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New GNN framework optimizes quantum circuit scheduling for multi-QPU systems

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new framework for scheduling quantum circuits on multi-QPU systems, aiming to maximize execution fidelity. This system utilizes a Graph Neural Network (GNN) to estimate the expected fidelity of a circuit on different QPUs before compilation. A scheduler then uses these estimates to balance fidelity and parallelism, offering a more resource-efficient approach than brute-force methods. AI

IMPACT This research could improve the efficiency and reliability of quantum computing by optimizing circuit execution on complex multi-QPU systems.

RANK_REASON Academic paper detailing a new method for quantum computing. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New GNN framework optimizes quantum circuit scheduling for multi-QPU systems

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Academic paper detailing a new method for quantum computing. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Innocenzo Fulginiti, Antonio Tudisco, Salvatore Zammuto, Patrick Hopf, Deborah Volpe, Helmut Seidl, Giovanna Turvani, Robert Wille, Christian B. Mendl, Martin Schulz ·

    Fidelity-Aware Scheduling of Quantum Circuits on Multi-QPU Systems

    arXiv:2609.09980v1 Announce Type: cross 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 …

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