QuIC-TAQS: Voltage-Tunable Hybrid Microwave-Acoustic Interconnects for Multi-modal Quantum Memories
QuIC-TAQS:用于多模态量子存储器的电压可调混合微波声互连
基本信息
- 批准号:2137776
- 负责人:
- 金额:$ 249.95万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-08-01 至 2026-07-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Quantum computers are expected to revolutionize the future of science and technology by solving complex problems that are beyond the reach of current classical supercomputers. So far, several physical platforms have been demonstrated as prototypes for implementation of universal quantum processors. Each physical implementation holds specific benefits in demonstrating coherent manipulation of quantum state while suffering downfalls that prevent their scalable integration. Many quantum computing tasks would benefit enormously from the ability to coherently connect those physically distinct information processing platforms. One such application is quantum random access memory (QRAM), a key component in many well-known quantum algorithms that allows stored data to be extracted in quantum superposition. This research develops a hybrid QRAM device composed of superconducting qubits and high-quality acoustic cavities joined together by highly tunable interconnects. The team will draw on their expertise in materials science, nanofabrication, quantum device physics, and quantum information theory to construct and optimize this device. This project entails integrated research, education, and outreach efforts that encourage full participation of underrepresented groups in quantum science and technology, including summer camps for K-12 students and teachers, course and outreach material development, undergraduate and graduate research and advising, and postdoc mentoring.Although QRAM is central to many important applications such as Grover’s search algorithm and solving linear systems of equations on a quantum computer, its experimental implementation has remained elusive. This is due to challenges in building a system that offers both a high-quality multi-mode quantum memory and a high degree of controllability. This project addresses this long-standing challenge by combining one of the frontrunners for quantum computing---superconducting Transmon qubits---with state-of-the-art acoustic resonator memories, which offer highly compact, long-lived quantum information storage. A coherent switchable interconnect needed for QRAM or transduction operation is provided by a voltage-tunable resonator that integrates a hybrid superconductor–semiconductor Josephson junction for on demand tuning of resonance frequency. This effort will not only lead to the first demonstration of QRAM in the laboratory but will also significantly advance the field of quantum transduction, where acoustic cavity modes are widely recognized as one of the most promising ways to connect distinct physical platforms due to their versatility and compatibility with a range of quantum systems.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.
