Communication in quantum wireless multihop networks is useful in global quantum networks. We propose a scheme for faithful quantum communication in quantum wireless multihop networks, by performing quantum teleportation between two distant nodes which do not initially share entanglement with each other. The required entanglement among intermediate nodes is established through entanglement swapping based on arbitrary types of Bell pairs. All the measurement outcomes and the types of Bell pairs are sent to the destination node independently. The initial quantum state can be finally recovered by corresponding local operations. Our scheme can reduce end-to-end communication delay by using simultaneous measurements in contrast to the scheme based on sequential entanglement swapping.

The traditional method for information transfer in a quantum communication system using partially entangled state resource is quantum distillation or direct teleportation. In order to reduce the waiting time cost in hop-by-hop transmission and execute independently in each node, we propose a quantum bridging method with partially entangled states to teleport quantum states from source node to destination node. We also prove that the designed specific quantum bridging circuit is feasible for partially entangled states teleportation across multiple intermediate nodes. Compared to two traditional ways, our partially entanglement quantum bridging method uses simpler logic gates, has better security, and can be used in less quantum resource situation.

Quantum multi-hop teleportation is important in the field of quantum communication. In this study, we propose a quantum multi-hop communication model and a quantum routing protocol with multihop teleportation for wireless mesh backbone networks. Based on an analysis of quantum multi-hop protocols, a partially entangled Greenberger–Horne–Zeilinger (GHZ) state is selected as the quantum channel for the proposed protocol. Both quantum and classical wireless channels exist between two neighboring nodes along the route. With the proposed routing protocol, quantum information can be transmitted hop by hop from the source node to the destination node. Based on multi-hop teleportation based on the partially entangled GHZ state, a quantum route established with the minimum number of hops. The difference between our routing protocol and the classical one is that in the former, the processes used to find a quantum route and establish quantum channel entanglement occur simultaneously. The Bell state measurement results of each hop are piggybacked to quantum route finding information. This method reduces the total number of packets and the magnitude of air interface delay. The deduction of the establishment of a quantum channel between source and destination is also presented here. The final success probability of quantum multi-hop teleportation in wireless mesh backbone networks was simulated and analyzed. Our research shows that quantum multi-hop teleportation in wireless mesh backbone networks through a partially entangled GHZ state is feasible.

Synthetic aperture radar (SAR) is a kind of active imaging radar, which can obtain high-resolution wide-swath SAR images, especially for spaceborne SAR systems. In practical electromagnetic environment, due to the overlap of same frequency bands, spaceborne SAR is extremely vulnerable to interferences from other electromagnetic systems, called radio frequency interference (RFI) to SAR systems. RFI seriously reduces the imaging quality of the SAR system and causes resolution reduction and scene occluded. To mitigate RFI in SAR systems, researchers have proposed many methods, in which semi-parametric methods, such as robust principal component analysis (RPCA)-based methods, played important roles in strong RFI mitigation in recent years. However, it is observed that they may be hard to recover the true scene well under extremely strong RFIs since the strong scatterers are also mixed in the extracted low-rank interferences. Therefore, in this paper, we propose a novel adaptive method, which combines the advantages of both semi-parametric method and frequency domain notched filter (FNF) method, called adaptive notch semi-parametric (ANSP) method, where the FNF method, as a non-parametric method, can retain more true scenes when mitigating interferences. As a result, the proposed method can not only effectively deal with strong RFIs but also protect the strong scatterers better with an adaptive threshold. This method can recover the true scene under extremely strong RFI and be applied to both Level-0 and Level-1 SAR data. Finally, we conduct experiments on several real SAR data and demonstrate the effectiveness of the proposed method.

The advent of noisy intermediate-scale quantum (NISQ) devices provide crucial promise for the development of quantum algorithms. Variational quantum algorithms have emerged as one of the best hopes to utilize NISQ devices. Among these is the famous variational quantum eigensolver (VQE), where one trains a parameterized and fixed quantum circuit (or an ansatz) to accomplish the task. However, VQE also suffers from some serious challenges, which are training difficulty and accuracy reduction due to deep quantum circuit and hardware noise. Motivated by these issues, we propose a runtime and resource-efficient scheme, Monto Carlo tree (MCT) search-based quantum circuit architecture optimization, where the ansatz is built in the variable form. Our approach first models the search space with a MCT and regards it as a supernet, where we make use of layers dependence to reduce the size of the search space. Second, a two-stage scheme is proposed for the search space training, where weight sharing and warm-up strategies are employed to avoid huge computation cost. Training results are stored in nodes of the MCT for future decisions, and hierarchical node selection is presented to obtain an optimal ansatz. As a proof of principle, we carry out a series of numerical experiments for condensed matter and quantum chemistry in a quantum simulator with and without noise. Consequently, our scheme can be efficient to mitigate trainability and accuracy issues by minimizing the ansatz depth and the number of entanglement gates.