Image retrieval method and device based on quantum Grover algorithm and medium

Abstract

The invention provides an image retrieval method and device based on a quantum Grover algorithm and a medium. The method specifically comprises the following steps: S1, acquiring a feature vector of an image to be retrieved; S2, calculating the distance between the feature vector and each standard feature vector in a standard database, wherein each standard feature vector corresponds to a standard image; and S3, based on a quantum Grover algorithm, determining a standard image corresponding to the standard feature vector with the shortest distance as an image retrieval result. According to the method, whether the currently obtained system state solution of the quantum system is the target image to be searched or not is measured and verified, so that the purpose of using less iterative operators is achieved, and the image retrieval efficiency is improved.

Description

technical field [0001] The present disclosure relates to the field of quantum computing, in particular to an image retrieval method, device and medium based on a quantum Grover algorithm. Background technique [0002] Quantum computing is a calculation method that combines the principles of quantum mechanics with classical computing science. It uses the state of microscopic particles to process and store information, and can realize parallel computing. The basic principle of this method is: firstly, the initial state of the information should be prepared, and then the processing and storage of the information should be completed by using the properties of state superposition, entanglement and interference in quantum mechanics, and finally, the measurement system should be used to measure the established quantum system to obtain the required information. Among them, the principle of quantum superposition state can store 2n information in n qubits, so that the quantum system ...

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Problems solved by technology

When M>N / 4, the number of iterations is not In order to search for the target image with a higher probability, it is necessary to increase the multiple applications of the G iteration operator. At this time, the probability of obtaining the target solution can be greatly increased, but at the same time, the implementation of the G iteration operator in Grover’s quantum circuit is quite Complicated, if more G iterative algorithms are called for each calculation, the quantum circuit of the entire algorithm will be more complicated, so for problems with large databases, this will undoubtedly waste computing resources and increase the complexity of calculations

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