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[English Abstract] Official Preprint DOI: 10.5281/zenodo.24041601 Series: Autonomous Infrastructure & Deterministic Quantum Systems Monograph Series Author: Hasebe, Yoko (長谷部 洋子) Affiliation: Lead Researcher, Autonomous Infrastructure Systems, Autonomous Living & Physical Infrastructure Institute, Iwakuni, Yamaguchi, Japan License & Integrity Covenant: Creative Commons Attribution 4.0 International (CC BY 4.0) with Strict No-Learn Covenant (NLL-v1.0-2026) In advanced Cyber-Physical Systems (CPS)—spanning Autonomous Traffic Control Systems (ATCS) for orbital space debris, COLREGs-compliant marine navigation, and human-collaborative edge robotics—Large Language Models (LLMs) and probabilistic Artificial General Intelligence (AGI) provide high-level semantic reasoning. However, their inherent non-determinism and hallucination risks render them structurally unfit for direct physical-layer actuation. This monograph establishes a four-pillar mathematical, cryptographic, thermodynamic, and legal governance architecture for next-generation autonomous infrastructure: 1. Integrated Governance of Probabilistic AI and Deterministic Physical Layers: We formulate a Control Decomposition framework coupling high-level semantic modules with a deterministic runtime shield powered by Tunable Input-to-State Safe Control Barrier Functions (TISSf-CBF) and Hardware-in-the-Loop Optimization (HITLO) on dedicated FPGA/ASIC silicon, converging control loops to <12.5 ms via Quadratic Programming (QP). A deterministic supervisor continuously monitors a secondary risk metric f_3(x, ẋ, d). Upon exceeding the strict threshold f_3 > 0.05, a step-function penalty (Φ = ∞) triggers immediate rejection of probabilistic AI commands and forces a deterministic safe fallback, ensuring strict compliance with Article VI of the Outer Space Treaty and the Space Liability Convention. 2. Post-Quantum Cryptography (PQC) and Quantum Audit Record (QAR) for Data Sovereignty: For decentralized Hardware Root of Trust (HRoT) nodes, we optimize NIST FIPS 203 ML-KEM-768 over the prime field q = 3329 (Z_q[X]/(X²⁵⁶+1)) using Incomplete NTT, ShiftAdd-Plantard modular reduction with precomputed twiddle factors, and a unified Cooley-Tukey Multi-path Delay Commutator (MDC) pipeline, reducing Area-Time Product (ATP) by 73.9%–79.5%. To defeat Side-Channel Attacks (SCA) and model extraction, we integrate Residue Number System (RNS) BRAM LUT mapping, compact Fisher-Yates hardware shuffling, TRNG-anchored Quantum Audit Records (QAR), and an asymmetric physical-logical gateway (hardware diode) that permits forward tensor inference while physically blocking unauthorized backpropagation and triggering immediate SRAM zeroization upon anomaly detection. 3. Subtractive Room-Temperature Infrastructure vs. Additive CapEx Datacenters: Addressing the Free Cash Flow (FCF) dead cross and privacy erosion of centralized multi-gigawatt AI datacenters, we propose an off-grid, room-temperature (300 K) edge AI architecture. By combining bulk-insulating topological insulator (TI) Spin-Orbit Torque (SOT) MRAM (θSH ∈ [1.0, 18.6], switching current density J_c ~ 10^5 A/cm^2 at 300 K) with organic microcavity Room-Temperature Quantum Batteries exhibiting Dicke superabsorption (O(1/√N) femtosecond charging) and triplet-state metastabilisation, edge nodes achieve cooling-free, self-sustaining operation. 4. Legal and Practical Intellectual Property (IP) Defense Framework: To prevent asymmetric IP expropriation during Request for Proposals (RFP) disclosures and technical evaluations, we codify a defense-in-depth legal strategy integrating explicit Prior Inventions (Background IP) carving, Reservation of Rights against implied licenses under TRIPS and patent law, equitable Breach of Confidence remedies, zero-knowledge trade secret black-boxing, and HDL/Verilog cryptographic watermark traps to defeat false Clean Room Development defenses during legal discovery. 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Yoko Hasebe (2026) studied this question.
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