Quantum distance-based classifier with distributed knowledge and state recycling
| Author | Sadowski P. |
|---|---|
| Title | Quantum distance-based classifier with distributed knowledge and state recycling |
| Journal | International Journal of Quantum Information |
| Year | 2018 |
| Status | Published |
| Volume | 16 |
| Issue | 8 |
| DOI | 10.1142/S0219749918400130 |
| URL | https://doi.org/10.1142/S0219749918400130 |
| Abstract | <p>In this work we examine recently proposed distance-based clas-<br /> sification method designed for near-term quantum processing units<br /> with limited resources. We further study possibilities to reduce the<br /> quantum resources without any efficiency decrease. We show that<br /> only a part of the information undergoes coherent evolution and this<br /> fact allows us to introduce an algorithm with significantly reduced<br /> quantum memory size. Additionally, considering only partial infor-<br /> mation at a time, we propose a classification protocol with information<br /> distributed among a number of agents. Finally, we show that the infor-<br /> mation evolution during a measurement can lead to a better solution<br /> and that accuracy of the algorithm can be improved by harnessing the<br /> state after the final measurement.</p> |