Dr Yanan Liu
Lecturer
School of Engineering
Career Summary
Biography
Dr. Yanan Liu joined the School of Engineering at the University of Newcastle as a Lecturer in March 2024.
She earned her PhD from the University of New South Wales (UNSW) in 2021, with her thesis being awarded a Dean’s Award for Outstanding PhD Theses.
Following the completion of her doctoral studies, Dr. Liu pursued a postdoctoral position at the Okinawa Institute of Science and Technology (OIST) from March 2021 to May 2022. During her time at OIST, she conducted research focusing on time-delayed feedback control design for quantum optical systems. Subsequently, Dr. Liu transitioned to a Research Fellow at the Centre for Quantum Dynamics (CQD) at Griffith University. In this capacity, she continued to explore her research interest in quantum measurement, control, and noise mitigation.
With a strong background in both control engineering and quantum physics, Dr. Liu is dedicated to interdisciplinary research and collaboration.Qualifications
- DOCTOR OF PHILOSOPHY, University of New South Wales
Keywords
- Feedback control
- Learning Control
- Quantum control
Languages
- English (Fluent)
- Mandarin (Mother)
Fields of Research
Code | Description | Percentage |
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400705 | Control engineering | 70 |
510805 | Quantum technologies | 30 |
Professional Experience
UON Appointment
Title | Organisation / Department |
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Lecturer | University of Newcastle School of Engineering Australia |
Academic appointment
Dates | Title | Organisation / Department |
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1/6/2022 - 14/2/2024 | Research Fellow | Griffith University Centre for Quantum Dynamics Australia |
1/3/2021 - 31/5/2022 | Postodoctoral Scholar | Okinawa Institute of Science and Technology Quantum Machines Unit Japan |
Publications
For publications that are currently unpublished or in-press, details are shown in italics.
Journal article (12 outputs)
Year | Citation | Altmetrics | Link | |||||
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2023 |
Liu Y, Munro WJ, Twamley J, 'A quantum ticking self-oscillator using delayed feedback', NEW JOURNAL OF PHYSICS, 25 (2023) [C1]
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2023 |
Cheng X, Lu X-J, Liu Y-N, Kuang S, 'Comparison of differential evolution, particle swarm optimization, quantum-behaved particle swarm optimization, and quantum evolutionary algorithm for preparation of quantum states', CHINESE PHYSICS B, 32 (2023) [C1]
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2023 |
Tonekaboni B, Chantasri A, Song H, Liu Y, Wiseman HM, 'Greedy versus map-based optimized adaptive algorithms for random-telegraph-noise mitigation by spectator qubits', PHYSICAL REVIEW A, 107 (2023) [C1]
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2022 |
Liu Y, Dong D, Petersen IR, Yonezawa H, 'Fault-tolerant H
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2022 |
Li G, Liu Y, Kuang S, Xiang C, 'Approximate bang-bang control assisted rapid switching feedback stabilization for stochastic qubit systems', JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 359 2073-2091 (2022) [C1]
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2022 |
Liu Y, Dong D, Petersen IR, Gao Q, Ding SX, Yokoyama S, Yonezawa H, 'Fault-Tolerant Coherent
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2022 |
Kuang S, Li G, Liu Y, Sun X, Cong S, 'Rapid Feedback Stabilization of Quantum Systems With Application to Preparation of Multiqubit Entangled States', IEEE TRANSACTIONS ON CYBERNETICS, 52 11213-11225 (2022) [C1]
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2021 |
Liu Y, Dong D, Kuang S, Petersen IR, Yonezawa H, 'Two-step feedback preparation of entanglement for qubit systems with time delay', AUTOMATICA, 125 (2021) [C1]
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2020 |
Liu Y, Dong D, Petersen IR, Gao Q, Ding SX, Yonezawa H, 'Coherent
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2019 |
Liu Y, Dong D, Petersen IR, Yonezawa H, 'Filter-Based Feedback Control for a Class of Markovian Open Quantum Systems', IEEE CONTROL SYSTEMS LETTERS, 3 565-570 (2019)
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2017 |
