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Basic quantum circuits for classification and approximation tasks

Wiśniewska Joanna, Sawerwain Marek, Obuchowicz Andrzej

International Journal of Applied Mathematics and Computer Science

2020

Vol. 30, no. 4

733--744

We discuss a quantum circuit construction designed for classification. The circuit is built of regularly placed elementary quantum gates, which implies the simplicity of the presented solution. The realization of the classification task is possible after the procedure of supervised learning which constitutes parameter optimization of Pauli gates. The process of learning can be performed by a physical quantum machine but also by simulation of quantum computation on a classical computer. The parameters of Pauli gates are selected by calculating changes in the gradient for different sets of these parameters. The proposed solution was successfully tested in binary classification and estimation of basic non-linear function values, e.g., the sine, the cosine, and the tangent. In both the cases, the circuit construction uses one or more identical unitary operations, and contains only two qubits and three quantum gates. This simplicity is a great advantage because it enables the practical implementation on quantum machines easily accessible in the nearest future.

Efektywnie symulowalne układy quditowe

Gielerak R., Ratajczak P.

Pomiary Automatyka Kontrola

2007

R. 53, nr 5

51-53

Przedstawiono wyniki symulacji losowych obliczeń kwantowych zrealizowanych za pomocą obwodów unitarnych klasy CHP dla obwodów quditowych. Potwierdzone teoretyczne oszacowania dotyczące złożoności obliczeniowej symulacji tego typu układów kwantowych. Symulacje przeprowadzono poprzez implementacje w języku C algorytmu Aaronsona-Gottesmana .

Simulations of random quantum calculations schemes realized within the class of CHP circuits are being performed and the results of them are being presented. In particular the theoretical estimations of computational complexity of the systems analyzed are being confirmed. The C language version of the Aaronson-Gottesman algorithm has been used for the analyzed simulation process.