By Professor Daoyi Dong

Preprints

Selim A; Mo H; Pota H; Dong D, 2024, Adaptive BESS and Grid Setpoints Optimization: A Model-Free Framework for Efficient Battery Management under Dynamic Tariff Pricing, http://dx.doi.org/10.48550/arxiv.2408.09989

Liu Y-H; Zeng Y; Tan Q-S; Dong D; Nori F; Liao J-Q, 2024, Optimal control of linear Gaussian quantum systems via quantum learning control, http://dx.doi.org/10.48550/arxiv.2406.05597

Ma H; Mooney GJ; Petersen IR; Hollenberg LCL; Dong D, 2023, Quantum autoencoders using mixed reference states, http://dx.doi.org/10.48550/arxiv.2309.15582

Liu Y; Dong D; Petersen IR; Yonezaw H, 2023, Fault-tolerant $H^\infty$ control for optical parametric oscillators with pumping fluctuations, http://dx.doi.org/10.48550/arxiv.2307.14583

Liu Y; Dong D; Kuang S; Petersen IR; Yonezawa H, 2023, Two-step feedback preparation of entanglement for qubit systems with time delay, http://dx.doi.org/10.48550/arxiv.2307.14599

Bao L; Qi B; Nori F; Dong D, 2023, Exponential sensitivity revival of noisy non-Hermitian quantum sensing with two-photon drives, http://dx.doi.org/10.48550/arxiv.2303.16575

Shindi O; Yu Q; Girdhar P; Dong D, 2023, Model-free Quantum Gate Design and Calibration using Deep Reinforcement Learning, http://dx.doi.org/10.48550/arxiv.2302.02371

Fan L-B; Shu C-C; Dong D; He J; Henriksen NE; Nori F, 2022, Quantum Coherent Control of a Single Molecular-Polariton Rotation, http://dx.doi.org/10.48550/arxiv.2212.11649

Jiang C; Pan Y; Wu Z-G; Gao Q; Dong D, 2022, Robust optimization for quantum reinforcement learning control using partial observations, http://dx.doi.org/10.48550/arxiv.2206.14420

Wang Z; Chen C; Dong D, 2022, A Dirichlet Process Mixture of Robust Task Models for Scalable Lifelong Reinforcement Learning, http://dx.doi.org/10.48550/arxiv.2205.10787

Xie D; Wang Z; Chen C; Dong D, 2022, Depthwise Convolution for Multi-Agent Communication with Enhanced Mean-Field Approximation, http://dx.doi.org/10.48550/arxiv.2203.02896

Dong D; Petersen IR, 2022, Quantum estimation, control and learning: opportunities and challenges, http://dx.doi.org/10.48550/arxiv.2201.05835

Ma H; Dong D; Petersen IR; Huang C-J; Xiang G-Y, 2021, On how neural networks enhance quantum state tomography with constrained measurements, http://dx.doi.org/10.48550/arxiv.2111.09504

Li Y; Aghvami AH; Dong D, 2021, Path Planning for Cellular-Connected UAV: A DRL Solution with Quantum-Inspired Experience Replay, http://dx.doi.org/10.48550/arxiv.2108.13184

Chen Y; Pan Y; Dong D, 2021, Residual Tensor Train: A Quantum-inspired Approach for Learning Multiple Multilinear Correlations, http://dx.doi.org/10.48550/arxiv.2108.08659

Bao L; Qi B; Dong D; Nori F, 2021, Fundamental limits for reciprocal and non-reciprocal non-Hermitian quantum sensing, http://dx.doi.org/10.48550/arxiv.2104.10822

Dong D, 2021, Learning Control of Quantum Systems, http://dx.doi.org/10.48550/arxiv.2101.07461

Ma H; Dong D; Ding SX; Chen C, 2020, Curriculum-based Deep Reinforcement Learning for Quantum Control, http://dx.doi.org/10.48550/arxiv.2012.15427

Wang Z; Chen C; Dong D, 2020, Instance Weighted Incremental Evolution Strategies for Reinforcement Learning in Dynamic Environments, http://dx.doi.org/10.48550/arxiv.2010.04605

Chen Y; Pan Y; Dong D, 2020, Quantum Language Model with Entanglement Embedding for Question Answering, http://dx.doi.org/10.48550/arxiv.2008.09943

Wang Z; Chen C; Dong D, 2020, Lifelong Incremental Reinforcement Learning with Online Bayesian Inference, http://dx.doi.org/10.48550/arxiv.2007.14196

Li Y; Aghvami AH; Dong D, 2020, Intelligent Trajectory Planning in UAV-mounted Wireless Networks: A Quantum-Inspired Reinforcement Learning Perspective, http://dx.doi.org/10.48550/arxiv.2007.13418

Dong D; Shu C-C; Chen J; Xing X; Ma H; Guo Y; Rabitz H, 2020, Learning control of quantum systems using frequency-domain optimization algorithms, http://dx.doi.org/10.48550/arxiv.2005.13080

Ma H; Huang C-J; Chen C; Dong D; Wang Y; Wu R-B; Xiang G-Y, 2020, On compression rate of quantum autoencoders: Control design, numerical and experimental realization, http://dx.doi.org/10.48550/arxiv.2005.11149

Yu Q; Wang Y; Dong D; Petersen IR; Xiang G-Y, 2020, Generation of accessible sets in the dynamical modelling of quantum network systems, http://dx.doi.org/10.48550/arxiv.2004.14663

Yu Q; Dong D; Petersen IR, 2020, Hybrid filtering for a class of nonlinear quantum systems subject to classical stochastic disturbances, http://dx.doi.org/10.48550/arxiv.2004.07050

