Year: 2025
Type: article
Abstract: Quantum-classical computing pipelines -- systems integrating quantum hardware for specific computational subroutines within larger classical workflows -- require system-level optimisation across the full stack: quantum circuit compilation (QCDE), error mitigation (QEMD), resource scheduling (QHRO), classical co-processing (RSHPC), and workflow orchestration (CRBWA). Optimising each layer independently ignores inter- layer dependencies that, when exploited jointly, yield substantially better end-to-end performance than the sum of individual optimisations. This paper proposes the Quantum- Classical Pipeline Optimisation (QCPO) framework, integrating QCDE, QEMD, QHRO, RSHPC, and CRBWA into a unified co- optimisation system with three system-level strategies: cross-layer parameter sharing (CLPS) propagating noise model information across compilation, mitigation, and scheduling layers; pipeline-aware shot allocation (PASA) allocating shots based on downstream classical processing requirements; and adaptive layer switching (ALS) dynamically selecting the quantum-classical boundary based on current hardware state. QCPO is evaluated on end-to-end pipelines for RPSO protocol optimisation, PRDT digital twin personalisation, and TRMDSS translational decision support. QCPO reduces total pipeline cost by 58.4% and end-to-end latency by 48.4% vs. independently-optimised layers on identical hardware.
Source: Quantum Frontiers Journal
Authors: Bianchi, Erik, Jensen, Marco
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
Funder: Austrian Science Fund
OpenAlex ID: W7220111975