Year: 2020
Type: article
Abstract: Reservoir computing is a machine learning paradigm that exploits nonlinear dissipative dynamical systems for temporal information processing, and can be combined with quantum computing to form quantum reservoir computers. This study proposes a class of quantum reservoir computers that can be implemented on noisy intermediate-scale quantum (NISQ) computers and possesses the properties required to be reservoir computers, especially universality. Efficient implementation and proof-of-principle demonstration on several cloud-based IBM superconducting quantum devices suggest that the proposed scheme could lead to promising applications of NISQ computers.
Source: Physical Review Applied
Authors: Jiayin Chen, Hendra I. Nurdin, Naoki Yamamoto
Institutions: Keio University, UNSW Sydney
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Award: G3036717327
OpenAlex ID: W3001926289