Publication | Closed Access
Transformations to diagonal bases in closed-loop quantum learning control experiments
53
Citations
30
References
2005
Year
EngineeringMachine LearningLearning ControlUnitary Linear TransformationControl VariablesQuantum ComputingQuantum Optimization AlgorithmQuantum Machine LearningSystems EngineeringRobot LearningQuantum EntanglementQuantum ScienceControl MethodQuantum FeedbackQuantum AlgorithmControl DesignDiagonal BasesControl EngineeringUltrafast Laser PulsesProcess Control
This paper discusses transformations between bases used in closed-loop learning control experiments. The goal is to transform to a basis in which the number of control parameters is minimized and in which the parameters act independently. We demonstrate a simple procedure for testing whether a unitary linear transformation (i.e., a rotation amongst the control variables) is sufficient to reduce the search problem to a set of globally independent variables. This concept is demonstrated with closed-loop molecular fragmentation experiments utilizing shaped, ultrafast laser pulses.
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