Quantum process tomography Quantum process tomography from incomplete data from incomplete data

Vladimír Bužek

Vladimír Bužek, G. Drobný, H. Wiedemann

Anirudh Acharya, Theodore Kypraios, Mădălin Guţǎ

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

Yong Siah Teo, Berthold‐Georg Englert, Jaroslav Řeháček +1 more

We propose an iterative algorithm for incomplete quantum process tomography with the help of quantum state estimation. The algorithm, which is based on the combined principles of maximum likelihood and maximum entropy, yields a unique estimator for an unknown quantum process when one has less than a complete set of linearly independent measurement data to specify the quantum process uniquely. We apply this iterative algorithm adaptively in various situations and so optimize the amount of resources required to estimate a quantum process with incomplete data.

Thiago O. Maciel, Reinaldo O. Vianna, Roberto S. Sarthour +1 more

We reconstruct the time dependent quantum map corresponding to the relaxation process of a twospin system in liquid-state NMR at room temperature.By means of quantum tomography techniques that handle informational incomplete data, we show how to properly post-process and normalize the measurements data for the simulation of quantum information processing, overcoming the unknown number of molecules prepared in a non-equilibrium magnetization state (N j ) by an initial sequence of radiofrequency pulses.From the reconstructed quantum map, we infer both longitudinal (T 1 ) and transversal (T 2 ) relaxation times, and introduce the J-coupling relaxation times (T T , J J 1 2 ), which are relevant for quantum information processing simulations.We show that the map associated to the relaxation process cannot be assumed approximated unital and trace-preserving for times greater than T .