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Cross-Plane Entanglement Orchestration with Pending Quantum Resources over Wireless Control Channels

Year: 2026
Type: article
Abstract: Quantum-network controllers often treat heralding, swapping outcomes, and other classical coordination messages as effectively instantaneous. This abstraction fails when the control plane is wireless, fading, or capacity-limited: a successful quantum operation can create a physical entangled resource that occupies scarce quantum memory but remains unusable until its classical confirmation is delivered. We formulate this interaction as a coupled quantum--classical stochastic processing system with confirmed and pending entanglement, perishable quantum memories, heterogeneous application utility, and operation-dependent confirmation workloads generated by successful quantum operations. We propose cross-plane potential-shaped goal-oriented online entanglement orchestration (CP-PS-OGOEO), which combines bounded downstream application-value propagation in the quantum plane, downstream-value-per-control-work scheduling of pending confirmations, and a dimensionless excess-load price that feeds wireless congestion back into quantum-resource production. The resulting controller preserves sample-path physical feasibility and exact accounting of pending resources and control work, establishes bounded-potential and quantum-budget properties under virtual-queue stability, and reduces to the underlying quantum-plane scheduler along trajectories when confirmation capacity is unlimited. Across 20 fresh paired seeds, CP-PS-OGOEO improves application utility over value-aware confirmation-only control by 37.6% at 3dB and 31.2% at 5dB under Rayleigh fading. The benefit is not universal: at 5dB, it is 9.0% worse under a light 1:1:1 confirmation workload but 28.8% and 31.7% better under 1:2:2 and 1:3:3 workloads. These results identify the operating regime where cross-plane feedback is valuable: wireless confirmation must be capacity-constrained while quantum operations generate materially significant control workload.
Language: English
Open Access status: green
OpenAlex ID: W7225628256
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