FET: Small: Collaborative Research: Efficient and Robust Characterization of Quantum Systems

FET：小型：协作研究：量子系统的高效且稳健的表征

• 批准号: 1909141
• 负责人: Amir Kalev
• 金额: $ 3万
• 依托单位: University of Maryland, College Park
• 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 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1909141&HistoricalAwards=false
• 关键词: FET; Small; Collaborative; Research; Efficient

Advances in quantum information and algorithms enable solutions that are beyond the reach of conventional technologies, with applications in many-body quantum physics, chemistry, cryptography, communication, and machine learning. While prototypes for quantum computers are being built, these are still prone to errors: reducing the noise to a tolerable and controllable level faces technical hurdles. To be able to scale-up to a full-fledged quantum computer, it is imperative to characterize, verify, and rigorously certify the behavior of current and near-future prototypes. The latter task incurs a heavy burden in data acquisition, processing and storage that leads to a pressing need for efficient and noise-robust characterization and verification protocols to test current quantum devices. The work done by members of this research team on novel optimization theory and algorithms, compressed sensing, and verification techniques have direct applications to this problem. The project will investigate and propose novel, highly-efficient, and robust methodologies to characterize, verify, and certify the behavior of quantum systems implementations, for better acquisition and processing of quantum information. The research will affect positively on how non-convex algorithms could be used in modern data science applications. Key broader outcomes of this proposal will be the establishment of an academic-industry collaboration (with the mentorship of two students in the process), and the introduction of quantum computing courses to Rice University.This project focuses on benchmarking and testing quantum states and processes, through efficient, noise-robust and provable quantum state tomography, as well as novel validation and certification tools for quantum computing. This research proposes to investigate new theoretical and practical approaches, via the following three paths: i) By using provable methods for distributing non-convex computations and optimization for the task of large-scale quantum state tomography. The proposed method complements the setting of compressed sensing quantum state tomography, where only a few measurements --compared to full tomography-- are available from a low-rank (highly-pure) quantum state and will be used in settings that are beyond the reach of state-of-the-art approaches. ii) By robustifying state-of-the-art validation methods using noise-robust optimization and techniques. The proposed research involves new, customized non-convex algorithms for the case where measurements are contaminated with non-homogeneous noise. iii) By designing efficient and noise-robust schemes for validating and certifying experimentally-relevant quantum operations. This project will study schemes to validate gates and error models behavior, which in turn will help certify the quality of the basic physical operations. The results of this proposal will be publicly available as an integrated part of an open-source software framework, in order to enhance reproducibility on available quantum information processors.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.

量子信息和算法的进步启用了无法实现传统技术的解决方案，并在多体量子物理学，化学，密码学，通信和机器学习中应用。虽然正在建造量子计算机的原型，但这些原型仍然容易出现错误：将噪声降低到可容忍的可控制水平的面孔技术障碍。为了能够扩展到成熟的量子计算机，必须表征，验证和严格证明当前和近乎未来的原型的行​​为。后一个任务会导致数据采集，处理和存储负担，这导致对有效和噪声的表征和验证协议的迫切需求，以测试当前的量子设备。该研究团队成员在新型优化理论和算法，压缩感应和验证技术方面所做的工作直接应用于此问题。该项目将调查并提出新颖，高效且健壮的方法，以表征，验证和证明量子系统实施的行为，以更好地获取和处理量子信息。这项研究将对现代数据科学应用中如何使用非凸算法产生积极影响。该提案的主要更广泛的结果将是建立学术 - 行业合作（在两个学生中的指导下），并向赖斯大学引入量子计算课程。该项目着重于基准测试和测试量子状态和流程，通过有效的，噪声量化的量子态和可预期的量子状态态层状和证书的量子化量和认证工具，以及量子化的新颖验证工具，以实现量子化和认证工具。 这项研究建议通过以下三个途径研究新的理论和实用方法：i）通过使用可证明的方法分发非convex计算和优化大规模量子状态层析成像的任务。所提出的方法补充了压缩传感量子层造影的设置，在该设置中，只有少量测量（到完整的层析成像）可以从低级别（高纯度）量子状态获得，并且将用于无法实现最先进方法的设置。 ii）通过使用噪声优化和技术来鲁棒化最新的验证方法。拟议的研究涉及新的，定制的非凸算法，以使测量受到非均匀噪声污染的情况。 iii）通过设计有效和噪声的方案，以验证和证明与实验相关的量子操作。该项目将研究验证门和错误模型行为的方案，这反过来将有助于证明基本的物理操作的质量。该提案的结果将作为开源软件框架的集成部分公开提供，以增强对可用量子信息处理器的可重复性。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评估值得通过评估来支持的。