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Toolkit for Characterizing Noisy Quantum Processors and Windows of Quantum Advantage

用于表征噪声量子处理器和量子优势窗口的工具包

基本信息

批准号：
1915165
负责人：
Tzu-Chieh Wei
金额：
$ 33万
依托单位：
SUNY at Stony Brook
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-01 至 2023-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1915165&HistoricalAwards=false
关键词：
Toolkit Characterizing Noisy Quantum Processors

项目摘要

Quantum computers offer potential advantages and possibly exponential speedup over existing classical computers for certain computational tasks. Success in building large-scale functioning quantum computers will undoubtedly be a revolution in computer technology. However, many of these applications will require quantum computers with very small error rates and which use quantum error corrections for tolerating faults - a technology that is still out of reach for near-term noisy devices. Nevertheless, there are certain tasks that near-term quantum processors can perform but are still difficult for the current best classical computers. The demonstration of a quantum advantage will first require development of tools characterizing the operation of quantum gates, state preparation and measurement, as well as the corresponding errors. This project will integrate these tools to streamline their use in cloud quantum computers. Understanding the noise and errors also helps to devise mitigation strategies so as to extract as much as possible the correct computation. This project will also employ classical simulations to compare the expected outcomes with runs on quantum computers and analyze schemes for demonstrating potential quantum advantages.The goal of this project is to develop and assemble a toolkit for near-term quantum information processing that may yield quantum advantage. In particular, the PI will design and integrate tools for (1) noisy-gate characterization of tomographic tools, (2) randomized benchmarking, (3) error mitigation methods. These will be tested in actual runs on cloud quantum computers. Furthermore, (4) classical simulations will be developed, such as tensor-network methods, for noisy quantum circuits, and (5) schemes for quantum supremacy via short-depth quantum circuits will be assessed. Other new schemes will also be explored that will provide alternative playgrounds for showing the advantages of quantum devices over classical ones. Developing a toolkit that consists of technical approaches and software building will help to verify intermediate-scale noisy quantum information processing and identify windows of parameters guiding towards demonstrating quantum advantage. This project will also involve training of graduate students in research activities, presentation and writing skills, and mentoring in career planning. It will provide undergraduates and high-school students some first-hand experience in quantum information science (QIS) research. The PI will work with his colleagues to develop a quantum information science/quantum technology track in the Master's program in the Department of Physics and Astronomy. Creation of such a QIS track/program will help steadily train a quantum-smart workforce that is projected to be of high demand in the United States in the next few decades.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.

量子计算机在某些计算任务上提供了潜在的优势，并可能比现有的经典计算机加速。建造大规模量子计算机的成功无疑将是计算机技术的一场革命。然而，这些应用中的许多将需要具有非常小的错误率的量子计算机，并且使用量子纠错来容忍故障-这一技术对于近期的噪声设备来说仍然遥不可及。尽管如此，近期的量子处理器可以执行某些任务，但对于目前最好的经典计算机来说仍然很困难。量子优势的证明首先需要开发表征量子门操作、状态准备和测量以及相应误差的工具。该项目将整合这些工具，以简化它们在云量子计算机中的使用。了解噪声和错误也有助于设计缓解策略，以便尽可能多地提取正确的计算。该项目还将使用经典模拟来比较预期结果与量子计算机上的运行，并分析方案以展示潜在的量子优势。该项目的目标是开发和组装一个工具包，用于近期量子信息处理，可能产生量子优势。特别是，PI将设计和集成工具，用于（1）断层扫描工具的噪声门表征，（2）随机基准测试，（3）错误缓解方法。这些将在云量子计算机上的实际运行中进行测试。此外，（4）将开发经典模拟，如张量网络方法，用于有噪声的量子电路，（5）将评估通过短深度量子电路实现量子霸权的方案。其他新的方案也将被探索，这将为展示量子设备相对于经典设备的优势提供替代的操场。开发一个由技术方法和软件构建组成的工具包将有助于验证中等规模的噪声量子信息处理，并确定引导展示量子优势的参数窗口。该项目还将涉及对研究生进行研究活动、演讲和写作技能方面的培训，以及职业规划方面的指导。它将为本科生和高中生提供量子信息科学（QIS）研究的第一手经验。 PI将与他的同事合作，在物理和天文学系的硕士课程中开发量子信息科学/量子技术轨道。创建这样一个QIS轨道/计划将有助于稳步培养量子智能劳动力，预计将在未来几十年内在美国的高需求。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。