Superstaq: Deep Optimization of Quantum Programs

• URL: http://arxiv.org/abs/2309.05157v1
• Date: Sun, 10 Sep 2023 22:14:38 GMT
• Title: Superstaq: Deep Optimization of Quantum Programs
• Authors: Colin Campbell, Frederic T. Chong, Denny Dahl, Paige Frederick, Palash Goiporia, Pranav Gokhale, Benjamin Hall, Salahedeen Issa, Eric Jones, Stephanie Lee, Andrew Litteken, Victory Omole, David Owusu-Antwi, Michael A. Perlin, Rich Rines, Kaitlin N. Smith, Noah Goss, Akel Hashim, Ravi Naik, Ed Younis, Daniel Lobser, Christopher G. Yale, Benchen Huang, Ji Liu
• Abstract summary: We describe Superstaq, a quantum software platform that optimize the execution of quantum programs by tailoring to underlying hardware primitives. For benchmarks such as the Bernstein-Vazirani algorithm and the Qubit Coupled Cluster chemistry method, we find that deep optimization can improve program execution performance by at least 10x compared to prevailing state-of-the-art compilers.
• Score: 7.48254648693787
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: We describe Superstaq, a quantum software platform that optimizes the execution of quantum programs by tailoring to underlying hardware primitives. For benchmarks such as the Bernstein-Vazirani algorithm and the Qubit Coupled Cluster chemistry method, we find that deep optimization can improve program execution performance by at least 10x compared to prevailing state-of-the-art compilers. To highlight the versatility of our approach, we present results from several hardware platforms: superconducting qubits (AQT @ LBNL, IBM Quantum, Rigetti), trapped ions (QSCOUT), and neutral atoms (Infleqtion). Across all platforms, we demonstrate new levels of performance and new capabilities that are enabled by deeper integration between quantum programs and the device physics of hardware.

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