2018/03/02 by Przemysław Sadowski, Sadowski, Przemysław
Computer Science · Physics and Astronomy · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Physical sciences #Multiagent Systems (cs.MA) #Quantum Physics (quant-ph) #cs.CV #cs.MA #quant-ph
paper · pdf · doi:10.48550/arxiv.1803.00853
17 pages, 2 figures, 4 tables
arxiv created 2018/03/02 · arxiv updated 2018/03/05
In this work we examine recently proposed distance-based classification method designed for near-term quantum processing units with limited resources. We further 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 memory size. 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 accuracy of the algorithm can be improved by harnessing the state after the final measurement.