Quantum reservoir processing

The concurrent rise of artificial intelligence and quantum information poses an opportunity for creating interdisciplinary technologies like quantum neural networks. Quantum reservoir processing, introduced here, is a platform for quantum information processing developed on the principle of reservoi...

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Bibliographic Details
Published innpj quantum information Vol. 5; no. 1
Main Authors Ghosh, Sanjib, Opala, Andrzej, Matuszewski, Michał, Paterek, Tomasz, Liew, Timothy C. H.
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 29.04.2019
Nature Publishing Group
Subjects
639/766/119
639/766/259
639/766/483/481
Artificial intelligence
Classical and Quantum Gravitation
Entropy
Information processing
Neural networks
Physics
Physics and Astronomy
Quantum Computing
Quantum Field Theories
Quantum Information Technology
Quantum Physics
Quantum theory
Relativity Theory
Spintronics
String Theory
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Summary:The concurrent rise of artificial intelligence and quantum information poses an opportunity for creating interdisciplinary technologies like quantum neural networks. Quantum reservoir processing, introduced here, is a platform for quantum information processing developed on the principle of reservoir computing that is a form of an artificial neural network. A quantum reservoir processor can perform qualitative tasks like recognizing quantum states that are entangled as well as quantitative tasks like estimating a nonlinear function of an input quantum state (e.g., entropy, purity, or logarithmic negativity). In this way, experimental schemes that require measurements of multiple observables can be simplified to measurement of one observable on a trained quantum reservoir processor.
ISSN:2056-6387
2056-6387
DOI:10.1038/s41534-019-0149-8