We present an empirical strategy to determine the Hamiltonian dynamics of a two-qubit system using only initialization and measurement in a single fixed basis. Signal parameters are estimated from measurement data using Bayesian methods from which the underlying Hamiltonian is reconstructed, up to three unobservable phase factors. We extend the method to achieve full control Hamiltonian tomography for controllable systems via a multistep approach. The technique is demonstrated and evaluated by analyzing data from simulated experiments including projection noise
In this work we combine two distinct machine learning methodologies, sequential Monte Carlo and Baye...
29 pages, 3 figuresCharacterizing the interactions and dynamics of quantum mechanical systems is an ...
The identification of parameters in the Hamiltonian that describes complex many-body quantum systems...
We present an empirical strategy to determine the Hamiltonian dynamics of a two-qubit system using o...
We consider how to characterize the dynamics of a quantum system from a restricted set of initial st...
Abstract: Quantum mechanics is one of the most interesting field in modern physics. In spite of its ...
© 2016 IEEE.Identifying parameters in the system Hamiltonian is a vitally important task in the deve...
Abstract. Using Bayesian experimental design techniques, we have shown that for a single two-level q...
Precision control of a quantum system requires accurate determination of the effective system Hamilt...
Precision control of a quantum system requires accurate determination of the effective system Hamilt...
In this paper we develop qubit Hamiltonian single parameter estimation techniques using Bayesian app...
Identifying the Hamiltonian of a quantum system from experimental data is considered. General limits...
The identification of parameters in the Hamiltonian that describes complex many-body quantum systems...
In this work we combine two distinct machine learning methodologies, sequential Monte Carlo and Baye...
We introduce a method of quantum tomography for a continuous variable system in position and momentu...
In this work we combine two distinct machine learning methodologies, sequential Monte Carlo and Baye...
29 pages, 3 figuresCharacterizing the interactions and dynamics of quantum mechanical systems is an ...
The identification of parameters in the Hamiltonian that describes complex many-body quantum systems...
We present an empirical strategy to determine the Hamiltonian dynamics of a two-qubit system using o...
We consider how to characterize the dynamics of a quantum system from a restricted set of initial st...
Abstract: Quantum mechanics is one of the most interesting field in modern physics. In spite of its ...
© 2016 IEEE.Identifying parameters in the system Hamiltonian is a vitally important task in the deve...
Abstract. Using Bayesian experimental design techniques, we have shown that for a single two-level q...
Precision control of a quantum system requires accurate determination of the effective system Hamilt...
Precision control of a quantum system requires accurate determination of the effective system Hamilt...
In this paper we develop qubit Hamiltonian single parameter estimation techniques using Bayesian app...
Identifying the Hamiltonian of a quantum system from experimental data is considered. General limits...
The identification of parameters in the Hamiltonian that describes complex many-body quantum systems...
In this work we combine two distinct machine learning methodologies, sequential Monte Carlo and Baye...
We introduce a method of quantum tomography for a continuous variable system in position and momentu...
In this work we combine two distinct machine learning methodologies, sequential Monte Carlo and Baye...
29 pages, 3 figuresCharacterizing the interactions and dynamics of quantum mechanical systems is an ...
The identification of parameters in the Hamiltonian that describes complex many-body quantum systems...