Quantum Design Automation: Foundations, Challenges, and the Road Ahead

TL;DR

This paper advocates for a holistic, end-to-end design approach in quantum computing, emphasizing integrated co-design of hardware and software to address scalability, performance, and fabrication challenges.

Contribution

It provides a comprehensive overview of interconnected design methods and tools for quantum computer development, highlighting co-optimization strategies and concrete examples.

Findings

Integrated design workflows facilitate quantum hardware-software co-optimization

Concrete examples demonstrate improvements in quantum instruction set and error correction

End-to-end design approaches can accelerate quantum hardware deployment

Abstract

Quantum computing is transitioning from laboratory research to industrial deployment, yet significant challenges persist: system scalability and performance, fabrication yields, and the advancement of algorithms and applications. We emphasize that in building quantum computers -- spanning quantum chips, system integration, instruction sets, algorithms, and middleware such as quantum error correction schemes -- design is everywhere. In this paper, we advocate for a holistic design perspective in quantum computing, a perspective we argue is pivotal to unlocking innovative co-design opportunities and addressing the aforementioned key challenges. To equip readers with sufficient background for exploring co-optimization opportunities, we detail how interconnected computational methods and tools collaborate to enable end-to-end quantum computer design. This coverage encompasses critical stages -- such as chip layout design automation, high-fidelity system-level simulation, Hamiltonian derivation for quantum system modeling, control pulse simulation, decoherence analysis, and physical verification and testing -- followed by quantum instruction set design. We then proceed to quantum system and software development, including quantum circuit synthesis, quantum error correction and fault tolerance, and logic verification and testing. Through these discussions, we illustrate with concrete examples -- including co-optimizing quantum instruction sets with algorithmic considerations, customizing error correction circuits to hardware-specific constraints, and streamlining quantum chip design through tailored code design, among others. We hope that the detailed end-to-end design workflow as well as these examples will foster dialogue between the hardware and software communities, ultimately facilitating the translation of meaningful research findings into future quantum hardware implementations.