11 citations · 18 across the 13 of their papers we have counts for
15 papers
Optimal filtering for a giant cavity in waveguide QED systems
Guangpu Wu, Shibei Xue, Yuting Zhu +2
In waveguide quantum electrodynamics (QED) systems, a giant cavity can be engineered to interact with quantum fields by multiple distant coupling points so that its non-Markovian d…
Tractable Infinite-Horizon Stochastic Model Predictive Control for Quantum Filtering via Eigenstate Reduction
Yunyan Lee, Ian R. Petersen, Daoyi Dong
Model predictive control has shown potential to enhance the robustness of quantum control systems. In this work, we propose a tractable Stochastic Model Predictive Control (SMPC) f…
Generalized collective quantum tomography: algorithm design, optimization, and validation
Shuixin Xiao, Yuanlong Wang, Zhibo Hou +6
Quantum tomography is a fundamental technique for characterizing, benchmarking, and verifying quantum states and devices. It plays a crucial role in advancing quantum technologies…
Parameter Estimation for Jump-Diffusion Stochastic Master Equations
Weichao Liang, Shuixin Xiao, Daoyi Dong +1
This paper investigates parameter estimation for open quantum systems under continuous observation, whose conditional dynamics are governed by jump-diffusion stochastic master equa…
Unified formalism and adaptive algorithms for optimal quantum state, detector and process tomography
Shuixin Xiao, Xiangyu Wang, Yuanlong Wang +8
Quantum tomography is a standard technique for characterizing, benchmarking and verifying quantum systems/devices and plays a vital role in advancing quantum technology and underst…
Time-Optimal Control of Finite Dimensional Open Quantum Systems via a Model Predictive Strategy
Yunyan Lee, Ian R. Petersen, Daoyi Dong
To mitigate dissipative effects from environmental interactions and efficiently stabilize quantum states, time-optimal control has emerged as an effective strategy for open quantum…
Robust Variational Ground-State Solvers via Dissipative Quantum Feedback Models
Yunyan Lee, Ian R. Petersen, Daoyi Dong
We propose a variational framework for solving ground-state problems of open quantum systems governed by quantum stochastic differential equations (QSDEs). This formulation natural…
Machine Learning for Estimation and Control of Quantum Systems
Hailan Ma, Bo Qi, Ian R. Petersen +3
The development of quantum technologies relies on creating and manipulating quantum systems of increasing complexity, with key applications in computation, simulation, and sensing.…
Simultaneous estimations of quantum state and detector through multiple quantum processes
Shuixin Xiao, Weichao Liang, Yuanlong Wang +3
The estimation of all the parameters in an unknown quantum state or measurement device, commonly known as quantum state tomography (QST) and quantum detector tomography (QDT), is c…
An online optimization algorithm for tracking a linearly varying optimal point with zero steady-state error
Alex Xinting Wu, Ian R. Petersen, Valery Ugrinovskii +1
In this paper, we develop an online optimization algorithm for solving a class of nonconvex optimization problems with a linearly varying optimal point. The global convergence of t…
Arbitrary State Transition of Open Qubit System Based on Switching Control
Guangpu Wu, Shibei Xue, Shan Ma +3
We present a switching control strategy based on Lyapunov control for arbitrary state transitions in open qubit systems. With coherent vector representation, we propose a switching…
A two-stage solution to quantum process tomography: error analysis and optimal design
Shuixin Xiao, Yuanlong Wang, Jun Zhang +4
Quantum process tomography is a critical task for characterizing the dynamics of quantum systems and achieving precise quantum control. In this paper, we propose a two-stage soluti…
Robust Quantum Control via a Model Predictive Control Strategy
Yunyan Lee, Ian R. Petersen, Daoyi Dong
This article presents a robust control strategy using Time-Optimal Model Predictive Control (TOMPC) for a two-level quantum system subject to bounded uncertainties. In this method,…
Quantum autoencoders using mixed reference states
Hailan Ma, Gary J. Mooney, Ian R. Petersen +2
One of the fundamental tasks in quantum information theory is quantum data compression, which can be realized via quantum autoencoders that first compress quantum states to low-dim…
Effects of parametric uncertainties in cascaded open quantum harmonic oscillators and robust generation of Gaussian invariant states
Igor G. Vladimirov, Ian R. Petersen, Matthew R. James
This paper is concerned with the generation of Gaussian invariant states in cascades of open quantum harmonic oscillators governed by linear quantum stochastic differential equatio…