Generation of accessible sets in the dynamical modelling of quantum network systems

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Yu, Q
Wang, Y
Dong, D
Petersen, IR
Xiang, GY
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2021
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Abstract

In this paper, we consider the dynamical modeling of a class of quantum network systems consisting of qubits. Qubit probes are employed to measure a set of selected nodes of the quantum network systems. For a variety of applications, a state space model is a useful way to model the system dynamics. To construct a state space model for a quantum network system, the major task is to find an accessible set containing all of the operators coupled to the measurement operators. This paper focuses on the generation of a proper accessible set for a given system and measurement scheme. We provide analytic results on simplifying the process of generating accessible sets for systems with a time-independent Hamiltonian. Since the order of elements in the accessible set determines the form of state space matrices, guidance is provided to effectively arrange the ordering of elements in the state vector. Defining a system state according to the accessible set, one can develop a state space model with a special pattern inherited from the system structure. As a demonstration, we specifically consider a typical 1D-chain system with several common measurements, and employ the propo

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IEEE Transactions on Control of Network Systems

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© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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Applied mathematics

Distributed computing and systems software

Electrical engineering

Communications engineering

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Yu, Q; Wang, Y; Dong, D; Petersen, IR; Xiang, GY, Generation of accessible sets in the dynamical modelling of quantum network systems, IEEE Transactions on Control of Network Systems, 2021

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