Fidelity-Aware Scheduling of Quantum Circuits on Multi-QPU Systems
Abstract
High Performance Computing-Quantum Computing (HPCQC) platforms expose multiple Quantum Processing Units (QPUs) that may differ in size, topology, native gates, and noise characteristics. For current noisy devices, errors compound along the compiled circuits quickly, and minimizing them, that is, maximizing the circuits' execution fidelity, is essential for reliable results. Fidelity depends on the compilation to a specific target device: the same high-level circuit may produce different executables and, therefore, different expected fidelities across QPUs. We present a low-overhead fidelity-aware scheduling framework for multi-QPU systems based on a Graph Neural Network (GNN) that estimates, before compilation, the expected fidelity of each circuit on each available QPU. Then, a tunable scheduler uses these estimates to control the trade-off between execution fidelity and parallelism. Results show that this framework allows for approximating an exhaustive fidelity-based assignment, saving computational resources compared to a brute-force approach that compiles each circuit on every device.
Related
- Online Scheduling and Distribution of Quantum Circuits over Quantum Networks
- ReFINE: Scheduling of Distillation and Coding for Rate-Fidelity Tradeoff in Quantum Networks
- Efficient Fidelity Estimation of General Quantum Resource States via Clifford Circuits
- Priority-Aware Routing for Quantum Networks:Integrating Coherence-Time Constraints into Scheduling
- Branch-Aware Quantum Constant Propagation for Dynamic Quantum Circuits
BibTeX
@misc{fulginiti2026fidelityaware,
title = {{Fidelity-Aware Scheduling of Quantum Circuits on Multi-QPU Systems}},
author = {Innocenzo Fulginiti and Antonio Tudisco and Salvatore Zammuto and Patrick Hopf and Deborah Volpe and Helmut Seidl and Giovanna Turvani and Robert Wille and Christian B. Mendl and Martin Schulz},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.09980},
eprint = {2609.09980},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.09980},
}
RIS
TY - UNPB
TI - Fidelity-Aware Scheduling of Quantum Circuits on Multi-QPU Systems
AU - Innocenzo Fulginiti
AU - Antonio Tudisco
AU - Salvatore Zammuto
AU - Patrick Hopf
AU - Deborah Volpe
AU - Helmut Seidl
AU - Giovanna Turvani
AU - Robert Wille
AU - Christian B. Mendl
AU - Martin Schulz
PY - 2026
DA - 2026/09/15
PB - arXiv
DO - 10.48550/arxiv.2609.09980
UR - https://arxiv.org/abs/2609.09980
AB - High Performance Computing-Quantum Computing (HPCQC) platforms expose multiple Quantum Processing Units (QPUs) that may differ in size, topology, native gates, and noise characteristics. For current noisy devices, errors compound along the compiled circuits quickly, and minimizing them, that is, maximizing the circuits' execution fidelity, is essential for reliable results. Fidelity depends on the compilation to a specific target device: the same high-level circuit may produce different executables and, therefore, different expected fidelities across QPUs. We present a low-overhead fidelity-aware scheduling framework for multi-QPU systems based on a Graph Neural Network (GNN) that estimates, before compilation, the expected fidelity of each circuit on each available QPU. Then, a tunable scheduler uses these estimates to control the trade-off between execution fidelity and parallelism. Results show that this framework allows for approximating an exhaustive fidelity-based assignment, saving computational resources compared to a brute-force approach that compiles each circuit on every device.
ER -