Quantum Artificial Intelligent Computing (QAIC): A Comprehensive Guide And Blueprint
Radhakrishnan Jayaraman · Zenodo (CERN European Organization for Nuclear Research) · 2026
Abstract: This publication presents a complete, self-contained exposition of Quantum Artificial Intelligent Computing (QAIC), a paradigm designed to overcome the limitations of both classical machine learning and gate-model quantum computing by embedding problem-specific constraints directly into physical hardware dynamics. Framed within the ICQER (Informational Constraints as Physical Operational Priors) methodology, the guide outlines a comprehensive blueprint spanning ten core domains: from conceptual foundations and mathematical formalisms to practical materials engineering and ethical governance. The guide details the hybridization of disparate qubit modalities—such as superconducting qubits, spin qubits, trapped ions, and photonic qumodes—to leverage the advantages of long coherence times and fast gate operations within a modular cluster architecture. It presents a novel toolbox of constraint-enforcing gate primitives, including projective gates and penalty Hamiltonians, alongside hybrid variational quantum-AI learning protocols (V-QAIC and RL-QAIC) that utilize real-time adaptive control to navigate constrained Hilbert spaces. Significant emphasis is placed on practical implementation, including the synergistic integration of graphene photonics and room-temperature superconducting (RTSC) materials for low-loss, scalable interconnects, as well as robust, noise-aware error correction strategies. This work concludes with a strategic, multi-phase implementation roadmap for building small-scale prototypes (100-1000 qumodes/qubits) and scaling toward application-class QAIC clusters. High-value use-cases, including accelerated materials discovery for RTSCs and complex combinatorial logistics, are benchmarked against classical and quantum competitors. Serving as the canonical reference for the Qindra Core initiative, this guide provides researchers, engineers, and policymakers with the necessary theoretical grounding, circuit schematics, fabrication recipes, and safety protocols to advance QAIC from theoretical promise to practical, fault-tolerant reality.