CAREER: FET: A Top-down Compilation Infrastructure for Optimization and Debugging in the Noisy Intermediate Scale Quantum (NISQ) era

职业：FET：用于噪声中级量子 (NISQ) 时代优化和调试的自上而下的编译基础设施

• 批准号: 2421059
• 负责人: Yufei Ding
• 金额: $ 49.95万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-02-15 至 2025-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2421059&HistoricalAwards=false
• 关键词: CAREER; FET; Top; down; Compilation

This project sets a comprehensive research agenda focusing on the construction of a top-down compilation infrastructure for quantum computing. It will develop theoretical and practical methodologies for enabling high-level algorithmic optimization, low-level pulse optimizations, as well as whole-system debugging and analysis. The compilation stack would facilitate automatic resource-efficient quantum algorithm designs and high-fidelity program executions on near-term quantum devices. It will benefit major quantum computing applications such as quantum chemistry and combinatorial optimization and contribute to the leadership of the United States in quantum information science and technology. The research findings will be widely disseminated through open-source software packages, publications in premier conferences and journals, tutorials at teaching workshops, as well as specialized K-12 programs for exposing the young generation to the frontiers of quantum information research.The project will integrate methods from the classical computing fields such as code generation and optimization, programming language design and implementation, and compilation techniques, to address the unique research challenges in quantum programming, optimization, and debugging. Specific targets include 1) A language and an autotuning compiler to automate resource-efficient algorithm development in the quantum computing domain; 2) A pulse-level compilation infrastructure to exploit the abundant freedom in pulse variation and scheduling towards more effective optimization and error mitigation; 3) Advanced testing and debugging support via systematic projection-based runtime assertion and invariant generation for quantum programming. The success of this research agenda will enable a more complete and efficient software stack for improving the feasibility of supporting end-to-end quantum applications on near-term devices.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目设定了一项全面的研究议程，重点是构建用于量子计算的自上而下的汇编基础架构。它将开发理论和实用方法，以实现高级算法优化，低级脉冲优化以及全系统调试和分析。汇编堆栈将促进近期量子设备上的自动资源有效量子算法设计和高保真程序执行。它将受益于量子化学和组合优化等主要量子计算应用，并有助于美国在量子信息科学技术领域的领导。研究发现将通过开源软件包，主要会议和期刊的出版物，教学研讨会的教程以及专门的K-112计划，以将年轻一代暴露于量子信息研究的边界。编程，优化和调试。特定目标包括1）一种语言和自动调整器，以使量子计算域中的资源有效算法开发自动化； 2）脉冲级汇编基础架构，以利用脉冲变化的丰富自由度，并调度更有效的优化和缓解误差； 3）通过基于系统投影的运行时断言和用于量子编程的不变生成的高级测试和调试支持。这项研究议程的成功将使更完整，更有效的软件堆栈能够提高支持近期设备上端到端量子应用程序的可行性。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响审查标准来通过评估来通过评估来支持的。