Creating Quantum Circuits for Training Perceptron Neural Networks on the Principles of Grover's Algorithm
C. B. Pronin, O. I. Maksimychev, Andrey Vladimirovich Ostroukh +2 more
This paper highlights a practical research of the possibility of forming quantum circuits for training neural networks. The demonstrated quantum circuits were based on the principles of Grover's Search Algorithm. The perceptron was chosen as the architecture for the example neural network. The multilayer perceptron is a popular neural network architecture due to its scalability and applicability for solving a wide range of problems. Large scale neural networks can require significant computing resources for training purposes, therefore Grover’s quantum search algorithm could be used as a way to speed up this process, thanks to its ability of simultaneously processing multiple input values of a given function.
Systems of Signals Generating and Processing in the Field of on Board Communications•Mar 15, 2022•10 citations