Multi-Root Trust Architecture for Quantum-Resilient AI Inference: ASIL-M and the IETF RATS Framework

This technical appendix provides the complete mathematical and engineering specification for hybrid quantum-classical AI safety within the AxoDen framework. The document establishes compositional safety guarantees for systems integrating classical data processing with quantum components. It addresses failure modes that escape classical safety standards: decoherence, entanglement leakage, correlated noise, and quantum fabrication (hallucination via adaptive measurement or variational circuits). Part I (Sections 2-6) establishes classical foundations: Entropy-Bounded Data Pipelines (EBDP) and Entropy-Frugal Intelligence (EFI), providing compositional theorems, surplus statistics for fabrication detection, and variational state reconciliation. Part II (Sections 7-11) extends all classical results to quantum systems using von Neumann entropy, conditional quantum mutual information (CQMI), and CPTP maps. Theorems provide compositional bounds for sequential and DAG-structured quantum pipelines. Part III (Sections 12-17) covers practical estimation via shadow tomography, certification protocols mapping to ISO 26262, DO-178C, and IEC 61508, runtime monitoring with ASIL-aware mitigation policies, and application case studies including a 10,000km quantum IMU deployment scenario. This document is the detailed technical companion to the published foundational papers (Zenodo DOIs 10.5281/zenodo.18213048, 10.5281/zenodo.18282922). Keywords: quantum AI safety, hybrid quantum-classical systems, entropy bounds, compositional verification, CPTP maps, shadow tomography, certifiable AI, functional safety, ISO 26262, DO-178C