Quantum State Tomography in Nonequilibrium Environments

Abstract

We generalize an approach to studying the quantum state tomography (QST) of open systems in terms of the dynamical map in Kraus representation within the framework of dynamic generation of informationally complete positive operator-valued measures. As applications, we use the generalized approach to theoretically study the QST of qubit systems in the presence of nonequilibrium environments which exhibit nonstationary and non-Markovian random telegraph noise statistical properties. We derive the time-dependent measurement operators for the quantum state reconstruction of the single qubit and two-qubit systems in terms of the polarization operator basis. It is shown that the behavior of the time-dependent measurement operators is closely associated with the dynamical map of the qubit systems.

Quantum teleportation in Heisenberg chain with magnetic-field gradient under intrinsic decoherence

“…In addition, the behaviors of all three above-mentioned criteria are oscillating, and this indicates that in some intervals when the behaviors have an increasing rate, the dynamics of the system will be non-Markovian, and at intervals when the behaviors have a decreasing rate, the dynamics of the system refer to Markovian. In intervals when the dynamic is Markovian, it means that information continuously flows from the system to the environment, while if there is a backflow of information from the environment to the system, this process has a non-Markovian dynamic, which is caused by the existence of quantum memory [56][57][58] . Since the non-Markovian dynamic of the system is determined from the information flow, witnesses based on QFI in 82 and fidelity in 83 have been suggested.…”

Special Issue on Photonic State Tomography: Methods and Applications

“…"Quantum State Tomography in Nonequilibrium Environments" provides us with an insightful perspective into the quantum state tomography of open systems [5]. The authors employ a novel approach, which is based on dynamical maps in the Kraus representation [6], to explore the complexities of nonequilibrium environments [7,8].…”