Presentation
QFw: A Quantum Framework for Large-Scale HPC Ecosystems
DescriptionThis work extends Quantum Framework (QFw) by integrating it with Northwest Quantum Simulator (NWQ-Sim) and by introducing a lightweight python library (qfw\_backend) that allows multiple frontends (e.g., Qiskit) to interact with QFw. This extension enables QFw to flexibly decouple frontends from backends (e.g., NWQ-Sim). We demonstrate this capability by executing a Greenberger-Horne-Zeilinger (GHZ) circuit using Qiskit and Pennylane with different backends. Also, QFw enables easy scaling to multiple nodes. We showcase this by running GHZ scaling tests up to 32 qubits for different numbers of nodes on Frontier. To demonstrate the use of QFw for real-world problems, we solve a metamaterial optimization problem which uses a Quantum Approximate Optimization Algorithm (QAOA). We observe that QFw over NWQ-Sim marginally improves Qiskit-aer's accuracy. These additions prepare QFw to run hybrid applications in a hybrid resource environment since it treats actual quantum hardware and simulators alike.
