학술논문
Superstaq: Deep Optimization of Quantum Programs
Document Type
Conference
Author
Campbell, Colin; Chong, Frederic T.; Dahl, Denny; Frederick, Paige; Goiporia, Palash; Gokhale, Pranav; Hall, Benjamin; Issa, Salahedeen; Jones, Eric; Lee, Stephanie; Litteken, Andrew; Omole, Victory; Owusu-Antwi, David; Perlin, Michael A.; Rines, Rich; Smith, Kaitlin N.; Goss, Noah; Hashim, Akel; Naik, Ravi; Younis, Ed; Lobser, Daniel; Yale, Christopher G.; Huang, Benchen; Liu, Ji
Source
2023 IEEE International Conference on Quantum Computing and Engineering (QCE) QCE Quantum Computing and Engineering (QCE), 2023 IEEE International Conference on. 01:1020-1032 Sep, 2023
Subject
Language
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.