directly into the safety layer of a large language model (LLM)-based autonomous agent. The framework constructs a self-adjoint Hilbert-Pólya operator whose spectrum coincides with the imaginary parts of the nontrivial zeros of the Riemann zeta function.

The full code is available in GitHub: https://github.com/frank-morales2020/MLxDL/blob/main/RH_HPC_H2E_JEPA.ipynb