Abstract
Artificial neural networks are one of the building blocks of artificial intelligence. And their quantum versions have a superior performance possibility. This work proposes an open quantum neuron as a unit structure of an open quantum network and demonstrates that it can be activated through the connected reservoir. It's been shown that the model successfully classifies the temperature data coming from distinct quantum thermal reservoirs and exhibits an activation through the reservoir parameters. Also, a possible physical version of the model operating in the microwave regime discussed to be three orders of magnitude faster than the classical classifiers.
Original language | English |
---|---|
Article number | 126442 |
Journal | Physics Letters, Section A: General, Atomic and Solid State Physics |
Volume | 384 |
Issue number | 23 |
DOIs | |
Publication status | Published - 17 Aug 2020 |
Bibliographical note
Publisher Copyright:© 2020 Elsevier B.V.
Keywords
- Quantum neuron
- Quantum thermalization
- Squeezed reservoir
- Superconducting circuits