Simulation of quantum computing on classical supercomputers with tensor-network edge cutting

Simulation of quantum computing on supercomputers is a significant research topic, which plays vital role in algorithm verification, error-tolerant and other applications. Tensor-network contraction based density matrix an important single-amplitude simulation strategy, but it hard to execute the distributed systems. In this paper, we studied problem detail, propose scheme cutting edges undirected graphs. This cuts graphs with large tree width obtain many subgraphs small width, these contracted different cores. The results slave cores are summarized master node, consistent original tensor-network contraction. Thus, can simulate larger scale circuit than single core. Moreover, NP-hard find global optimum edges, search strategy heuristic approach it. order verify effectiveness our scheme, conduct tests approximation optimization (QAOA) Shor's algorithm, 120-qubit three-regular QAOA 4096-core supercomputer, greatly exceeds core 100 qubits.