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Acceleration of quantum optimal control theory algorithms with mixing strategies
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Acceleration of quantum optimal control theory algorithms with mixing strategies
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We propose the use of mixing strategies to accelerate the convergence of the common iterative algorithms utilized in Quantum Optimal Control Theory (QOCT). We show how the non-linear equations of QOCT can be viewed as a "fixed-point" non-linear problem. The iterative algorithms for this class of problems may benefit from mixing strategies, as it happens, e.g. in the quest for th ground-state density in Kohn-Sham density functional theory. We demonstrate, with some numerical examples, how the same mixing schemes utilized in this latter non-linear problem, may significantly accelerate the QOCT iterative procedures.
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