Dynamical phase transitions in quantum reservoir computing
Martínez-Peña, Rodrigo; Giorgi, Gian Luca; Nokkala, Johannes; Soriano, Miguel C.; Zambrini, Roberta
Physical Review Letters 127, 100502 (1-7) (2021)
Physical Review Letters 127, 100502 (1-7) (2021)
Closed quantum systems exhibit different dynamical regimes, like Many-Body Localization or thermalization, which determine the mechanisms of spread and processing of information. Here we address the impact of these dynamical phases in quantum reservoir computing, an unconventional computing paradigm recently extended into the quantum regime that exploits dynamical systems to solve nonlinear and temporal tasks. We establish that the thermal phase is naturally adapted to the requirements of quantum reservoir computing and report an increased performance at the thermalization transition. Uncovering the underlying physical mechanisms behind optimal information processing capabilities of spin networks is essential for future experimental implementations and provides a new perspective on dynamical phases.
Additional files
Related research projects
QUAREC
Machine learning with quantum reservoir computing
P.I.: Roberta Zambrini
Project funded by the government of the Balearic Islands with the goal of extending Reservoir Computing into the quantum domain. The project is mainly theoretical/numerical, but also deals with the identification of …
QuaResC
Quantum machine learning using reservoir computing
P.I.: Miguel C. Soriano, Roberta Zambrini
The QuaResC project engages in a new collaboration UIB and CSIC researchers at IFISC with the objective to address an interdisciplinary topic between artificial intelligence and quantum physics: quantum machine learning using …
QuaResC (CSIC)
Quantum machine learning using reservoir computing
P.I.: Roberta Zambrini
The QuaResC project engages in a new collaboration UIB and CSIC researchers at IFISC with the objective to address an interdisciplinary topic between artificial intelligence and quantum physics: quantum machine learning using …
QuaResC (UIB)
Quantum machine learning using reservoir computing
P.I.: Miguel C. Soriano
The QuaResC project engages in a new collaboration UIB and CSIC researchers at IFISC with the objective to address an interdisciplinary topic between artificial intelligence and quantum physics: quantum machine learning using …
Related News
Dynamical phase transitions in quantum Reservoir Computing
Sept. 3, 2021
Information can be processed by physical, chemical and biological systems with a major example being our brain. In this context, quantum reservoir computing is a promising approach in the fields of complex systems and artificial neural networks characterized by a …
Transicions dinàmiques de fase en computació quàntica de reservoris (quantum reservoir computing)
Sept. 3, 2021
La informació pot ser processada per sistemes físics, químics i biològics, i el cervell humà n’és un exemple paradigmàtic. En aquest context, la computació quàntica de reservoris és un enfocament prometedor en els camps dels sistemes complexos i les xarxes …
Transiciones dinámicas de fase en Reservoir Computing cuántico
Sept. 3, 2021
La información puede ser procesada por sistemas físicos, químicos y biológicos, siendo nuestro cerebro un ejemplo paradigmático de ello. En este contexto, el Reservoir Computing cuántico es un enfoque prometedor en los campos de los sistemas complejos y las redes …