Economic Debugging Report: Transition Strategy from Thermal Hegemony to Decentralized Quantum Sovereignty via Tensor G5 and AEGIS-G (経済的デバッグ報告書:熱的覇権から分散型量子主権への移行戦略 — Tensor G5とAEGIS-Gによる物理層の価値再定義)

This monograph presents an architectural, thermodynamic, and economic debugging of the contemporary artificial intelligence hardware paradigm, charting a strategic transition from centralized "Thermal Hegemony" to decentralized "Room-Temperature Quantum (RT-Quantum) Sovereignty." We analyze the approximately 450-fold unit valuation disparity between legacy centralized data center accelerators (e.g., NVIDIA H100/B200 priced at ~$20,000–$40,000 / 3.2M JPY with an estimated BOM of ~$3,320 and 700W–1000W TDP) and vertically integrated edge-inference silicon (Google Tensor G5 fabricated on TSMC 3nm N3E at an estimated unit silicon cost of ~$40–$60 / 7,000 JPY operating fanless under 5W). We demonstrate that the current 15GW data center power footprint represents a thermodynamic dead-end and a rent-seeking tax built on artificial CoWoS/HBM bottlenecks and perpetual cloud OpEx lock-in. To dismantle this centralized cognitive extraction model, we formalize the deployment architecture of AEGIS-G, a decentralized cognitive firewall OS executing deterministic local inference over the RTO P2.0 and QFS-zkVM framework (defined over the 64-bit Goldilocks prime field $\mathbb{F}_p, p = 2^{64}-2^{32}+1$) with Human-in-Command (HIC) cryptographic interlocks. Aligning with Chilean constitutional Neurorights precedents, UK Information Commissioner's Office (ICO) neurodata guidance, and the UK Data Use and Access Act 2025 (Article 22 human-in-the-loop safeguards), we formulate a concrete public-sector procurement mandate for the United Kingdom in coordination with the AI Safety Institute (AISI): freezing £500M in centralized GPU cluster expenditures and redirecting capital toward a National Cognitive Defense Infrastructure powered by on-device edge sovereignty.