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StreamingQEC: Streaming Quantum Error Correction in Tightly Integrated Quantum-Classical Systems via Certified Recurrence

Panayiotis Christou, Shuwen Kan, Hao Wang, Ying Mao 2026-07-16
Design Space Exploration Quant Ph × Agentic Architecture

StreamingQEC addresses the problem of modeling resource contention in hybrid quantum-classical systems during fault-tolerant quantum error correction. The method introduces a system-level simulator with explicit discrete-event simulation, an automatic staged-fluid mode for faster exploration, and a certified recurrence mechanism that compresses repeated scheduling states. Experimental evidence shows recurrence achieves a 24.0x host-side speedup while preserving 59,743,936 decoding events for a 16-job anchor workload, and the staged-fluid mode yields a mean makespan error of 2.60%. This matters because it enables system architects to evaluate resource-limited pipeline stalls and saturation under microsecond-scale QEC cycles, which is critical for designing scalable fault-tolerant quantum computers.

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HybridQC: Hardware-Grounded Simulation of Tightly Integrated Hybrid Quantum-Classical Systems

Panayiotis Christou, Shuwen Kan, Ying Mao 2026-07-16
Quant Ph × Hardware Simulation Communication Scheduling Runtime Workload

HybridQC addresses the problem that hybrid quantum-classical system performance is increasingly limited by classical control and communication, not quantum execution, and that existing tools fail to capture system-topology issues like controller bottlenecks and resource contention. The method introduces a topology-aware discrete-event simulator that models hybrid compute units as configurable graphs of classical and quantum devices, decomposes jobs into typed directed acyclic graphs, and supports interchangeable scheduling policies. Calibrated against live D-Wave and IBM processors, HybridQC achieves mean absolute percentage errors of 3.92%-8.04% for D-Wave QPU access time and 5.26%-19.01% for IBM quantum-seconds, and workload experiments show that balanced 10x HCU scaling improves makespan by only 2.19x-3.42x while scheduling policy changes shift makespan by up to 1.80x. This matters because HybridQC provides a systematic framework to evaluate topology, scheduling, and scaling limits of hybrid architectures before physical deployment, enabling researchers to identify bottlenecks and optimize resource allocation.

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