REU Site: Quantum Algorithms and Optimization (QAO)

REU 网站：量子算法和优化 (QAO)

• 批准号: 2244512
• 负责人: Rebekah Herrman
• 金额: $ 36.02万
• 依托单位: University of Tennessee Knoxville
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-15 至 2026-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2244512&HistoricalAwards=false
• 关键词: REU; Site; Quantum; Algorithms; Optimization

Quantum algorithms have the potential to revolutionize how currently intractable problems are solved, however more research is required to realize their full potential. The goal of this Research Experience for Undergraduates (REU) site is to encourage student participation in cutting-edge, interdisciplinary quantum computing research that focuses on solving large-scale optimization problems. Optimization problems are the focus of this research as they have real-world applications, such as packaging routing and scheduling. Undergraduates who participate in this REU site will gain critical research experience by developing code that implements quantum algorithms, mathematically proving bounds on algorithm performance, and comparing leading quantum algorithms to the best classical algorithms. Furthermore, the students will participate in professional development opportunities that are designed to encourage them to consider their career plans.The proposed REU site will host ten students for ten weeks each summer. Participants will perform quantum algorithms research as applied to solve realistic, large-scale combinatorial optimization problems. Students will learn fundamental quantum algorithms research techniques such as how to run quantum algorithms on hardware, use machine learning and statistical methods to analyze data generated by the experiments, and provide theoretical or computational performance bounds. The goals of the program are to broaden student participation in interdisciplinary quantum computing research, develop the next generation quantum computing workforce, and develop participants’ research and scientific writing skills. The projects for this REU site will be designed so that the students’ research will become more independent as the summer progresses. Pre- and post- program surveys will be administered and the results will be used to refine the REU site each year.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.

量子算法有可能彻底改变目前棘手问题的解决方式，但需要更多的研究才能充分发挥其潜力。这个本科生研究体验（REU）网站的目标是鼓励学生参与尖端的跨学科量子计算研究，重点是解决大规模优化问题。优化问题是本研究的重点，因为它们具有实际应用，如包装路由和调度。参加这个REU网站的本科生将通过开发实现量子算法的代码，数学上证明算法性能的界限，以及将领先的量子算法与最佳经典算法进行比较来获得关键的研究经验。此外，学生将参加专业发展机会，旨在鼓励他们考虑自己的职业规划。拟议的REU网站将在每年夏天接待十名学生十周。参与者将进行量子算法研究，以解决现实的大规模组合优化问题。学生将学习基本的量子算法研究技术，例如如何在硬件上运行量子算法，使用机器学习和统计方法来分析实验生成的数据，并提供理论或计算性能界限。 该计划的目标是扩大学生参与跨学科量子计算研究，培养下一代量子计算劳动力，并培养参与者的研究和科学写作技能。这个REU网站的项目将被设计，使学生的研究将成为夏季的进展更加独立。项目前和项目后的调查将被管理，调查结果将用于每年改进REU网站。该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估的支持。