Algorithms for closed loop control of quantum dynamics

Research output: Contribution to journalConference article

16 Scopus citations

Abstract

Most quantum systems considered for control by external fields are plagued by a serious lack of complete information about the underlying Hamiltonian. Traditional feedback control techniques are generally not appropriate due to the latter problem, as well as the ultrafast nature of typical quantum dynamics phenomena and the fact that observations of the quantum system will inevitably lead to a disturbance which may often be contradictory to the desired control. In contrast, learning control techniques have a special role to play in the manipulation of quantum dynamics phenomena. The unique capabilities of quantum systems making them amenable to learning control are (a) the ability to have very large numbers of identical systems for submission to control, (b) the high duty cycle of laboratory laser controls, and (c) the ability to observe the impact of trial controls at ultrafast time scales. Various learning algorithms have been proposed to guide this control process. The present paper will discuss these proposals, as well as some new perspectives.

Original languageEnglish (US)
Pages (from-to)937-941
Number of pages5
JournalProceedings of the IEEE Conference on Decision and Control
Volume1
StatePublished - Dec 1 2000
Event39th IEEE Confernce on Decision and Control - Sydney, NSW, Australia
Duration: Dec 12 2000Dec 15 2000

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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