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Research Article | Open Access

Transfer functions of non-Markovian linear quantum feedback networks

Re-Bing Wu1( )Tzyh-Jong Tarn2
Center for Networked and Intelligent Systems, Department of Automation, Tsinghua University, Beijing 100084, China
Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
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Abstract

Enabled by rapidly developing quantum technologies, it is possible to network quantum systems at a much larger scale in the near future. To deal with non-Markovian dynamics that is prevalent in solid-state devices, we propose a general transfer function based framework for modeling linear quantum networks, in which signal flow graphs are applied to characterize the network topology by flow of quantum signals. We define a noncommutative ring D and use its elements to construct Hamiltonians, transformations and transfer functions for both active and passive systems. The signal flow graph obtained for direct and indirect coherent quantum feedback systems clearly show the feedback loop via bidirectional signal flows. Importantly, the transfer function from input to output field is derived for non-Markovian quantum systems with colored inputs, from which the Markovian input-output relation can be easily obtained as a limiting case. Moreover, the transfer function possesses a symmetry structure that is analogous to the well-known scattering transformation in Schrödinger picture. Finally, we show that these transfer functions can be integrated to build complex feedback networks via interconnections, serial products and feedback, which may include either direct or indirect coherent feedback loops, and transfer functions between quantum signal nodes can be calculated by the Riegle’s matrix gain rule. The theory paves the way for modeling, analyzing and synthesizing non-Markovian linear quantum feedback networks in the frequency-domain.

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Cybernetics and Intelligence
Article number: 9390005

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Cite this article:
Wu R-B, Tarn T-J. Transfer functions of non-Markovian linear quantum feedback networks. Cybernetics and Intelligence, 2026, 1(1): 9390005. https://doi.org/10.26599/CAI.2024.9390005

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Received: 02 January 2023
Revised: 04 December 2023
Accepted: 05 December 2023
Published: 07 April 2026
© The author(s) 2026.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0, http://creativecommons.org/licenses/by/4.0/).