FET: Small: Efficient Inference Tools for Quantum Systems: Algorithms, Applications, and Analysis

FET：小型：量子系统的高效推理工具：算法、应用和分析

• 批准号: 1910571
• 负责人: Henry Pfister
• 金额: $ 50万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1910571&HistoricalAwards=false
• 关键词: FET; Small; Efficient; Inference; Tools

Quantum information science has entered an exciting new era. Researchers are now actively trying to build quantum computers that can achieve significant gains over classical computers. For example, Shor's quantum algorithm for factoring large integers can achieve an exponential speedup over the current best classical approaches. To realize this goal, however, researchers must design fault-tolerant protocols that deal with the fragile nature of quantum phenomena. In this broader context, this project will design efficient protocols to extract reliable information from noisy quantum devices. Another part of this project will use information-theoretic tools to study the information-processing power of quantum networks. The results are expected to have broad applications in quantum information science. The PIs will also mentor graduate students and provide undergraduate research opportunities in quantum technologies.The ability to distinguish quantum states is an important part of quantum communications and quantum information science. Even in relatively simple quantum systems, it can be difficult to design and implement good protocols for quantum state discrimination. One goal of this project is to answer the question: Are there efficient methods of quantum state discrimination that apply to large classes of practically relevant states? This is related to another part of the project, whose goal is to understand the strengths and limitations of quantum technology in the emerging era of noisy intermediate-scale quantum devices. This project will investigate the rate at which information and entanglement decay in noisy quantum networks. For instance, we will derive noise thresholds, below which information and entanglement can propagate through networks. Such results can be applied to fault-tolerant quantum computing and also to analyze information scrambling in chaotic quantum systems, such as black holes. Many research directions in this project are built upon mathematical tools for analyzing quantum systems, such as the strong data-processing inequality. The final part of this project will develop these tools and derive information-theoretic limits for quantum state discrimination and quantum networks.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.

量子信息科学进入了一个激动人心的新时代。研究人员现在正在积极尝试建造量子计算机，使其比传统计算机取得显著的进步。例如，Shor的分解大整数的量子算法可以比目前最好的经典方法实现指数级的加速。然而，为了实现这一目标，研究人员必须设计出容错协议，以处理量子现象的脆弱性。在这个更广泛的背景下，该项目将设计有效的协议，从有噪声的量子设备中提取可靠的信息。该项目的另一部分将使用信息理论工具来研究量子网络的信息处理能力。这一结果有望在量子信息科学中得到广泛应用。pi还将指导研究生，并提供量子技术方面的本科生研究机会。分辨量子态的能力是量子通信和量子信息科学的重要组成部分。即使在相对简单的量子系统中，也很难设计和实现量子态判别的良好协议。这个项目的一个目标是回答这个问题：是否存在适用于大量实际相关状态的有效量子态判别方法？这与该项目的另一部分有关，该项目的目标是了解量子技术在嘈杂的中等规模量子设备的新兴时代的优势和局限性。该项目将研究噪声量子网络中信息和纠缠衰减的速率。例如，我们将推导噪声阈值，低于该阈值，信息和纠缠可以通过网络传播。这些结果可以应用于容错量子计算，也可以用于分析混沌量子系统（如黑洞）中的信息混乱。本项目的许多研究方向是建立在分析量子系统的数学工具上的，例如强数据处理不等式。本项目的最后一部分将开发这些工具，并推导量子态鉴别和量子网络的信息理论限制。该奖项反映了美国国家科学基金会的法定使命，并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，被认为值得支持。

项目成果

Quantum Algorithm for Petz Recovery Channels and Pretty Good Measurements

• DOI: 10.1103/physrevlett.128.220502
• 发表时间: 2022-06-01
• 期刊: PHYSICAL REVIEW LETTERS
• 影响因子: 8.6
• 作者: Gilyen, Andras;Lloyd, Seth;Wilde, Mark M.
• 通讯作者: Wilde, Mark M.

Belief propagation with quantum messages for quantum-enhanced classical communications

• DOI: 10.1038/s41534-021-00422-1
• 发表时间: 2020-03
• 期刊: npj Quantum Information
• 影响因子: 7.6
• 作者: Narayanan Rengaswamy;K. Seshadreesan;S. Guha;H. Pfister

Adaptive procedures for discriminating between arbitrary tensor-product quantum states

用于区分任意张量积量子态的自适应程序

• DOI: 10.1103/physreva.106.012408
• 发表时间: 2022
• 期刊: Physical Review A
• 影响因子: 2.9
• 作者: Brandsen, Sarah;Lian, Mengke;Stubbs, Kevin D.;Rengaswamy, Narayanan;Pfister, Henry D.
• 通讯作者: Pfister, Henry D.

On explicit L2-convergence rate estimate for piecewise deterministic Markov processes in MCMC algorithms

• DOI: 10.1214/21-aap1710
• 发表时间: 2020-07
• 期刊: The Annals of Applied Probability
• 作者: Jianfeng Lu;Lihan Wang

Restrictions on realizable unitary operations imposed by symmetry and locality

• DOI: 10.1038/s41567-021-01464-0
• 发表时间: 2020-03
• 期刊: Nature Physics
• 影响因子: 19.6
• 作者: I. Marvian