Superstaq: Deep Optimization of Quantum Programs

التفاصيل البيبلوغرافية
العنوان: Superstaq: Deep Optimization of Quantum Programs
المؤلفون: 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
سنة النشر: 2023
المجموعة: Quantum Physics
مصطلحات موضوعية: Quantum Physics
الوصف: 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.
Comment: Appearing in IEEE QCE 2023 (Quantum Week) conference
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2309.05157
رقم الانضمام: edsarx.2309.05157
قاعدة البيانات: arXiv