Yu Q; Wang Y; Dong D; Petersen IR, 2020, On the capability of a class of quantum sensors, http://dx.doi.org/10.48550/arxiv.2003.08679

Wang Y; Yokoyama S; Dong D; Petersen IR; Huntington EH; Yonezawa H, 2019, Two-stage Estimation for Quantum Detector Tomography: Error Analysis, Numerical and Experimental Results, http://dx.doi.org/10.48550/arxiv.1905.05323

Tan L; Dong D; Li D; Xue S, 2019, Quantum Hamiltonian Identification with Classical Colored Measurement Noise, http://dx.doi.org/10.48550/arxiv.1905.01625

Huang C-J; Ma H; Yin Q; Tang J-F; Dong D; Chen C; Xiang G-Y; Li C-F; Guo G-C, 2019, Realization of a quantum autoencoder for lossless compression of quantum data, http://dx.doi.org/10.48550/arxiv.1903.08699

Wu K-D; Hou Z; Xiang G-Y; Li C-F; Guo G-C; Dong D; Nori F, 2019, Detecting Non-Markovianity via Quantified Coherence: Theory and Experiments, http://dx.doi.org/10.48550/arxiv.1903.03359

Zhang S; Liu K; Dong D; Feng X; Pan F, 2019, Subspace Stabilization Analysis for Non-Markovian Open Quantum Systems, http://dx.doi.org/10.48550/arxiv.1901.10088

Wu R-B; Ding H; Dong D; Wang X, 2018, Learning Robust and High-Precision Quantum Controls, http://dx.doi.org/10.48550/arxiv.1811.01884

Wang Y; Dong D; Sone A; Petersen IR; Yonezawa H; Cappellaro P, 2018, Quantum Hamiltonian Identifiability via a Similarity Transformation Approach and Beyond, http://dx.doi.org/10.48550/arxiv.1809.02965

Chen C; Dong D; Li H-X; Chu J; Tarn T-J, 2018, Fidelity-based Probabilistic Q-learning for Control of Quantum Systems, http://dx.doi.org/10.48550/arxiv.1806.03145

Shu C-C; Yuan K-J; Dong D; Petersen IR; Bandrauk AD, 2018, Identifying Strong-Field Effects in Indirect Photofragmentation Reactions, http://dx.doi.org/10.48550/arxiv.1806.04078

Wu C; Qi B; Chen C; Dong D, 2018, Robust Learning Control Design for Quantum Unitary Transformations, http://dx.doi.org/10.48550/arxiv.1806.02140

Cui W; Dong D, 2017, Modelling and Control of Quantum Measurement Induced Backaction in Double Quantum Dots, http://dx.doi.org/10.48550/arxiv.1712.04791

Guo Y; Dong D; Shu C-C, 2017, Achieving robust and high-fidelity quantum control via spectral phase optimization, http://dx.doi.org/10.48550/arxiv.1709.00652

Wang Y; Yin Q; Dong D; Qi B; Petersen IR; Hou Z; Yonezawa H; Xiang G-Y, 2017, Quantum gate identification: error analysis, numerical results and optical experiment, http://dx.doi.org/10.48550/arxiv.1707.06039

Yokoyama S; Pozza ND; Serikawa T; Kuntz KB; Wheatley TA; Dong D; Huntington EH; Yonezawa H, 2017, Characterization of entangling properties of quantum measurement via two-mode quantum detector tomography using coherent state probes, http://dx.doi.org/10.48550/arxiv.1705.06441

Shu C-C; Dong D; Petersen IR; Henriksen NE, 2017, Complete elimination of nonlinear light-matter interactions with broadband ultrafast laser pulses, http://dx.doi.org/10.48550/arxiv.1705.02099

Yu Q; Dong D; Petersen IR; Gao Q, 2017, Hybrid Filtering for a Class of Quantum Systems with Classical Disturbances, http://dx.doi.org/10.48550/arxiv.1703.08976

Dong D; Xing X; Ma H; Chen C; Liu Z; Rabitz H, 2017, Learning-based Quantum Robust Control: Algorithm, Applications and Experiments, http://dx.doi.org/10.48550/arxiv.1702.03946

Pan Y; Dong D; Petersen IR, 2016, Dark Modes of Quantum Linear Systems, http://dx.doi.org/10.48550/arxiv.1611.04643

Wang Y; Dong D; Qi B; Zhang J; Petersen IR; Yonezawa H, 2016, A Quantum Hamiltonian Identification Algorithm: Computational Complexity and Error Analysis, http://dx.doi.org/10.48550/arxiv.1610.08841

Liu Z; Wang L; Wang J; Dong D; Hu X, 2016, Distributed sampled-data control of nonholonomic multi-robot systems with proximity networks, http://dx.doi.org/10.48550/arxiv.1609.02174

Dong D; Wu C; Chen C; Qi B; Petersen IR; Nori F, 2016, Learning robust control for generating universal quantum gates, http://dx.doi.org/10.48550/arxiv.1606.06084

Hou Z; Zhong H-S; Tian Y; Dong D; Qi B; Li L; Wang Y; Nori F; Xiang G-Y; Li C-F; Guo G-C, 2016, Full reconstruction of a 14-qubit state within four hours, http://dx.doi.org/10.48550/arxiv.1602.08604

Kuang S; Dong D; Petersen IR, 2015, Rapid Lyapunov control of finite-dimensional quantum systems, http://dx.doi.org/10.48550/arxiv.1512.02545

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