The 1st International Workshop on Network Science for Quantum Communication Networks (NetSciQCom 2022)
Rodney Van Meter (Keio University, Japan)
Nageswara Rao (Oak Ridge National Laboratory, United States)
Quantum Networking and Communications at Oak Ridge National Laboratory
Nicholas Peters, Muneer Alshowkan, Joseph Chapman, Phil Evans, David Hooper, Warren Warren Grice, Hsuan-Hao Lu, Joe Lukens, Raphael Pooser, Claire Marvinney, Alexander Miloshevsky, Brian Williams and Brandon Wilson (Oak Ridge National Laboratory, USA)
In this article we review recent and ongoing research in quantum communications and networking within the Quantum Information Science Section at Oak Ridge National Laboratory. Our research spans applications such as quantum key distribution as well as more fundamental aspects needed to develop scalable quantum networks including quantum repeaters and space-based quantum communications platforms.
Quantum Data Networking for Distributed Quantum Computing: Opportunities and Challenges
Chunming Qiao (University at Buffalo, USA); Yangming Zhao, Gongming Zhao and Hongli Xu (University of Science and Technology of China, China)
Quantum Data Networking can significantly transform the landscape of quantum computing by enabling several small quantum computers (QCs) to form a distributed system to achieve the same computing power as a large quantum computer which is infeasible to build. However, this requires quantum state information, in the form of qubits, to be exchanged among multiple geographically distributed QCs, and there are many challenges associated with reliably transferring qubits from one QC to another efficiently. In this paper, we discuss various QDN design options, present main challenges and describe promising solutions to tackle the challenges.
Guoliang Xue (Arizona State University, United States)
Order Matters: On the Impact of Swapping Order on an Entanglement Path in a Quantum Network
Alena Chang and Guoliang Xue (Arizona State University, USA)
In this paper, we study the properties of path metrics of an entanglement path for a given entanglement swapping order of the path. We show how to efficiently compute the path metrics of an entanglement path for any given swapping order. We also show that different entanglement swapping orders for the same path can lead to different expected throughputs. A key finding is that the binary operator corresponding to entanglement swapping along a path is not associative. We further show that the problem of computing an s-t path with maximum expected throughput under any entanglement swapping order does not have the sub-path optimality property. In contrast, many traditional path finding problems such as the minimum delay path problem and the most reliable path problem all have the sub-path optimality property, which is a key property most path finding algorithms such as Dijkstra's algorithm rely on. We perform extensive simulations to validate our theoretical findings.
Optimal Entanglement Distribution using Satellite Based Quantum Networks
Nitish K. Panigrahy (Yale University, USA); Prajit Dhara (University of Arizona, USA); Don Towsley (University of Massachusetts at Amherst, USA); Saikat Guha (University of Arizona, USA); Leandros Tassiulas (Yale University, USA)
Recent technological advancements in satellite based quantum communication has made it a promising technology for realizing global scale quantum networks. Due to better loss distance scaling compared to ground based fiber communication, satellite quantum communication can distribute high quality quantum entanglements among ground stations that are geographically separated at very long distances. This work focuses on optimal distribution of bipartite entanglements to a set of pair of ground stations using a constellation of orbiting satellites. In particular, we characterize the optimal satellite-to-ground station transmission scheduling policy with respect to the aggregate entanglement distribution rate subject to various resource constraints at the satellites and ground stations. We cast the optimal transmission scheduling problem as an integer linear programming problem and solve it efficiently for some specific scenarios. Our framework can also be used as a benchmark tool to measure the performance of other potential transmission scheduling policies.
Adaptive, Continuous Entanglement Generation for Quantum Networks
Alexander Kolar and Allen Zang (University of Chicago, USA); Joaquin Chung and Martin Suchara (Argonne National Laboratory, USA); Rajkumar Kettimuthu (Argonne National Lab, USA)
Joint modulation of 3-PPM and quantum squeezed states in communication systems
Yaoyao Wang (China); Xiaoguang Chen (Fudan University, China)
Arunabha Sen (ASU, United States)