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The past decade has demonstrated increasing interests in using optimalcontrol based methods within coherent quantum controllable systems. Theversatility of such methods has been demonstrated with particular elegancewithin nuclear magnetic resonance (NMR) where natural separation betweencoherent and dissipative spin dynamics processes has enabled coherent quantumcontrol over long periods of time to shape the experiment to almost idealadoption to the spin system and external manipulations. This has led to newdesign principles as well as powerful new experimental methods within magneticresonance imaging, liquid-state and solid-state NMR spectroscopy. For thisdevelopment to continue and expand, it is crucially important to constantlyimprove the underlying numerical algorithms to provide numerical solutionswhich are optimally compatible with implementation on current instrumentationand at same time are numerically stable and offer fast monotonic convergencetowards the target. Addressing such aims, we here present a smoothingmonotonically convergent algorithm for pulse sequence design in magneticresonance which with improved optimization stability lead to smooth pulsesequence easier to implement experimentally and potentially understand withinthe analytical framework of modern NMR spectroscopy.

A smoothing monotonic convergent optimal control algorithm for NMR pulse sequence design