Polariton lasers emit coherent monochromatic light through a spontaneous emission
process. As a rare example of a system in which Bose–Einstein condensation and …

This manuscript serves a specific purpose: to give readers from fields such as material
science, chemistry, or electronics an overview of implementing a reservoir computing (RC) …

Memristive devices are a class of physical systems with history-dependent dynamics
characterized by signature hysteresis loops in their input–output relations. In the past few …

Reservoir computing is a temporal information processing system that exploits artificial or
physical dissipative dynamics to learn a dynamical system and generate the target time …

Realizing the promise of quantum information processing remains a daunting task given the
omnipresence of noise and error. Adapting noise-resilient classical computing modalities to …

Closed quantum systems exhibit different dynamical regimes, like many-body localization or
thermalization, which determine the mechanisms of spread and processing of information …

The combination of machine learning and quantum computing has emerged as a promising
approach for addressing previously untenable problems. Reservoir computing is an efficient …

Quantum reservoir computing aims at harnessing the rich dynamics of quantum systems for
machine-learning purposes. It can be used for online time series processing while having a …

Time-series processing is a major challenge in machine learning with enormous progress in
the last years in tasks such as speech recognition and chaotic series prediction. A promising …

Quantum reservoir computing (QRC) is a highly promising computational paradigm that
leverages quantum systems as a computational resource for nonlinear information …