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International Journal of Modern Physics B

QUANTUM ASSOCIATIVE MEMORY

M. Andrecut, Mazhar Ali

Published May 10, 2003• 12 citations
Publisher

Abstract

The unique characteristic of quantum mechanics may be used in the near future to create a quantum associative memory with a capacity exponential in the number of neurons. In this paper we discuss some quantum computational ideas and algorithms necessary to develop a quantum associative memory.
DOI
10.1142/s0217979203018284

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Abstract This paper discusses an approach to constructing an artificial quantum associative memory (QuAM). The QuAM makes use of two quantum computational algorithms, one for pattern storage and the other for pattern recall. The result is an exponential increase in the capacity of the memory when compared to traditional associative memories such as the Hopfield network. Further, the paper argues for considering pattern recall as a non-unitary process and demonstrates the utility of non-unitary operators for improving the pattern recall performance of the QuAM. 1.
An approach to constructing an artificial quantum associative memory based on entanglement (QuEAM) is discussed. The QuEAM is an exponential increase in the capacity of the memory when compared to classical associative memories such as the Hopfield network. According to the characteristics of amount of entanglement, the study algorithm based on Grover's well-known algorithm is locally magnified the probability amplitude for the qubit. The basic principle of entangled states is discussed. Concrete examples illustrating the properties of the proposed model are also presented.