Temporal Foundations, Vol. III: Engineering of Quantum Systems

Andriy Lemeshko, Isamu Ohnishi

Andriy Lemeshko, Isamu Ohnishi

Syed Muntasir Mamun

This seventh volume of the series establishes the first formal post-post-quantum taxonomy—a three-tier ontological and epistemological hierarchy that reclassifies all post-quantum cryptographic schemes according to the fundamental nature and justification of their security. The hierarchy progresses from computational (algorithmic hardness assumptions) through physical (thermodynamic, noise-engineered, and hardware-constrained irreversibility) to device-independent (information-theoretic guarantees independent of device implementation). Building directly upon the anatomical critiques, hybrid primitives (Vol II), QRAM-hardness (Vol III), parameterized adversary models (Vol IV), GKP-resistant countermeasures (Vol V), and NISQ empirical validation (Vol VI), we provide a complete reclassification of NIST PQC standards, hybrid protocols, and the novel primitives introduced across the series. Dedicated Mamun, SM (2026) ……………………………….1 Theoretical and Physical Boundaries of Lattice-Based Post-Quantum Cryptography: An Anatomical Critique of Post-Post-Quantum Taxonomy (Vol-VII) sections dissect the ontology (what security is) and epistemology (how security claims are known and justified) of each tier. K S C The taxonomy reveals that current lattice-based schemes remain anchored in the provisional computational tier, while the countermeasures developed in Vols III–VI elevate them into the physical tier. True device-independent security remains an aspirational frontier. Also available on Academia.edu: https://www.academia.edu/attachments/132771868/download_file?s=portfolio

Peter Sidajaya

Syed Muntasir Mamun

Volume V concludes the KSCCN Anatomical Review series by translating the theoretical foundations (Vol I), computational realizations (Vol II), empirical validations (Vol III), and higher categorical extensions (Vol IV) into concrete deployment pathways for sovereign AI and physics-informed machine learning. We examine three strategic application domains: (1) digital sovereignty architectures that embed local gauge groupoids to enforce data localization and jurisdictional symmetry constraints without sacrificing model performance; (2) quantum-AI interfaces where groupoid-equivariant layers are lifted to equivariant quantum circuits capable of handling partial symmetries in hybrid quantum-classical models; and (3) scientific machine learning pipelines for high-energy physics (lattice gauge theory at scale), climate modeling on stratified and foliated domains, and materials discovery under crystallographic groupoid constraints. We provide deployment blueprints, engineering patterns for JAX/PyTorch + quantum SDK integration, risk mitigation strategies for groupoid misspecification and numerical stability, and a maturity roadmap from prototype to production. The volume closes with reflections on the completed five-volume programme and its contribution to equitable, symmetry-respecting, and sovereignty-aware artificial intelligence. 1. Also available on Academia.edu: https://www.academia.edu/attachments/133131470/download_file?s=portfolio

Arno Böhm