QCORE: A Quantum-Control-Oriented Real-Time Execution Architecture with Extensible Closed-Loop Services and Shared AI Acceleration

2026-08-07

AI Summary

Scalable quantum processors require coordinated implementation of control, readout, feedback, calibration, and error correction under stringent latency and shared-resource constraints, yet existing systems typically optimize only subsets of these functions. This work proposes QCORE, an architecture situated between the host and analog front-end that partitions tasks into four hardware domains and enables closed-loop operation through fast result bypassing, a measurement packet interface, and a service-oriented control backbone. QCORE uniquely integrates closed-loop feedback, traceable measurement interfaces, and tile-local quantum error correction (QEC), ensuring hard real-time performance while supporting secure calibration and persistent state updates. Experiments demonstrate that under 0.8 background load, the shared feedback path achieves a P99 latency of (1.984 ± 0.004)L_max; closed-loop operation reduces frequency error by 83.2% ± 0.8% and decreases state assignment error under readout drift from 10.39% ± 0.54% to 5.37% ± 0.29%; furthermore, 100,000 transactions exhibit no version mixing, and tile-local QEC yields a 2.08× capacity-normalized scaling gain.

Abstract

Scalable quantum processors require control, readout, feedback, calibration, and error correction to coexist under bounded latency and shared-resource constraints, whereas existing platforms typically optimize only a subset of these capabilities. This article presents QCORE (Quantum-Control-Oriented Real-Time Execution), a QPU-side digital control reference architecture positioned between the Host and a platform-specific analog/mixed-signal front end. QCORE separates task management, shared resources, hard-real-time execution, and long-timescale services into four hardware partitions. A fast-result sideband closes same-round feedback, a Measurement Packet provides a traceable measurement and service interface, and a common service-control skeleton, Tile-local QEC, and versioned safe-point commit organize calibration, error correction, and long-term state updates. Transaction-level, event-driven, and quantum-behavioral models are used for evaluation. At a background load of 0.8, the $P_{99}$ latency of the shared Measurement Packet/Event feedback path is $(1.984\pm0.004)L_{\max}$. Closed-loop operation reduces the mean frequency error by $83.2\%\pm0.8\%$ and lowers the state-assignment error at maximum readout drift from $10.39\%\pm0.54\%$ to $5.37\%\pm0.29\%$. No unsafe acceptance or mixed-version observation is observed in 100,000 configuration transactions, and Tile-local QEC reduces modeled global-boundary demand and yields a $2.08\times$ capacity-normalized scaling estimate.

Problem

• quantum control
• real-time execution
• closed-loop feedback
• error correction
• shared-resource constraints

Innovation

• quantum control architecture
• real-time execution
• closed-loop feedback
• shared AI acceleration
• tile-local QEC