Grover quantum simulation algorithm optimization method based on cloud computing

Abstract

The invention discloses a Grover quantum simulation algorithm optimization method based on cloud computing, and mainly solves the problems of few quantum bits and low simulation efficiency of quantumalgorithm simulation at home and abroad. According to the invention, optimization is carried out for Grover quantum search single iteration unitary operation, an optimization algorithm which greatly saves storage space and remarkably improves unitary operation efficiency is provided, and distributed processing is conducted on large-matrix unitary operation on a cloud computing cluster by utilizingthe advantages of a MapReduce parallel computing model based on Hadoop. The high-performance parallel computing capability provided by the cloud computing platform is fully utilized, the advantages of the cluster architecture are utilized to construct the multi-bit quantum parallel computing model, and the simulation algorithm efficiency is successfully improved.

Description

technical field [0001] The invention relates to the technical field of cloud computing, in particular to an optimization method of a Grover quantum simulation algorithm based on cloud computing. Background technique [0002] The scale of existing quantum computers in the real sense is still relatively small, and quantum computers have not yet moved from the laboratory to practical applications. Therefore, simulating the operation of quantum computers through quantum simulation has become the main method of current quantum theory research. [0003] Currently, jQuantum, a commonly used simulation software for quantum algorithm simulation, supports up to 15 qubits. Although the emulator QCCE developed by K. DeRaedt and others runs on the supercomputer JUGENE of the Jülich Research Center in Germany, it can simulate a maximum of 42-bit quantum algorithms, but the supercomputer JUGENE uses 262144 CPUs and 64TB of storage, not only time overhead It is extremely large, and has ext...

AI Technical Summary

Problems solved by technology

Although this method improves the simulation efficiency to a certain extent, the simulation using GPU still has the problems of high cost of GPU hardware and poor versatility.

[0004] In the current general-purpose technology, the simulation of quantum algorithms at home and abroad can only simulate fewer qubits, and the simulation efficiency is low. Although the performance of simulation can be improved to a certain extent by stacking hardware, the cost will increase geometrically. , so it is difficult to apply widely

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