Neural Network Quantum Error Mitigation for Algorithms on Near-Term Intermediate Scale Quantum Devices

近期中规模量子设备算法的神经网络量子误差缓解

• 批准号: 2138113
• 负责人: Justin Reyes
• 金额: $ 30万
• 依托单位: Reyes, Justin
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2138113&HistoricalAwards=false
• 关键词: Neural; Network; Quantum; Error; Mitigation

Justin Reyes is awarded an NSF Mathematical and Physical Sciences Ascending Postdoctoral Research Fellowship to conduct a program of research and education at the University of Central Florida. Reyes will utilize machine learning algorithms for the detection, categorization, and mitigation of errors from various noise channels in quantum circuits. The goal will be to develop and optimize algorithms which mitigate errors in quantum variational algorithms that are implementable on Noisy Intermediate-Scale Quantum (NISQ) devices. Along with the research, Reyes intends to act as a mentor to underrepresented minority students through the American Physical Society Bridge Program in Physics.The contributions of this proposal onto the scientific community are numerous. In quantum computation, the success of this proposed research would advance the progress of current implementations of quantum computation on NISQ devices, providing a novel and improved means of characterizing and mitigating noise in quantum circuits. Within the field of quantum many-body systems and quantum chemistry, more accurate approximations to the ground states of molecular energies would be obtained. In computer science, the results of this proposal would advance the study of combinatorial optimization by providing more accurate approximate solutions, while potentially paving a path forward for continued improvement. Within mathematics, a deeper understanding of the correlations between noise and the spread of error would be provided, leading to potentially new models of noise characterization.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.

贾斯汀·雷耶斯被授予美国国家科学基金会数学和物理科学提升博士后研究奖学金，以在中佛罗里达大学开展一项研究和教育项目。雷耶斯将利用机器学习算法来检测、分类和缓解量子电路中各种噪声通道的错误。目标将是开发和优化算法，以减轻量子变分算法中的错误，这些算法可以在有噪声的中间尺度量子(NISQ)设备上实现。随着这项研究的进行，雷耶斯打算通过美国物理学会物理学桥梁计划，为未被充分代表的少数族裔学生提供指导。这一提议对科学界的贡献是巨大的。在量子计算方面，这项研究的成功将推动目前在NISQ器件上实现量子计算的进展，为表征和降低量子电路中的噪声提供一种新的和改进的手段。在量子多体系统和量子化学领域中，分子能量的基态将得到更精确的近似。在计算机科学中，这一建议的结果将通过提供更准确的近似解来推进组合优化的研究，同时可能为继续改进铺平道路。在数学中，将提供对噪声和误差传播之间的相关性的更深层次的理解，从而导致潜在的新的噪声特征模型。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。