Collaborative Research: FET: Medium: Robust Quantum Networks via Efficient Entanglement Distribution

量子计算有潜力，如果实现，将显著改变计算格局。然而，建造大规模量子计算机是一个关键挑战。量子网络(QN)通过连接较小的量子计算机，使构建大型、强大和更有能力的量子计算平台成为可能。联网的量子系统有可能显著改变社会的各种活动，因为它导致了医学和工程学的更快发展；更安全和保护隐私的通信；这个项目还利用量子网络的潜力和吸引力来设计和提供各种教育计划，包括一个灵活的量子计算和网络学士后计划，以迎合非传统学生，改善本科生和研究生群体的多样性，并发展一支有量子能力的劳动力。构建支持跨节点稳健通信的量子网络需要几个基本的科学和技术进步，特别是因为经典技术不能直接用于量子制度。量子网络可以用来构建比独立量子计算机更强大、更具弹性的量子计算系统。这个项目正在研究量子网络的设计和实现，通过开发一种基础设施来有效地通信和管理网络中的量子纠缠。此外，该项目正在解决量子网络的两个关键应用中的具体挑战：(I)分布式量子算法，和(Ii)量子传感器网络。该项目正在使用大规模模拟和遍布纽约长岛的6节点QN试验台来评估开发的技术。试验台提供了一个高保真的平台来评估我们开发的技术的有效性。总体而言，该项目有三个研究推动力。第一个推力，该项目正在开发一个基础设施，以促进有效的沟通和纠缠管理。特别是，它正在开发优化技术，以(I)使用多条路径高效地产生长距离纠缠，以及(Ii)高效地分配预先分配的纠缠。此外，该项目正在开发实际环境中有效的纠缠蒸馏策略，以及用于组播原语的协议。在第二个重点中，该项目是在两个关键的QN应用的背景下解决挑战，以证实和验证所开发的技术。特别是，该项目正在开发用于集中式量子电路的高效分布式实现的优化技术；高效的分布式实现对于QN的计算成功非常重要。在量子传感器网络的背景下，它正在设计有效的协议来估计二元参数函数，并研究在这些设置下纠缠的好处。在第三个推力中，该项目使用大规模模拟和小型QN试验台来评估上述技术。为了有效地评估QN的绩效，该项目正在为QN制定新的绩效指标；这需要对经典的网络指标进行非平凡的概括。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Quantum Computing has the potential, if realized, to significantly alter the computing landscape. However, building large-scale quantum computers is a key challenge. Quantum Networks (QNs) enable the construction of large, robust, and more capable quantum-computing platforms by connecting smaller quantum computers. Networked quantum systems have the potential to significantly alter various activities in society by leading to faster development in medicine and engineering; more secure and privacy-preserving communication; and hitherto infeasible optimizations that leverage the immense computational power to identify efficiencies in manufacturing, logistics, finance, etc. This project is also using the potential and attractiveness of QNs to design and offer a variety of educational programs, including a flexible post-baccalaureate program in quantum computing and networking to cater to non-traditional students, improve the diversity of undergraduate and graduate student body, and develop a quantum capable workforce.Building QNs that support robust communication across nodes requires several fundamental scientific and technological advances, especially since classical techniques cannot be directly used in the quantum regime. QNs can be used to build quantum computing systems that are more capable and more resilient than stand-alone quantum computers. This project is examining the design and implementation of QNs from the ground up by developing an infrastructure for efficient communication and management of quantum entanglements in the network. In addition, the project is addressing specific challenges in two key applications of QNs: (i) Distributed quantum algorithms, and (ii) Quantum sensor networks. The project is evaluating the developed techniques using large-scale simulations and over a 6-node QN testbed spread across Long Island, NY. The testbed is providing a high-fidelity platform to evaluate the effectiveness of our developed techniques. Overall, the project has three research thrusts.In the first thrust, the project is developing an infrastructure to facilitate efficient communication and entanglement management. In particular, it is developing optimization techniques for (i) efficient generation of long-distance entanglement using multiple paths, and (ii) efficient distribution of pre-distributed entanglements. In addition, the project is developing efficient entanglement-distillation strategies in practical settings, and protocols for multicast primitives. In the second thrust, the project is addressing challenges in the context of two key QN applications to corroborate and validate the developed techniques. In particular, the project is developing optimization techniques for efficient distributed implementation of centralized quantum circuits; efficient distributed implementations are important for QN’s computational success. In the context of quantum sensor networks, it is designing efficient protocols for the estimation of binary parameter functions and investigating the benefit of entanglements in these settings. In the third thrust, the project is evaluating the above techniques using large-scale simulations and a small QN testbed. To evaluate QN performance effectively, the project is formulating novel performance metrics for QNs; this requires non-trivial generalization of the classical network metrics.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.