Quantum reservoir computing in finite dimensions

Most existing results in the analysis of quantum reservoir computing (QRC) systems with classical inputs have been obtained using the density matrix formalism. This paper shows that alternative representations can provide better insight when dealing with design and assessment questions. More explici...

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Main Authors: Martínez-Peña, Rodrigo, Ortega, Juan-Pablo
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/169944
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1699442023-08-21T15:42:05Z Quantum reservoir computing in finite dimensions Martínez-Peña, Rodrigo Ortega, Juan-Pablo School of Physical and Mathematical Sciences Science::Physics Science::Mathematics Bloch Vectors Density Matrix Approach Most existing results in the analysis of quantum reservoir computing (QRC) systems with classical inputs have been obtained using the density matrix formalism. This paper shows that alternative representations can provide better insight when dealing with design and assessment questions. More explicitly, system isomorphisms are established that unify the density matrix approach to QRC with the representation in the space of observables using Bloch vectors associated with Gell-Mann bases. It is shown that these vector representations yield state-affine systems previously introduced in the classical reservoir computing literature and for which numerous theoretical results have been established. This connection is used to show that various statements in relation to the fading memory property (FMP) and the echo state property (ESP) are independent of the representation and also to shed some light on fundamental questions in QRC theory in finite dimensions. In particular, a necessary and sufficient condition for the ESP and FMP to hold is formulated using standard hypotheses, and contractive quantum channels that have exclusively trivial semi-infinite solutions are characterized in terms of the existence of input-independent fixed points. Published version R.M.-P. and J.-P.O. acknowledge partial financial support from the Swiss National Science Foundation (Grant No. 200021 175801/1). R.M.-P. acknowledges the Spanish State Research Agency for support through the Severo Ochoa and María de Maeztu Program for Centers and Units of Excellence in R&D (Grant No. MDM-2017-0711) and through the QUARESC project (Projects No. 2019-109094GB-C21 and 2019-109094GBC22/AEI/10.13039/501100011033). Part of this work was funded by MICINN/AEI/FEDER and the University of the Balearic Islands through a predoctoral fellowship (Grant No. MDM-2017-0711-18-1) for R.M.-P. 2023-08-15T08:04:24Z 2023-08-15T08:04:24Z 2023 Journal Article Martínez-Peña, R. & Ortega, J. (2023). Quantum reservoir computing in finite dimensions. Physical Review E, 107(3-2), 035306-1-035306-16. https://dx.doi.org/10.1103/PhysRevE.107.035306 2470-0045 https://hdl.handle.net/10356/169944 10.1103/PhysRevE.107.035306 37072987 2-s2.0-85151336162 3-2 107 035306-1 035306-16 en Physical Review E © 2023 American Physical Society. All rights reserved. This paper was published in Physical Review E and is made available with permission of American Physical Society. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Physics
Science::Mathematics
Bloch Vectors
Density Matrix Approach
spellingShingle Science::Physics
Science::Mathematics
Bloch Vectors
Density Matrix Approach
Martínez-Peña, Rodrigo
Ortega, Juan-Pablo
Quantum reservoir computing in finite dimensions
description Most existing results in the analysis of quantum reservoir computing (QRC) systems with classical inputs have been obtained using the density matrix formalism. This paper shows that alternative representations can provide better insight when dealing with design and assessment questions. More explicitly, system isomorphisms are established that unify the density matrix approach to QRC with the representation in the space of observables using Bloch vectors associated with Gell-Mann bases. It is shown that these vector representations yield state-affine systems previously introduced in the classical reservoir computing literature and for which numerous theoretical results have been established. This connection is used to show that various statements in relation to the fading memory property (FMP) and the echo state property (ESP) are independent of the representation and also to shed some light on fundamental questions in QRC theory in finite dimensions. In particular, a necessary and sufficient condition for the ESP and FMP to hold is formulated using standard hypotheses, and contractive quantum channels that have exclusively trivial semi-infinite solutions are characterized in terms of the existence of input-independent fixed points.
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Martínez-Peña, Rodrigo
Ortega, Juan-Pablo
format Article
author Martínez-Peña, Rodrigo
Ortega, Juan-Pablo
author_sort Martínez-Peña, Rodrigo
title Quantum reservoir computing in finite dimensions
title_short Quantum reservoir computing in finite dimensions
title_full Quantum reservoir computing in finite dimensions
title_fullStr Quantum reservoir computing in finite dimensions
title_full_unstemmed Quantum reservoir computing in finite dimensions
title_sort quantum reservoir computing in finite dimensions
publishDate 2023
url https://hdl.handle.net/10356/169944
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