QCF, A useful tool for Quantum Neural Network implementation in Matlab

Kishori Radhey, Manu Pratap Singh


Most proposals for quantum neural networks have skipped over the implementation of
the Qubit, superposition, entanglement and measurement in order to be used in
MATLAB environment. Quantum computing uses unitary operators acting on discrete
state vectors. Matlab is a well-known (classical) matrix computing environment, which
makes it well suited for simulating quantum algorithms. The Quantum Computing
Function (QCF) library extends Matlab by adding functions to represent and visualize
common quantum operations. On the other hand a new mathematical model of
computation called Quantum Neural Networks (QNNs) is defined, building on Deutsch's
model of quantum computational network. The Quantum Neural Network (QNN) model
began in order to combine quantum computing with the striking properties of neural
computing. In this paper the use and importance of those functions is illustrated with the
help of few examples. This paper presents a brief overview of QCF that how it can be
useful in Quantum Neural Network simulation.


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DOI: http://dx.doi.org/10.29218/srmsjoms.v3i01.10875

Copyright (c) 2018 SRMS Journal of Mathematical Sciences

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