Abstract: A quantum circuit generation method includes determining a reference state of a target molecule and N excitations states corresponding to the reference state, where N is a positive integer greater than or equal to 1; determining M excitations states from the N excitations states based on an attribute of the reference state and attributes of the N excitations states, where M is a positive integer greater than or equal to 1 and less than or equal to N; and generating a first quantum circuit based on the M excitations states such as to improve computation efficiency and to reduce resource consumption.

Abstract: Example embodiments of the present disclosure relate to a solution for ph-AFQMC with direct product multi-Slater determinants trial. Multiple active spaces of a molecular system may be obtained and multiple coefficient tensors may be determined respectively. A composite coefficient tensor may be determined based on a tensor product of the multiple coefficient tensors of the multiple active spaces, and a trial wave function may be further determined based on the composite coefficient tensor and a cutoff value. As such, the multiple coefficient tensors for the multiple active spaces may be determined, thus the computation can be reduced. Additionally, since a cutoff value is used, the composite coefficient tensor is a sparse tensor and the number of Slater determinants may be reduced. Further, the determined trial wave function may be further used in a ph-AFQMC algorithm, and a balance between accuracy and efficiency may be achieved.

Abstract: The present disclosure relates to the field of quantum computing, and in particular to simulating quantum circuits with a quantum simulator. The disclosure presents a processor for a quantum simulator. The processor is configured to perform a local search algorithm to determine a plurality of contraction expressions suitable to contract a respective tensor network into a determined contracted tensor network. The processor is further configured to determine, for each contraction expression, a contraction cost for contracting the respective tensor network based on a cost function, and to select the contraction expression with the lowest contraction cost to contract each tensor network into the determined contracted tensor network. The cost function is based on three parameters, which respectively indicate a required memory amount, a computational complexity, and a number of read-write operations required for contracting the respective tensor network into the determined contracted tensor network.

Abstract: This application relates to the quantum computer field, and provides a quantum circuit generation method and a related device. The method includes: determining a reference state of a target molecule and N excitations states corresponding to the reference state, where N is a positive integer greater than or equal to 1; determining M excitations states from the N excitations states based on an attribute of the reference state and attributes of the N excitations states, where M is a positive integer greater than or equal to 1 and less than or equal to N; and generating a first quantum circuit based on the M excitations states. The foregoing technical solution can reduce a quantity of excitations states used to generate the first quantum circuit, thereby reducing a depth of the quantum circuit, reducing a quantity of quantum gates and a quantity of layers, improving computation efficiency, and reducing resource consumption.