Quantum Hardware Roofline: Evaluating the Impact of Gate Expressivity on Quantum Processor Design

• URL: http://arxiv.org/abs/2403.00132v1
• Date: Thu, 29 Feb 2024 21:28:18 GMT
• Title: Quantum Hardware Roofline: Evaluating the Impact of Gate Expressivity on Quantum Processor Design
• Authors: Justin Kalloor, Mathias Weiden, Ed Younis, John Kubiatowicz, Bert De Jong, Costin Iancu
• Abstract summary: This paper explores hardware design trade-offs across NISQ systems to guide algorithm and hardware design choices. The evaluation is driven by algorithmic workloads and algorithm fidelity models. By providing a method to evaluate the suitability of algorithms for hardware platforms, this work emphasizes the importance of hardware-software co-design for quantum computing.
• Score: 0.8341988468339112
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The design space of current quantum computers is expansive with no obvious winning solution. This leaves practitioners with a clear question: "What is the optimal system configuration to run an algorithm?". This paper explores hardware design trade-offs across NISQ systems to guide algorithm and hardware design choices. The evaluation is driven by algorithmic workloads and algorithm fidelity models which capture architectural features such as gate expressivity, fidelity, and crosstalk. We also argue that the criteria for gate design and selection should be extended from maximizing average fidelity to a more comprehensive approach that takes into account the gate expressivity with respect to algorithmic structures. We consider native entangling gates (CNOT, ECR, CZ, ZZ, XX, Sycamore, $\sqrt{\text{iSWAP}}$), proposed gates (B Gate, $\sqrt[4]{\text{CNOT}}$, $\sqrt[8]{\text{CNOT}}$), as well as parameterized gates (FSim, XY). Our methodology is driven by a custom synthesis driven circuit compilation workflow, which is able to produce minimal circuit representations for a given system configuration. By providing a method to evaluate the suitability of algorithms for hardware platforms, this work emphasizes the importance of hardware-software co-design for quantum computing.

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