Design of a Linear Quantum Projection Filter

Peng Zhang; Qing Gao; Jinhu Lv; Daoyi Dong

doi:10.1109/SSCI47803.2020.9308176

Design of a Linear Quantum Projection Filter

Peng Zhang
, Qing Gao
, Jinhu Lv
, Daoyi Dong

School of Automation Science and Electrical Engineering

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In order to reduce the computational cost for online calculation of the quantum filter, in this paper, a linear quantum projection filtering scheme is developed by projecting the time evolution trajectory of quantum system state onto a lower-dimensional linear submanifold spanned by a set of basis matrices. The lower-dimensional submanifold is obtained through an extended singular value decomposition algorithm. Compared with the existing works on quantum projection filtering, the proposed approach requires no prior knowledge on the structure of the submanifold, and thus can be used to deal with general open quantum systems. Simulation results demonstrate that the proposed linear projection filter is able to approximate the high-dimensional quantum filter within acceptable accuracy.

Original language	English
Title of host publication	2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	876-881
Number of pages	6
ISBN (Electronic)	9781728125473
DOIs	https://doi.org/10.1109/SSCI47803.2020.9308176
State	Published - 1 Dec 2020
Event	2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 - Virtual, Online, Australia Duration: 1 Dec 2020 → 4 Dec 2020

Publication series

Name	2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020

Conference

Conference	2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
Country/Territory	Australia
City	Virtual, Online
Period	1/12/20 → 4/12/20

Keywords

linear quantum projection filter
quantum systems
singular value decomposition
stochastic differential equations

Access to Document

10.1109/SSCI47803.2020.9308176

Cite this

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title = "Design of a Linear Quantum Projection Filter",

abstract = "In order to reduce the computational cost for online calculation of the quantum filter, in this paper, a linear quantum projection filtering scheme is developed by projecting the time evolution trajectory of quantum system state onto a lower-dimensional linear submanifold spanned by a set of basis matrices. The lower-dimensional submanifold is obtained through an extended singular value decomposition algorithm. Compared with the existing works on quantum projection filtering, the proposed approach requires no prior knowledge on the structure of the submanifold, and thus can be used to deal with general open quantum systems. Simulation results demonstrate that the proposed linear projection filter is able to approximate the high-dimensional quantum filter within acceptable accuracy.",

keywords = "linear quantum projection filter, quantum systems, singular value decomposition, stochastic differential equations",

author = "Peng Zhang and Qing Gao and Jinhu Lv and Daoyi Dong",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 ; Conference date: 01-12-2020 Through 04-12-2020",

year = "2020",

month = dec,

day = "1",

doi = "10.1109/SSCI47803.2020.9308176",

language = "英语",

series = "2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "876--881",

booktitle = "2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020",

address = "美国",

}

Zhang, P, Gao, Q, Lv, J & Dong, D 2020, Design of a Linear Quantum Projection Filter. in 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020., 9308176, 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020, Institute of Electrical and Electronics Engineers Inc., pp. 876-881, 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020, Virtual, Online, Australia, 1/12/20. https://doi.org/10.1109/SSCI47803.2020.9308176

Design of a Linear Quantum Projection Filter. / Zhang, Peng; Gao, Qing; Lv, Jinhu et al.
2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 876-881 9308176 (2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Design of a Linear Quantum Projection Filter

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AU - Gao, Qing

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AU - Dong, Daoyi

PY - 2020/12/1

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N2 - In order to reduce the computational cost for online calculation of the quantum filter, in this paper, a linear quantum projection filtering scheme is developed by projecting the time evolution trajectory of quantum system state onto a lower-dimensional linear submanifold spanned by a set of basis matrices. The lower-dimensional submanifold is obtained through an extended singular value decomposition algorithm. Compared with the existing works on quantum projection filtering, the proposed approach requires no prior knowledge on the structure of the submanifold, and thus can be used to deal with general open quantum systems. Simulation results demonstrate that the proposed linear projection filter is able to approximate the high-dimensional quantum filter within acceptable accuracy.

AB - In order to reduce the computational cost for online calculation of the quantum filter, in this paper, a linear quantum projection filtering scheme is developed by projecting the time evolution trajectory of quantum system state onto a lower-dimensional linear submanifold spanned by a set of basis matrices. The lower-dimensional submanifold is obtained through an extended singular value decomposition algorithm. Compared with the existing works on quantum projection filtering, the proposed approach requires no prior knowledge on the structure of the submanifold, and thus can be used to deal with general open quantum systems. Simulation results demonstrate that the proposed linear projection filter is able to approximate the high-dimensional quantum filter within acceptable accuracy.

KW - linear quantum projection filter

KW - quantum systems

KW - singular value decomposition

KW - stochastic differential equations

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DO - 10.1109/SSCI47803.2020.9308176

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BT - 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020

Y2 - 1 December 2020 through 4 December 2020

ER -

Design of a Linear Quantum Projection Filter

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