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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 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.

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.

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.

Quantum networks, which enable the transfer of quantum information across long distances, promise to provide exciting benefits and new possibilities in many areas including communication, computation, security, and metrology. These networks rely on entanglement between qubits at distant nodes to transmit information; however, creation of these quantum links is not dependent on the information to be transmitted. Researchers have explored schemes for continuous generation of entanglement, where network nodes may generate entanglement links before receiving user requests. In this paper we present an adaptive scheme that uses information from previous requests to better guide the choice of randomly generated quantum links before future requests are received. We analyze parameter spaces where such a scheme may provide benefit and observe an increase in performance of up to 75% over other continuous schemes on single-bottleneck and autonomous systems networks. We also test the scheme for other parameter choices and observe continued benefits of up to 95%. The power of our adaptive scheme on a randomized request queue is demonstrated on a single-bottleneck topology. We also explore quantum memory allocation scenarios, where a difference in latency performance implies the necessity of optimal allocation of resources for quantum networks.

Pulse position modulation(PPM) is an excellent modulation form that is widely used for deep-space information transmission and also in quantum modulation form. It is verified that the squeezed state is superior to the traditional coherent state modulation in 3-PPM modulation. In this paper, a new modulation method is proposed, that is, two squeezed states are applied to 3-PPM modulation. Compared with one squeezed state modulation, it is found that the two squeezed state modulation has lower error probability.