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

• URL: http://arxiv.org/abs/2511.10479v1
• Date: Fri, 14 Nov 2025 01:53:44 GMT
• Title: Quantum Design Automation: Foundations, Challenges, and the Road Ahead
• Authors: Feng Wu, Jingzhe Guo, Tian Xia, Linghang Kong, Fang Zhang, Ziang Wang, Aochu Dai, Ziyuan Wang, Zhaohui Yang, Hao Deng, Kai Zhang, Zhengfeng Ji, Yuan Feng, Hui-Hai Zhao, Jianxin Chen,
• Abstract summary: We advocate for a holistic design perspective in quantum computing.<n>We detail how interconnected computational methods and tools collaborate to enable end-to-end quantum computer design.
• Score: 39.223805375181776
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

Related papers

• Investigating Quantum Circuit Designs Using Neuro-Evolution [2.9631016562930537]
  We propose an evolutionary approach to the automated design and training of quantum circuits.<n>The proposed method searches over gate types, qubit connectivity, parameterization, and circuit depth while respecting hardware and noise constraints.<n>Preliminary results demonstrate that circuits evolved on classification tasks are able to achieve over 90% accuracy.
  arXiv  Detail & Related papers  (2026-02-03T18:57:39Z)
• Quantum-enhanced Computer Vision: Going Beyond Classical Algorithms [50.573955644831386]
  Quantum-enhanced Computer Vision (QeCV) is a new research field at the intersection of computer vision, machine learning and quantum computing.<n>It has high potential to transform how visual signals are processed and interpreted with the help of quantum computing.<n>This survey contributes to the existing literature on QeCV with a holistic review of this research field.
  arXiv  Detail & Related papers  (2025-10-08T17:59:51Z)
• Artificial intelligence for representing and characterizing quantum systems [49.29080693498154]
  Efficient characterization of large-scale quantum systems is a central challenge in quantum science.<n>Recent advances in artificial intelligence (AI) have emerged as a powerful tool to address this challenge.<n>This review discusses how each of these AI paradigms contributes to two core tasks in quantum systems characterization.
  arXiv  Detail & Related papers  (2025-09-05T08:41:24Z)
• Digital quantum simulation of many-body systems: Making the most of intermediate-scale, noisy quantum computers [51.56484100374058]
  This thesis is centered around simulating quantum dynamics on quantum devices.<n>We present an overview of the most relevant quantum algorithms for quantum dynamics.<n>We identify relevant problems within quantum dynamics that could benefit from quantum simulation in the near future.
  arXiv  Detail & Related papers  (2025-08-29T10:37:19Z)
• Benchmarking fault-tolerant quantum computing hardware via QLOPS [2.0464713282534848]
  To run quantum algorithms, it is essential to develop scalable quantum hardware with low noise levels.<n>Various fault-tolerant quantum computing schemes have been developed for different hardware platforms.<n>We propose Quantum Logical Operations Per Second (QLOPS) as a metric for assessing the performance of FTQC schemes.
  arXiv  Detail & Related papers  (2025-07-16T08:31:51Z)
• Modeling Quantum Links for the Exploration of Distributed Quantum Computing Systems [3.0135120410768796]
  We review protocols and models for estimating latency, losses, and fidelity in quantum communication primitives relying on quantum state distribution via microwave photons.<n>We also propose a scalable simulation framework to support the design and evaluation of future distributed quantum computing systems.
  arXiv  Detail & Related papers  (2025-05-13T13:53:44Z)
• How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits [3.970891204847277]
  Small-scale demonstrations have become possible for quantum algorithmic primitives on hundreds of physical qubits.<n>We show how the road to scaling could be paved by adopting existing semiconductor technology to build much higher-quality qubits.<n>We argue that, to tackle industry-scale classical optimization and machine learning problems, heterogeneous quantum-probabilistic computing with custom-designed accelerators should be considered.
  arXiv  Detail & Related papers  (2024-11-15T18:22:46Z)
• QCircuitBench: A Large-Scale Dataset for Benchmarking Quantum Algorithm Design [63.02824918725805]
  Quantum computing is recognized for the significant speedup it offers over classical computing through quantum algorithms.<n>QCircuitBench is the first benchmark dataset designed to evaluate AI's capability in designing and implementing quantum algorithms.
  arXiv  Detail & Related papers  (2024-10-10T14:24:30Z)
• Quantum Circuit Synthesis and Compilation Optimization: Overview and Prospects [59.07692103357675]
  This survey explores the feasibility of an integrated design and optimization scheme that spans from the algorithmic level to quantum hardware.<n>It becomes more possible to reduce manual design costs, enhance the precision and efficiency of execution, and facilitate the implementation and validation of the superiority of quantum algorithms on hardware.
  arXiv  Detail & Related papers  (2024-06-30T15:50:10Z)
• Quantum algorithms: A survey of applications and end-to-end complexities [88.57261102552016]
  The anticipated applications of quantum computers span across science and industry.<n>We present a survey of several potential application areas of quantum algorithms.<n>We outline the challenges and opportunities in each area in an "end-to-end" fashion.
  arXiv  Detail & Related papers  (2023-10-04T17:53:55Z)
• Software tools for quantum control: Improving quantum computer performance through noise and error suppression [3.6508609114589317]
  We introduce software tools for the application and integration of quantum control in quantum computing research. We provide an overview of a set of python-based classical software tools for creating and deploying optimized quantum control solutions. We describe a software architecture leveraging both high-performance distributed cloud computation and local custom integration into hardware systems.
  arXiv  Detail & Related papers  (2020-01-13T04:34:06Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.