Title:Distributed Bedside Tomographic Reconstruction via Google Android Edge-Tensor Arrays: Carbon Nanotube (CNT) Cold-Cathode X-Ray Sources and Deterministic QFS-zkVM Verification

This monograph establishes a deterministic physical-layer and cryptographic architecture for distributed bedside tomographic image reconstruction utilizing Google Android Edge-Tensor Arrays coupled with stationary Carbon Nanotube (CNT) cold-cathode X-ray emitter arrays. Conventional hospital-grade Computed Tomography (CT) relies on mechanically rotating high-inertia gantries, thermionic X-ray tubes, and centralized cloud/server clusters—introducing severe mechanical vulnerability, high thermal dissipation, and clinical latency in acute bedside or point-of-care diagnostics. To resolve these constraints, we formulate an ultra-low-latency, decentralized iterative reconstruction pipeline executed across interconnected Google Android Edge-Tensor TPUs. By synchronizing electronically switched multi-pixel CNT cold-cathode emission matrices with localized tensor processing, the system eliminates mechanical gantry rotation while minimizing radiation dose via sparse-view compressed sensing. Crucially, to prevent algorithmic hallucination, adversarial perturbation, and unauthorized data extraction during clinical image synthesis, every forward-projection and back-projection tensor operator is arithmetized within the Quantum-Safe Financial & Infrastructure Zero-Knowledge Virtual Machine (QFS-zkVM) over the 64-bit Goldilocks prime field ($\mathbb{F}_p, p = 2^{64} - 2^{32} + 1$). Under the Human-in-Command (HIC) governance standard and Real-Time Operations Protocol (RTO P2.0), each reconstructed volumetric slice and diagnostic telemetry packet is cryptographically notarized prior to clinical display, guaranteeing mathematical verifiability, radiation safety interlock compliance, and zero-trust sovereignty at the clinical edge. 論文要旨(日本語) 本論文は、カーボンナノチューブ(CNT)冷陰極X線源アレイとGoogle Android Edge-Tensor Arrays(エッジTPU群)を結合した、分散型ベッドサイド断層画像(CT)再構成の決定論的物理層および暗号検証アーキテクチャを確立するものである。従来の大型回転ガントリーや熱陰極管、中央集権型クラウド処理に依存するCTシステムが抱える機械的制約・熱損失・通信遅延を排除し、電子制御によるCNT冷陰極マルチビーム照射とAndroidエッジテンソル演算による超低遅延の分散反復再構成を実現する。さらに、医療画像生成におけるAIのハルシネーション(幻覚)やデータ改ざん、無断学習・知財搾取を完全に阻止するため、すべての投影・逆投影テンソル演算を64ビットGoldilocks素体($\mathbb{F}_p, p = 2^{64} - 2^{32} + 1$)上のQFS-zkVM(ゼロ知識仮想マシン)内で算術化・証明する。Human-in-Command(HIC)統治原則およびRTO P2.0プロトコルのもと、ベッドサイドにおける放射線安全インターロックの厳格な担保と医療データの完全な主権保護を同時に達成する。