Quantum probabilistic associative memory architecture

Alpha-Beta Hybrid Quantum Associative Memory Using Hamming Distance

“…By comparison, for the proposed Alpha-Beta HQAM model, there was a completely correct retrieval for six of the ten letters, while they did not retrieve any correctly, and with respect to the others it is noticeable at a glance that there are fewer incorrect pixels, so it can be said that, in general, the proposed model in the retrieval is better than the one reported in [ 24 ] It should be noted that the retrieval phase proposed in the new model is less complex to implement, since only the Quantum Hamming Distance algorithm is used, compared to the others which need three algorithms, increasing the number of quantum gates and more qubits needed…”

“…In addition, the results were compared with those obtained in Neto et al [ 24 ], they designed a quantum associative memory, where the retrieval phase consists of three parts: Exchange, Quantum Fourier Transform and Grover’s algorithm. To test their method, they used a dataset of 10 letters as shown in Figure 7 , in order to directly compare the result with them, a variant of the letters dataset was created to match the letter J.…”

“…In Figure 8 , item (a) shows the obtained result in [ 24 ], item (b) shows the obtained results by the proposed Alpha-Beta HQAM model.…”

“… ( a ) Figure designed from the results obtained in [ 24 ]. ( b ) The obtained results by the proposed Alpha-Beta HQAM model.…”

Parametric Probabilistic Quantum Memory

“…Quantum associative memories have been used to perform classification tasks in several works [27,17,23,4,28,29,30]. In [29] Grover's algorithm and a quantum associative memory based on it are used to perform classification tasks in a toy dataset representing orange and apples with 3-qubit patterns.…”