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Discovery Projects - Grant ID: DP130101658

Discovery Projects - Grant ID: DP130101658
ARC | Discovery Projects
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  • Several recent developments in estimation and robust control of quantum systems

    Dong, Daoyi; Wang, Yuanlong (2018)
    Projects: ARC | Discovery Projects - Grant ID: DP130101658 (DP130101658)
    This paper summarizes several recent developments in the area of estimation and robust control of quantum systems and outlines several directions for future research. Quantum state tomography via linear regression estimation and adaptive quantum state estimation are introduced and a Hamiltonian identification algorithm is outlined. Two quantum robust control approaches including sliding mode control and sampling-based learning control are illustrated.

    Fault Tolerant Quantum Filtering and Fault Detection for Quantum Systems

    Gao, Qing; Dong, Daoyi; Petersen, Ian R. (2015)
    Projects: ARC | Discovery Projects - Grant ID: DP130101658 (DP130101658)
    This paper aims to determine the fault tolerant quantum filter and fault detection equation for a class of open quantum systems coupled to a laser field that is subject to stochastic faults. In order to analyze this class of open quantum systems, we propose a quantum-classical Bayesian inference method based on the definition of a so-called quantum-classical conditional expectation. It is shown that the proposed Bayesian inference approach provides a convenient tool to simultaneously derive t...

    Robust Learning Control Design for Quantum Unitary Transformations

    Wu, Chengzhi; Qi, Bo; Chen, Chunlin; Dong, Daoyi (2018)
    Projects: ARC | Discovery Projects - Grant ID: DP130101658 (DP130101658)
    Robust control design for quantum unitary transformations has been recognized as a fundamental and challenging task in the development of quantum information processing due to unavoidable decoherence or operational errors in the experimental implementation of quantum operations. In this paper, we extend the systematic methodology of sampling-based learning control (SLC) approach with a gradient flow algorithm for the design of robust quantum unitary transformations. The SLC approach first use...

    Full reconstruction of a 14-qubit state within four hours

    Hou, Zhibo; Zhong, Han-Sen; Tian, Ye; Dong, Daoyi; Qi, Bo; Li, Li; Wang, Yuanlong; Nori, Franco; Xiang, Guo-Yong; Li, Chuan-Feng; Guo, Guang-Can (2016)
    Projects: ARC | Discovery Projects - Grant ID: DP130101658 (DP130101658)
    Full quantum state tomography (FQST) plays a unique role in the estimation of the state of a quantum system without \emph{a priori} knowledge or assumptions. Unfortunately, since FQST requires informationally (over)complete measurements, both the number of measurement bases and the computational complexity of data processing suffer an exponential growth with the size of the quantum system. A 14-qubit entangled state has already been experimentally prepared in an ion trap, and the data process...

    Real-time Information, Uncertainty and Quantum Feedback Control

    Qi, Bo; Dong, Daoyi; Chen, Chunlin; Liu, Lijun; Xi, Zairong (2014)
    Projects: ARC | Discovery Projects - Grant ID: DP130101658 (DP130101658)
    Feedback is the core concept in cybernetics and its effective use has made great success in but not limited to the fields of engineering, biology, and computer science. When feedback is used to quantum systems, two major types of feedback control protocols including coherent feedback control (CFC) and measurement-based feedback control (MFC) have been developed. In this paper, we compare the two types of quantum feedback control protocols by focusing on the real-time information used in the f...

    Recursively Adaptive Quantum State Tomography: Theory and Two-qubit Experiment

    Qi, Bo; Hou, Zhibo; Wang, Yuanlong; Dong, Daoyi; Zhong, Han-Sen; Li, Li; Xiang, Guo-Yong; Wiseman, Howard M.; Li, Chuan-Feng; Guo, Guang-Can (2015)
    Projects: ARC | Discovery Projects - Grant ID: DP130101658 (DP130101658)
    Adaptive techniques have important potential for wide applications in enhancing precision of quantum parameter estimation. We present a recursively adaptive quantum state tomography (RAQST) protocol for finite dimensional quantum systems and experimentally implement the adaptive tomography protocol on two-qubit systems. In this RAQST protocol, an adaptive measurement strategy and a recursive linear regression estimation algorithm are performed. Numerical results show that our RAQST protocol c...

    Realization of mutually unbiased bases for a qubit with only one wave plate: Theory and experiment

    Hou, Zhibo; Xiang, Guoyong; Dong, Daoyi; Li, Chuan-Feng; Guo, Guang-Can (2015)
    Projects: ARC | Discovery Projects - Grant ID: DP130101658 (DP130101658)
    We consider the problem of implementing mutually unbiased bases (MUB) for a polarization qubit with only one wave plate, the minimum number of wave plates. We show that one wave plate is sufficient to realize two MUB as long as its phase shift (modulo $360^\circ$) ranges between $45^\circ$ and $315^\circ$. {It can realize} three MUB (a complete set of MUB for a qubit) if the phase shift of the wave plate is within $[111.5^\circ, 141.7^\circ]$ or its symmetric range with respect to 180$^\circ$...

    Distributed sampled-data control of nonholonomic multi-robot systems with proximity networks

    Liu, Zhixin; Wang, Lin; Wang, Jinhuan; Dong, Daoyi; Hu, Xiaoming (2016)
    Projects: ARC | Discovery Projects - Grant ID: DP130101658 (DP130101658)
    This paper considers the distributed sampled-data control problem of a group of mobile robots connected via distance-induced proximity networks. A dwell time is assumed in order to avoid chattering in the neighbor relations that may be caused by abrupt changes of positions when updating information from neighbors. Distributed sampled-data control laws are designed based on nearest neighbour rules, which in conjunction with continuous-time dynamics results in hybrid closed-loop systems. For un...

    Modelling and Control of Quantum Measurement Induced Backaction in Double Quantum Dots

    Quantum measurements disturb the quantum system being measured, and this is known as measurement-induced backaction. In this work, we consider a double quantum dot monitored by a nearby quantum point contact where the measurement-induced backaction plays an important role. Taking advantage of the quantum master equation approach, we calculate the tunnelling current, and propose a simple feedbackcontrol law to realize and stabilize the tunnelling current. Theoretical analysis and numerical sim...

    Fidelity-based Probabilistic Q-learning for Control of Quantum Systems

    Chen, Chunlin; Dong, Daoyi; Li, Han-Xiong; Chu, Jian; Tarn, Tzyh-Jong (2018)
    Projects: ARC | Discovery Projects - Grant ID: DP130101658 (DP130101658)
    The balance between exploration and exploitation is a key problem for reinforcement learning methods, especially for Q-learning. In this paper, a fidelity-based probabilistic Q-learning (FPQL) approach is presented to naturally solve this problem and applied for learning control of quantum systems. In this approach, fidelity is adopted to help direct the learning process and the probability of each action to be selected at a certain state is updated iteratively along with the learning process...
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