Workshops Archive

Scaling Hybrid Quantum--HPC Applications with the Quantum Framework

Workshop: The 1st International Workshop for Software Frameworks and Workload Management on Quantum-HPC Ecosystems

Authors: Srikar Chundury (North Carolina State University); Amir Shehata, Seongmin Kim, and Muralikrishnan Gopalakrishnan Meena (Oak Ridge National Laboratory (ORNL)); Chao Lu (Oak Ridge National Laboratory); Kalyan Gottiparthi (Oak Ridge National Laboratory (ORNL)); Eduardo Antonio Coello Perez (Oak Ridge National Laboratory); Frank Mueller (North Carolina State University); and In-Saeng Suh (Oak Ridge National Laboratory (ORNL))

Abstract: Hybrid quantum–high performance computing (Q-HPC) workflows are emerging as a key strategy for running quantum applications at scale on noisy intermediate-scale quantum (NISQ) devices. These workflows must operate seamlessly across diverse simulators and hardware backends since no single simulator offers the best performance for every circuit type. Efficiency depends strongly on circuit structure, entanglement, and depth, making backend-agnostic execution essential for fair benchmarking, platform selection, and the identification of quantum advantage opportunities. We extend the Quantum Framework (QFw), a modular HPC-aware orchestration layer, to integrate local simulators (Qiskit Aer, NWQ-Sim, QTensor, TN-QVM) and a cloud backend (IonQ) under a unified interface. Benchmarking variational and non-variational workloads reveal workload-specific strengths: Qiskit Aer’s matrix product state excels for large Ising models, NWQ-Sim leads on entanglement and Hamiltonian simulation, and distributed NWQ-Sim accelerates optimization tasks. These findings demonstrate that simulator-agnostic, HPC-aware orchestration enables scalable, reproducible Q-HPC ecosystems, advancing quantum advantage.

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