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Models for open quantum systems, which play important roles in electron transport problems and quantum computing, must take into account the interaction of the quantum system with the surrounding environment. Although such models can be…

Quantum Physics · Physics 2024-07-17 Ke Wang , Xiantao Li

With the rapid progress in quantum hardware, there has been an increased interest in new quantum algorithms to describe complex many-body systems searching for the still-elusive goal of 'useful quantum advantage'. Surprisingly, quantum…

Quantum Physics · Physics 2021-09-22 Kade Head-Marsden , Stefan Krastanov , David A. Mazziotti , Prineha Narang

The gradient descent approach is the key ingredient in variational quantum algorithms and machine learning tasks, which is an optimization algorithm for finding a local minimum of an objective function. The quantum versions of gradient…

Quantum Physics · Physics 2022-04-19 Jin-Min Liang , Shi-Jie Wei , Shao-Ming Fei

This paper proposes a probabilistic Bayesian formulation for system identification (ID) and estimation of nonseparable Hamiltonian systems using stochastic dynamic models. Nonseparable Hamiltonian systems arise in models from diverse…

Dynamical Systems · Mathematics 2022-09-19 Harsh Sharma , Nicholas Galioto , Alex A. Gorodetsky , Boris Kramer

An observer-based Hamiltonian identification algorithm for quantum systems is proposed. For the 2-level case an exponential convergence result based on averaging arguments and some relevant transformations is provided. The convergence for…

Mathematical Physics · Physics 2007-05-23 Mazyar Mirrahimi , Pierre Rouchon

Identifying Hamiltonian of a quantum system is of vital importance for quantum information processing. In this Letter, we realized and benchmarked a quantum Hamiltonian identification algorithm recently proposed [Phys. Rev. Lett.…

Quantum Physics · Physics 2014-10-16 Shi-yao Hou , Hang Li , Gui-Lu Long

In this work, we consider the problem of online (real-time, single-shot) estimation of static or slow-varying parameters along quantum trajectories in quantum dynamical systems. Based on the measurement signal of a continuously-monitored…

Quantum Physics · Physics 2024-06-19 Henrik Glavind Clausen , Pierre Rouchon , Rafal Wisniewski

In this work, the Einstein notation is utilized to synthesize state and parameter transition matrices, by solving a set of ordinary differential equations. Additionally, for the system identification problem, it has been demonstrated that…

Systems and Control · Electrical Eng. & Systems 2024-07-08 Premjit Saha , Tarunraj Singh

We develop a general approach for monitoring and controlling evolution of open quantum systems. In contrast to the master equations describing time evolution of density operators, here, we formulate a dynamical equation for the evolution of…

Quantum Physics · Physics 2009-08-09 M. Mohseni , A. T. Rezakhani

Engineering quantum systems offers great opportunities both technologically and scientifically for communication, computation, and simulation. The construction and operation of large scale quantum information devices presents a grand…

Quantum Physics · Physics 2012-05-30 Sophie G. Schirmer , Daniel K. L. Oi , Weiwei Zhou , Erling Gong , Ming Zhang

Determining the Hamiltonian of a quantum system is essential for understanding its dynamics and validating its behavior. Hamiltonian learning provides a data-driven approach to reconstruct the generator of the dynamics from measurements on…

Characterizing the interactions and dynamics of quantum mechanical systems is an essential task in the development of quantum technologies. We propose an efficient protocol based on the estimation of the time derivatives of few qubit…

Engineering the Hamiltonian of a quantum system is fundamental to the design of quantum systems. Automating Hamiltonian design through gradient-based optimization can dramatically accelerate this process. However, computing the gradients of…

The dynamics of many open quantum systems are described by stochastic master equations. In the discrete-time case, we recall the structure of the derived quantum filter governing the evolution of the density operator conditioned to the…

Optimization and Control · Mathematics 2015-03-23 Pierre Six , Philippe Campagne-Ibarcq , Landry Bretheau , Benjamin Huard , Pierre Rouchon

Large-scale quantum devices provide insights beyond the reach of classical simulations. However, for a reliable and verifiable quantum simulation, the building blocks of the quantum device require exquisite benchmarking. This benchmarking…

Quantum Physics · Physics 2022-02-16 Agnes Valenti , Guliuxin Jin , Julian Léonard , Sebastian D. Huber , Eliska Greplova

We investigate the problem of determining the Hamiltonian of a locally interacting open-quantum system. To do so, we construct model estimators based on inverting a set of stationary, or dynamical, Heisenberg-Langevin equations of motion…

Quantum Physics · Physics 2020-08-19 Eugene F. Dumitrescu , Pavel Lougovski

System identification is of special interest in science and engineering. This article is concerned with a system identification problem arising in stochastic dynamic systems, where the aim is to estimate the parameters of a system along…

Methodology · Statistics 2022-01-27 Christos Merkatas , Simo Särkkä

Recent works have shown that generic local Hamiltonians can be efficiently inferred from local measurements performed on their eigenstates or thermal states. Realistic quantum systems are often affected by dissipation and decoherence due to…

Quantum Physics · Physics 2020-03-25 Eyal Bairey , Chu Guo , Dario Poletti , Netanel H. Lindner , Itai Arad

A precise understanding of the influence of a quantum system's environment on its dynamics, which is at the heart of the theory of open quantum systems, is crucial for further progress in the development of controllable large-scale quantum…

Quantum Physics · Physics 2022-10-10 I. A. Luchnikov , E. O. Kiktenko , M. A. Gavreev , H. Ouerdane , S. N. Filippov , A. K. Fedorov

Several quantities important in condensed matter physics, quantum information, and quantum chemistry, as well as quantities required in meta-optimization of machine learning algorithms, can be expressed as gradients of implicitly defined…

Quantum Physics · Physics 2022-11-28 Shahnawaz Ahmed , Nathan Killoran , Juan Felipe Carrasquilla Álvarez