量子计算机有望通过解决当前经典超级计算机无法解决的复杂问题来彻底改变科学技术的未来。到目前为止,已经有几个物理平台被证明是实现通用量子处理器的原型。每个物理实现都有特定的好处,可以展示量子态的相干操纵,同时遭受阻止其可扩展集成的失败。许多量子计算任务将从连贯连接这些物理上不同的信息处理平台的能力中受益匪浅。其中一个应用是量子随机存取存储器(QRAM),这是许多众所周知的量子算法中的关键组件,它允许以量子叠加的方式提取存储的数据。本研究发展一种混合QRAM装置,其由超导量子位和高品质声腔组成,并通过高度可调的互连线连接在一起。该团队将利用他们在材料科学,纳米纤维,量子器件物理和量子信息理论方面的专业知识来构建和优化该设备。该项目需要综合研究,教育和推广工作,鼓励代表性不足的群体充分参与量子科学和技术,包括K-12学生和教师夏令营,课程和推广材料开发,本科生和研究生研究和咨询,虽然QRAM是许多重要应用程序的核心,如Grover的搜索算法和求解线性方程组。虽然量子计算机上的方程,其实验实现仍然难以捉摸。这是由于构建一个既能提供高质量多模量子存储器又能提供高度可控性的系统所面临的挑战。该项目通过将量子计算的领跑者之一-超导量子比特-与最先进的声学谐振器存储器相结合来解决这一长期存在的挑战,声学谐振器存储器提供高度紧凑,长寿命的量子信息存储。QRAM或换能操作所需的相干可切换互连由电压可调谐谐振器提供,该电压可调谐谐振器集成了用于谐振频率的按需调谐的混合超导体-半导体约瑟夫森结。这一努力不仅将导致QRAM在实验室中的首次演示,而且还将显著推进量子转导领域,其中声腔模式由于其多功能性和与一系列量子系统的兼容性而被广泛认为是连接不同物理平台的最有前途的方法之一。该奖项反映了NSF的法定使命,并被认为值得通过使用基金会的学术价值和更广泛的影响审查标准。
项目成果
期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
专利数量(0)
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Lin Zhu其他文献
Controllable fabrication of graded and gradient porous polypropylene
分级和梯度多孔聚丙烯的可控制造
- DOI:
10.1007/s10934-014-9878-4 - 发表时间:
2015 - 期刊:
- 影响因子:2.6
- 作者:
Lin Zhu;Ya Wang;X. Yu;Xiang‐qian Shen;Xinhua Xu - 通讯作者:
Xinhua Xu
A Fast and Accurate Transient Stability Assessment Method Based on Deep Learning: WECC Case Study
基于深度学习的快速准确暂态稳定性评估方法:WECC案例研究
- DOI:
10.1109/isgt50606.2022.9817531 - 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Yinfeng Zhao;Shutang You;Mirka Mandich;Lin Zhu;Chengwen Zhang;Hongyu Li;Yu Su;Yilu Liu;Huaiguang Jiang;Haoyu Yuan;Y. Zhang;Jin Tan - 通讯作者:
Jin Tan
A Methods Review of Post-trial Follow-up Studies of Cardiovascular Prevention Finds Potential Biases in Estimating Legacy Effects.
心血管预防试验后随访研究的方法回顾发现估计遗留效应的潜在偏差。
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:7.2
- 作者:
Lin Zhu;K. Bell;A. Nayak;A. Hayen - 通讯作者:
A. Hayen
Quasi-Static Time Series Fatigue Simulation for PV Inverter Semiconductors with Long-Term Solar Profile
具有长期太阳能曲线的光伏逆变器半导体的准静态时间序列疲劳仿真
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Yunting Liu;L. Tolbert;Paychuda Kritprajun;Q. Dong;Lin Zhu;J. Hambrick;K. Schneider;K. Prabakar - 通讯作者:
K. Prabakar
Multiple-quantum-well Perovskite for Hole-transport-layer-free Light-emitting Diodes
用于无空穴传输层发光二极管的多量子阱钙钛矿
- DOI:
10.1016/j.cclet.2021.06.084 - 发表时间:
2021 - 期刊:
- 影响因子:9.1
- 作者:
Peifeng Li;Jie Wang;Hong Chen;Hao Zhang;Cheng Li;Wenjie Xu;Renzhi Li;Lin Zhu;Nana Wang;Jianpu Wang - 通讯作者:
Jianpu Wang
Lin Zhu的其他文献
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{{ truncateString('Lin Zhu', 18)}}的其他基金
EAGER:Coupled Optomechanical Resonators and Arrays
EAGER:耦合光机谐振器和阵列
- 批准号:
1331728 - 财政年份:2013
- 资助金额:
$ 249.95万 - 项目类别:
Standard Grant
Collaborative Research: Hybrid Integration of Plasmonic Interferometer Sensors and Active Optoelectronic Devices on a Single Microfluidic Chip
合作研究:在单个微流控芯片上混合集成等离子体干涉仪传感器和有源光电器件
- 批准号:
1127957 - 财政年份:2011
- 资助金额:
$ 249.95万 - 项目类别:
Standard Grant
Controlling and enhancing optical gradient forces in integrated optomechanical devices
控制和增强集成光机设备中的光学梯度力
- 批准号:
1101845 - 财政年份:2011
- 资助金额:
$ 249.95万 - 项目类别:
Standard Grant
相似国自然基金
北半球历史生物地理学问题探讨:基于RAD taqs方法的紫荆属亲缘地理学研究
- 批准号:31470312
- 批准年份:2014
- 资助金额:85.0 万元
- 项目类别:面上项目
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