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Quantum distance-based classifier with distributed knowledge and state recycling

Przemysław Sadowski

Przemysław Sadowski

Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Gliwice, Poland

E-mail Address: [email protected]

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https://doi.org/10.1142/S0219749918400130Cited by:3 (Source: Crossref)

This article is part of the issue:

Special Issue on Quantum Techniques in Machine Learning; Guest Editors: Alessandra Di Pierro and Stefano Mancini

Abstract

In this work, we examine a recently proposed distance-based classification method designed for near-term quantum processing units with limited resources. We study possibilities to reduce the quantum resources without any efficiency decrease. We show that only a part of the information undergoes coherent evolution and this fact allows us to introduce an algorithm with significantly reduced quantum system size requirements. Additionally, considering only partial information at a time, we propose a classification protocol with information distributed among a number of agents. Finally, we show that the information evolution during a measurement can lead to a better solution and that the accuracy of the algorithm can be improved by harnessing the state after the final measurement.

Keywords:

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