Sun X, Kuang S, Liu Y, Zhou J, Cong S, 'Feedback stabilization of N-dimensional stochastic quantum systems based on bang-bang control', Control Theory and Technology, 15 206-218 (2017) For an N-dimensional quantum system under the influence of continuous measurement, this paper presents a switching control scheme where the control law is of bang-bang type and ac... [more] For an N-dimensional quantum system under the influence of continuous measurement, this paper presents a switching control scheme where the control law is of bang-bang type and achieves asymptotic preparation of an arbitrarily given eigenstate of a non-degenerate and degenerate measurement operator, respectively. In the switching control strategy, we divide the state space into two parts: a set containing a target state, and its complementary set. By analyzing the stability of the stochastic system model under consideration, we design a constant control law and give some conditions that the control Hamiltonian satisfies so that the system trajectories in the complementary set converge to the set which contains the target state. Further, for the case of a non-degenerate measurement operator, we show that the system trajectories in the set containing the target state will automatically converge to the target state via quantum continuous measurement theory; while for the case of a degenerate measurement operator, the corresponding system trajectories will also converge to the target state via the construction of the control Hamiltonians. The convergence of the whole closed-loop systems under the cases of a non-degenerate and a degenerate measurement operator is strictly proved. The effectiveness of the proposed switching control scheme is verified by the simulation experiments on a finite-dimensional angular momentum system and a two-qubit system.
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2017 |
Liu Y, Kuang S, Cong S, 'Lyapunov-Based Feedback Preparation of GHZ Entanglement of
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Show 9 more journal articles |
Conference (3 outputs)
Year | Citation | Altmetrics | Link | |||||
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2022 |
Song C, Liu Y, McManus D, Dong D, 'Learning Control with Evolution Strategy for Inhomogeneous Open Quantum Ensembles', Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics (2022) This paper investigates the application of an evolutionary algorithm, evolution strategy (ES)(mu+lambda) to the control design in several inhomogeneous open quantum ensembles. We ... [more] This paper investigates the application of an evolutionary algorithm, evolution strategy (ES)(mu+lambda) to the control design in several inhomogeneous open quantum ensembles. We apply the ES (mu+lambda) to assist the sampling-based learning control (SLC) technique, by which a set of control signals is designed to drive the inhomogeneous open quantum ensemble to a given target state. We illustrate our algorithm in two-level and four-level inhomogeneous open quantum ensembles. Numerical results show the effectiveness of the proposed control algorithm. The comparison with other evolutionary algorithms such as differential evolution (DE) and genetic algorithm (GA) shows the superiority of our ES (mu+lambda) both in average fidelity and stability. In a four-level open quantum ensemble, for example, the fitness error after optimization using the ES (mu+lambda) is decreased by around 59% compared to DE, and the standard deviation is lowered by about 47%.
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2019 |
Argha A, Su SW, Liu Y, Celler BG, 'Control Allocation Based Sliding Mode Fault Tolerant Control', 2019 AMERICAN CONTROL CONFERENCE (ACC), PA, Philadelphia (2019)
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2019 |
Liu Y, Dong D, Petersen IR, Kuang S, Yonezawa H, 'Feedback preparation of Bell states for two-qubit systems with time delay', 2019 AMERICAN CONTROL CONFERENCE (ACC), PA, Philadelphia (2019)
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Grants and Funding
Summary
Number of grants | 1 |
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Total funding | $53,941 |
Click on a grant title below to expand the full details for that specific grant.
20241 grants / $53,941
Alexander von Humboldt Postdocs$53,941
Funding body: Alexander Von Humboldt Foundation
Funding body | Alexander Von Humboldt Foundation |
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Project Team | Dr. Yanan Liu and Professor Steven X. Ding |
Scheme | Postdoctoral Research Fellowship |
Role | Lead |
Funding Start | 2024 |
Funding Finish | 2025 |
GNo | |
Type Of Funding | External |
Category | EXTE |
UON | N |
Dr Yanan Liu
Position
Lecturer
School of Engineering
College of Engineering, Science and Environment