Deterministic Safety Standardization for Next-Generation Physical AI and Orbital Infrastructure: Sub-0.5ms Control Barrier Function Quadratic Programming (CBF-QP), FIPS 203 ML-KEM-768 Quantum Audit Records (QAR), and Systemic Risk Mitigation Protocol

Contemporary general-purpose artificial intelligence (AGI) development led by frontier technology conglomerates remains overwhelmingly anchored in stochastic, autoregressive, and diffusion-based probabilistic inference. When deployed directly into safety-critical cyber-physical infrastructure and Low Earth Orbit (LEO) autonomous constellations, the absence of a deterministic physical-layer safety guarantee induces two existential failure modes: Temporal Blind Spots caused by communication and operating-system jitter, and Algorithmic Flash Crashes (coupled multi-agent physical runaway). This monograph establishes the foundational mathematical, cryptographic, actuarial, and statutory architecture of the Next-Generation Physical AI and Space Infrastructure Safety Standardization Consortium. First, we formulate a bare-metal Control Barrier Function Quadratic Programming (CBF-QP) deterministic supervisor executed within a sub-0.5 ms Hard-In-The-Loop Optimization (HITLO) fabric via PHOENIX_BRIDGE optical interconnects, mathematically intercepting 100% of stochastic AI hallucinations prior to physical actuation. Second, we integrate ultra-low-latency post-quantum cryptography (NIST FIPS 203 ML-KEM-768 accelerated via 7-stage Incomplete Number Theoretic Transforms) with immutable Quantum Audit Records (QAR) verified in a zero-knowledge virtual machine (QFS-zkVM) over the 64-bit Goldilocks prime field F_p (p = 2^64 - 2^32 + 1). Third, we demonstrate how this architecture resolves critical bottlenecks across three strategic sectors: (1) eliminating mega-constellation collision cascades and discharging strict state liability under Article VII of the 1967 Outer Space Treaty for Defense and Aerospace Agencies (DoD, NASA) via the Autonomous Traffic Control System (ATCS); (2) bounding heavy-tailed AI catastrophe distributions via the Systemic Risk Mitigation Protocol (SRMP) to restore finite expected loss (E[L] < infinity) for Mega-Insurance, Reinsurance, and Catastrophe (CAT) Bond Markets; and (3) transcending the trade-off between overly conservative rule-based models (Mobileye RSS) and fragile end-to-end Deep Learning (Sim-to-Real gap) in Next-Generation Mobility and Robotics. Finally, we specify a two-phase global standardization roadmap coupling Q-SAFA decentralized bailout smart contracts with SEC Rule 15c3-5 pre-trade-style hardware interlocks and Delaware Caremark fiduciary oversight standards to establish the global mandatory "License to Operate" for autonomous cyber-physical infrastructure. License & Integrity Covenant: Creative Commons Attribution 4.0 International (CC BY 4.0) with Strict No-Learn Covenant (NLL-v1.0-2026). Author: Hasebe, Yoko (長谷部 洋子) — Lead Researcher, Autonomous Infrastructure Systems, Autonomous Living & Physical Infrastructure Institute, Iwakuni, Yamaguchi, Japan.