FET: CIF: Small: Distributed Quantum Information Processing using Structured Operators

FET：CIF：小型：使用结构化运算符的分布式量子信息处理

基本信息

批准号：
2007878
负责人：
Sandeep Sadanandarao
金额：
$ 40万
依托单位：
Regents of the University of Michigan - Ann Arbor
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-10-01 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2007878&HistoricalAwards=false
关键词：
FET CIF Small Distributed Quantum

项目摘要

Many quantum communication/computing algorithms require quantum computers performing logical operations simultaneously on a sufficiently large number of quantum bits which have been combined into a superposition state. Unfortunately, the current state-of-the-art quantum computers can only operate on tens of qubits for storing and processing tasks. One of the biggest obstacles toward building a scalable quantum system is decoherence, a term that encompasses all the processes contributing to the decay of information coded in a quantum register. As the number of qubits is increased, the decoherence rate increases, and hence quantum information becomes more fragile. One way to overcome this challenge is to employ the distributed paradigm, where a network of limited qubit-capacity quantum computers, connected through classical and quantum links, are used to solve problems in a distributed manner by casting known centralized algorithms into their distributed versions. This may have significant impact on the society in terms of superior computing and communication platforms. One of the goals of this project is to provide bridge among different disciplines such as quantum mechanics, information theory, and abstract algebra, and thereby contribute to furthering collaborations between communities. A concerted effort is made to involve women and under-represented minority students in this project,This project aims to develop a foundational approach to address some of the challenges in distributed quantum information processing, communication, and computation from a quantum information-theoretic perspective. The research effort of this project is based on two interconnected yet complementary research thrusts. In one thrust of the project, the problem of distributed measurement compression is addressed based on a novel Markov structured quantum measurements and the technique of random binning. Other implications of this approach, both concerning fundamental problems and practical applications are highlighted. In the second thrust of the project, a novel approach for studying distributed reliable (lossless) compression and computation of quantum sources is considered. As a part of the second thrust, the quantum-to-quantum rate distortion problem is addressed from a new perspective -- by exploring the duality connection between the problem of quantum error correction over a quantum channel and rate-distortion compression of a quantum source. This project also addresses problem of distributed function computation in the context of quantum-to-classical rate-distortion coding.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.

许多量子通信/计算算法都需要在足够数量的量子位上同时执行逻辑操作的量子计算机，这些量子位已合并为叠加态。不幸的是，当前的最新量子计算机只能在数十台用于存储和处理任务的量子位上运行。构建可扩展量子系统的最大障碍之一是破坏性，该术语涵盖了有助于量子寄存器中编码的信息衰减的所有过程。随着Qubits数量的增加，反应速率增加，因此量子信息变得更加脆弱。克服这一挑战的一种方法是利用分布式范式，在这种范式中，通过经典和量子链路连接的有限量子能力量子计算机网络通过将已知的集中算法投入到分布式版本中来以分布式方式来解决问题。这可能会在卓越的计算和通信平台方面对社会产生重大影响。该项目的目标之一是在不同学科（例如量子力学，信息理论和抽象代数）等不同学科之间提供桥梁，从而有助于促进社区之间的合作。该项目旨在使妇女和代表性不足的少数族裔学生参与一致的努力，该项目旨在开发一种基本方法，以解决分布式量子信息处理，沟通和计算的一些挑战，从量化信息理论的角度来看。该项目的研究工作基于两个相互联系但互补的研究推力。在项目的一个推力中，基于新颖的马尔可夫结构化量子测量和随机套在一起的技术来解决分布式测量压缩的问题。这种方法的其他含义，关于基本问题和实用应用的既重点又突出了。在该项目的第二个推力中，考虑了研究分布式可靠（无损）压缩和量子源的计算的新型方法。作为第二个推力的一部分，从新的角度解决了量子到量子率失真问题 - 通过探索量子通道上量子误差校正问题与量子源的速率降低压缩之间的双重性连接。该项目还解决了分布式功能计算问题在量子到古典率延伸编码的背景下。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估来获得支持。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Computing Sum of Sources over a Classical-Quantum MAC

通过经典量子 MAC 计算源之和

DOI：
10.1109/tit.2022.3192876
发表时间：
2021
期刊：
IEEE Transactions on Information Theory
影响因子：
2.5
作者：
Sohail, Mohammad Aamir;Atif, Touheed Anwar;Padakandla, Arun;Sandeep Pradhan, S.
通讯作者：
Sandeep Pradhan, S.

Synthesizing Correlated Randomness using Algebraic Structured Codes

使用代数结构化代码合成相关随机性