Identification of quantum closed systems via the quantum process tomography

Weiwei Zhou, S. G. Schirmer, Hongwei Xie +1 more

The dynamics of an unknown closed quantum system can be characterized by a Hamiltonian. We discuss the identification of this Hamiltonian from quantum process tomography data at several time points for systems with a time-independent Hamiltonian. Quantum process tomography (QPT) yields a set of unitary operators and allows us to convert the identification problem into an estimation problem for the eigenfrequencies of the system. Spectral decomposition of Hermitian and unitary operators shows that process tomography needs to be performed at least at two different time points and the identifiability of the Hamiltonian depends on the choice of these points. Sufficient conditions on the timing to ensure complete identifiability of the Hamiltonian are presented under the assumption that unitary matrices obtained from QPT are exact without numerical errors.

Norman Y. Yao, Chris R. Laumann, Alexey Vyacheslavovich Gorshkov +2 more

Mirko Lobino

Yannick Deville, Alain Deville

System identification and inversion are two closely related problems, which lead to various configurations. In the quantum framework, system identification was only studied in the non-blind (or supervised) mode, i.e. with known input states (in addition to known output states). It is then called quantum process tomography. We here develop its blind (or unsupervised) version, operating with unknown (unentangled) input states (which are here not controlled by an automated loop). Our approach takes advantage of the blind quantum source separation (i.e. blind multi-qubit system inversion) methods based on disentanglement that we recently introduced. It is detailed for Heisenberg spin coupling and could be extended to other classes of processes. It estimates the parameter values of the Heisenberg Hamiltonian.

Shuixin Xiao, Yuanlong Wang, Qi Yu +3 more

Yuanlong Wang, Bo Qi, Daoyi Dong +1 more

Identifying parameters in the system Hamiltonian is a vitally important task in the development of quantum technology. This paper investigates the problem of Hamiltonian identification for closed quantum systems and develops a new algorithm to achieve the task of identifying the Hamiltonian. Under the framework of standard quantum process tomography and without prior assumptions, we first convert the problem of Hamiltonian identification into an optimization problem and then design an iterative algorithm to numerically solve this problem. Numerical results for a two-qubit system are presented to show the effectiveness of the proposed algorithm through analyzing the mean squared error.