@inproceedings{fdb3e1ce01f74451b29a0db7e4f800db,
title = "Feedback design for quantum state manipulation by measurements",
abstract = "In this paper, we propose feedback designs for manipulating a quantum state to a target state by performing sequential measurements. In light of Belavkin's quantum feedback control theory, for a given set of (projective or non-projective) measurements and a given time horizon, we show that finding the measurement selection policy that maximizes the successful manipulation is an optimal control problem for a controlled Markovian process. The optimal policy is Markovian and can be solved by dynamical programming. Numerical examples indicate that making use of feedback information significantly improves the success probability compared to classical scheme without taking feedback.",
keywords = "Quantum measurement, Quantum state manipulation, Stochastic optimal control",
author = "Shuangshuang Fu and Guodong Shi and Alexandre Proutiere and James, {Matthew R.}",
note = "Publisher Copyright: {\textcopyright} 2015 American Automatic Control Council.; 2015 American Control Conference, ACC 2015 ; Conference date: 01-07-2015 Through 03-07-2015",
year = "2015",
month = jul,
day = "28",
doi = "10.1109/ACC.2015.7170719",
language = "English",
series = "Proceedings of the American Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "104--107",
booktitle = "ACC 2015 - 2015 American Control Conference",
address = "United States",
}