Quantum reservoir computing in finite dimensions

Rodrigo Martínez-Peña and Juan-Pablo Ortega
Phys. Rev. E 107, 035306 – Published 24 March 2023

Abstract

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.

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  • Received 2 December 2022
  • Revised 7 February 2023
  • Accepted 13 March 2023

DOI:https://doi.org/10.1103/PhysRevE.107.035306

©2023 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & TechnologyInterdisciplinary PhysicsNonlinear Dynamics

Authors & Affiliations

Rodrigo Martínez-Peña1,* and Juan-Pablo Ortega2,†

  • 1Instituto de Física Interdisciplinar y Sistemas Complejos, CSIC, Campus Universitat de les Illes Balears, 07122 Palma de Mallorca, Spain
  • 2Division of Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637371

  • *rmartinez@ifisc.uib-csic.es
  • juan-pablo.ortega@ntu.edu.sg

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Issue

Vol. 107, Iss. 3 — March 2023

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