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Alpha-Beta Hybrid Quantum Associative Memory Using Hamming Distance
Authors:Angeles Alejandra Sá  nchez-Manilla,Itzamá    pez-Yá  ñ  ez,Guo-Hua Sun
Abstract:This work presents a quantum associative memory (Alpha-Beta HQAM) that uses the Hamming distance for pattern recovery. The proposal combines the Alpha-Beta associative memory, which reduces the dimensionality of patterns, with a quantum subroutine to calculate the Hamming distance in the recovery phase. Furthermore, patterns are initially stored in the memory as a quantum superposition in order to take advantage of its properties. Experiments testing the memory’s viability and performance were implemented using IBM’s Qiskit library.
Keywords:quantum associative memory   hamming distance   quantum machine learning   pattern recognition   Alpha-Beta associative model
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