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Fault-Tolerant Quantum Computer Architecture: Towards Scalable, AI-Assisted, and Energy-Aware Error Correction Frameworks

Harsh Singh

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.13140/rg.2.2.15039.06561

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Abstract: Autonomous cyber-physical networks increasingly combine distributed sensing, edge intelligence, networked control, and safety-critical actuation, yet their reliability is constrained by correlated cyber faults, communication loss, model drift, hardware degradation, and the fragility of emerging quantum resources. This paper develops a fault-tolerant distributed quantum-intelligence architecture that couples photonic circuit emulation, quantum error-aware computation, AI-augmented control, distributed consensus, and deterministic safety fallback. The purpose is to formalize how heterogeneous quantum, photonic, AI, and control subsystems can jointly preserve mission-level stability when individual components fail or become uncertain. The study adopts a model-based systems methodology, synthesizes the supplied literature on fault-tolerant photonic quantum computing, distributed autonomous control, cyber-physical resilience, AI-native edge systems, and quantum-assisted optimization, and formulates a multi-layer state-space and reliability model. A composite Fault-Tolerant Quantum Intelligence Resilience Index (FTQIRI) integrates quantum reliability, photonic emulation fidelity, AI robustness, network resilience, closed-loop stability, and cyber assurance. An illustrative 0–10 numerical model yields an integrated score of 8.49 for the proposed architecture versus 6.34 for a conventional hybrid baseline, indicating the expected value of cross-layer redundancy and adaptive orchestration rather than empirical superiority. The paper further specifies an invention-oriented architecture, independent system and method claim drafts, and dependent claim concepts around digital-twin emulation, syndrome-informed control, consensus-based failover, cryptographic verification, and safety envelopes. The principal contribution is a unified mathematical and engineering framework that treats quantum fault tolerance and cyber-physical fault tolerance as coupled control problems, thereby connecting photonic quantum hardware, distributed intelligence, and autonomous network safety within one verifiable decision loop. Keywords: fault-tolerant quantum computing; distributed quantum intelligence; photonic circuit emulation; autonomous cyber-physical systems; AI-augmented control; quantum error correction; resilient edge intelligence; distributed consensus; safe reinforcement learning; digital twin; quantum–classical co-design; cyber resilience; multi-agent control; reliability optimization; verifiable AI
Fault-tolerant quantum computation (FTQC) critically depends on real-time classical decoding, which is rapidly emerging as a system bottleneck. As quantum systems scale, decoding latency and throughput limitations lead to exponential syndrome backlogs and logical operation stalls. While hardware accelerators and parallel windowing offer pathways to speed up decoding, dynamically deploying a finite pool of decoders across a vast quantum error correction architecture remains an unresolved resource allocation problem. To address this, we formulate FTQC decoding as a constrained dynamic scheduling problem by utilizing a spatio-temporal framework based on slices. We propose Triage, a dual-mode architecture that mitigates operation stalls by adaptively combining a cost-efficient heuristic scheduler with a priority-aware emergency mode to rapidly resolve the causal cone of critical operations. Our evaluation shows that Triage maintains low algorithm stalls and logical error rates even under scarce classical resource constraints. Across various benchmarks, Triage achieves an average logical error rate reduction of 52.6% compared to standard temporal parallelism, enabling an efficient classical control plane for scalable FTQC architectures.