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Given the limitations on the number of qubits in current NISQ devices, the implementation of large-scale quantum algorithms on such devices is challenging, prompting research into distributed quantum computing. This paper focuses on the issue of excessive communication complexity in distributed quantum computing oriented towards quantum circuits. To reduce the number of quantum state transmissions, i.e., the transmission cost, in distributed quantum circuits, a circuit partitioning method based on the QUBO model is proposed, coupled with the lookahead method for transmission cost optimization. Initially, the problem of distributed quantum circuit partitioning is transformed into a graph minimum cut problem. The QUBO model, which can be accelerated by quantum algorithms, is introduced to minimize the number of quantum gates between QPUs and the transmission cost. Subsequently, the dynamic lookahead strategy for the selection of transmission qubits is proposed to optimize the transmission cost in distributed quantum circuits. Finally, through numerical simulations, the impact of different circuit partitioning indicators on the transmission cost is explored, and the proposed method is evaluated on benchmark circuits. Experimental results demonstrate that the transmission cost optimized through the method proposed in this paper is significantly reduced compared with current methods for optimizing transmission cost, achieving noticeable improvements across different numbers of partitions.

In this paper, we present some enhanced error estimates for augmented subspace methods with the nonconforming Crouzeix-Raviart (CR) element. Before the novel estimates, we derive the explicit error estimates for the case of single eigenpair and multiple eigenpairs based on our defined spectral projection operators, respectively. Then we first strictly prove that the CR element based augmented subspace method exhibits the second-order convergence rate between the two steps of the augmented subspace iteration, which coincides with the practical experimental results. The algebraic error estimates of second order for the augmented subspace method explicitly elucidate the dependence of the convergence rate of the algebraic error on the coarse space, which provides new insights into the performance of the augmented subspace method. Numerical experiments are finally supplied to verify these new estimate results and the efficiency of our algorithms., Comment: 23 pages, 5 figures. arXiv admin note: text overlap with arXiv:2106.00548, arXiv:2401.04063

This study proposes a class of augmented subspace schemes for the weak Galerkin (WG) finite element method used to solve eigenvalue problems. The augmented subspace is built with the conforming linear finite element space defined on the coarse mesh and the eigenfunction approximations in the WG finite element space defined on the fine mesh. Based on this augmented subspace, solving the eigenvalue problem in the fine WG finite element space can be reduced to the solution of the linear boundary value problem in the same WG finite element space and a low dimensional eigenvalue problem in the augmented subspace. The proposed augmented subspace techniques have the second order convergence rate with respect to the coarse mesh size, as demonstrated by the accompanying error estimates. Finally, a few numerical examples are provided to validate the proposed numerical techniques., Comment: 29 pages, 24c figures

In recent years, quantum computing has entered the Noisy Intermediate-Scale Quantum (NISQ). However, NISQ devices have inherent limitations in terms of connectivity and hardware noise, necessitating the transformation of quantum logic circuits for correct execution on NISQ chips. The synthesis of CNOT circuits considering physical constraints can transform quantum algorithms into low-level quantum circuits, which can be directly executed on physical chips. In the current trend, quantum chip architectures without Hamiltonian paths are gradually replacing architectures with Hamiltonian paths due to their scalability and low-noise characteristics. To this end, this paper addresses the nearest neighbor synthesis of CNOT circuits in the architecture with and without Hamiltonian paths, aiming to enhance the fidelity of the circuits after execution. Firstly, a key-qubit priority mapping model for the general architecture with and without Hamiltonian paths is proposed. Secondly, the initial mapping is further improved by using tabu search to reduce the number of CNOT gates after circuit synthesis and enhance its fidelity. Finally, the noise-aware CNOT circuit nearest neighbor synthesis algorithm for the general architecture is proposed based on the key-qubit priority mapping model. Experimental results show that the proposed method can enhance the fidelity of the CNOT circuit by about 64.7% on a real quantum computing device, achieving a significant optimization effect. Furthermore, the method can be extended to other circuits, thereby improving the overall performance of quantum computing on NISQ devices.

A quantum circuit must be preprocessed before implementing on NISQ devices due to the connectivity constraint. Quantum circuit mapping (QCM) transforms the circuit into an equivalent one that is compliant with the NISQ device's architecture constraint by adding SWAP gates. The QCM problem asks the minimal number of auxiliary SWAP gates, and is NP-complete. The complexity of QCM with fixed parameters is studied in the paper. We give an exact algorithm for QCM, and show that the algorithm runs in polynomial time if the NISQ device's architecture is fixed. If the number of qubits of the quantum circuit is fixed, we show that the QCM problem is NL-complete by a reduction from the undirected shortest path problem. Moreover, the fixed-parameter complexity of QCM is W[1]-hard when parameterized by the number of qubits of the quantum circuit. We prove the result by a reduction from the clique problem. If taking the depth of the quantum circuits and the coupling graphs as parameters, we show that the QCM problem is still NP-complete over shallow quantum circuits, and planar, bipartite and degree bounded coupling graphs.

The quantum circuit mapping approach is an indispensable part of the software stack for the noisy intermediatescale quantum (NISQ) device. It has a significant impact on the reliability of computational tasks on NISQ devices. To improve the overall fidelity of physical circuits, we propose a quantum circuit mapping method based on multi-agent cooperation. This approach considers the Spatio-temporal variation of quantum operation quality on the NISQ device when inserting ancillary operation. It consists of two core components: the qubit placement algorithm and the qubit routing method. The qubit placement algorithm exploits the iterated local search framework to find a desirable initial mapping for the reduced symmetric form of the original circuit. The qubit routing method generates the physical circuit through multi-agent communication and collaboration. Each agent inserts the ancillary gates independently according to its environment state. The quality of the physical circuit evolves according to an information-exchanging mechanism between agents, which combines the local search and global search. To experiment on the benchmark circuits (with hundreds of quantum gates) beyond the capacity of current NISQ devices, we build a noisy simulator with gate error 10x lower than that of the latest NISQ device of IBM. The experimental results confirm the performance of our approach in improving circuit fidelity. Compared with the stateof-the-art method, our method can improve the success rate by 25.86% on average and 95.42% at maximum., Comment: 13 pages, 10 figures