From quantum feature maps to quantum reservoir computing: Perspectives and applications

• ArXiv number: 2510.01797

We explore the interplay between two emerging paradigms: reservoir computing and quantum computing. We observe how quantum systems featuring beyond-classical correlations and vast computational spaces can serve as non-trivial, experimentally viable reservoirs for typical tasks in machine learning. With a focus on neutral atom quantum processing units, we describe and exemplify a novel quantum reservoir computing (QRC) workflow. We conclude exploratively discussing the main challenges ahead, whilst arguing how QRC can offer a natural candidate to push forward reservoir computing applications.

Related research projects

CoQuSy

Complex Quantum Systems: machine learning, thermodynamics, and emergent phenomena

I.P.: Gian Luca Giorgi, Gonzalo Manzano, Roberta Zambrini

CoQuSy is a coordinated project and joins all the researchers at IFISC (belonging either to CSIC or UIB) working in the common line of complex quantum systems. The coordination is motivated by …

CoQuSy-CSIC

Complex Quantum Systems: machine learning, thermodynamics, and emergent phenomena

I.P.: Gonzalo Manzano, Roberta Zambrini

CoQuSy is a coordinated project and joins all the researchers at IFISC (belonging either to CSIC or UIB) working in the common line of complex quantum systems. The coordination is motivated by …

CoQuSy-UIB

Complex Quantum Systems: machine learning, thermodynamics, and emergent phenomena

I.P.: Gian Luca Giorgi

CoQuSy is a coordinated project and joins all the researchers at IFISC (belonging either to CSIC or UIB) working in the common line of complex quantum systems. The coordination is motivated by …

Quantum Spain

Quantum Spain

I.P.: Roberta Zambrini

Reserach topic: QUANTUM MACHINE LEARNING Convenio en el BOE: https://www.boe.es/diario_boe/txt.php?id=BOE-A-2023-18333 IFISC participation both as UIB and as CSIC (2 separate budgets)