Feedback quantum control of molecular electronic population transfer

Adaptive Femtosecond Quantum Control

“…However, the key advantages of the adaptive approach to quantum control (i.e., that no a priori knowledge about the Hamiltonian and the PES of the system is needed, and the fact that the experimental conditions are implicitly taken into account) have led to significant progress in the control of physical and chemical processes. Among the first demonstrations of this method were the optimization of the excited state population of a laser dye by Bardeen et al [45] and the automated compression of femtosecond laser pulses [44,[46][47][48]. Since then, the dissociation of molecules in the gas phase [49][50][51][52], energy transfer in large biomolecular molecules [53], selective excitation of different vibrational modes [54,55] and the control of the geometrical rearrangement in the liquid phase [56] and many other problems have been successfully controlled.…”

“…Adaptive femtosecond quantum control has proven to be a very powerful tool to control a variety of chemical reactions and physical processes [15,45,49,52,53,56,59,127,159]. However, in many cases it is quite difficult to extract the control mechanism(s) utilized by the optimal pulse shape obtained in the optimal control experiment, a problem already encountered in chapter 4.…”

“…A suitable parametrization of the spectral phases can also give a handle on time-domain parameterizations, e.g., by scanning only pulse sequences with a certain temporal spacing [164]. In several demonstrations of closed-loop quantum control, the additional information gained from closed-loop optimizations in restricted subspaces facilitated the interpretation of possible control mechanisms [45,53,54,[165][166][167][168][169][170][171][172]. The obtained results can also be used to change the basis of the search space, further simplifying the optimization procedure in subsequent experiments [165,166,170,173].…”

“…This approach has proven to be an excellent method for reaching specific control objectives [15,45,49,52,53,56,59,127,159]. However, it is usually difficult to gain insight into the reaction mechanisms at play or to extract information on the interaction of the investigated system with electromagnetic fields from the optimized field shapes.…”

Strong field quantum control by selective population of dressed states

“…An alternative approach based on the use of the combination of pulse shaping techniques [12] with adaptive feedback learning loops (closed loop) was suggested [13] for the case when the underlying potential surfaces are unknown. Implementations of this technique demonstrate the optimization of almost any conceivable physical quantity [14][15][16][17][18][19][20][21][22][23][24][25][26]. However, it is not clear whether this methodology is suitable to extract the underlying physical mechanism from the electrical fields obtained during the optimization process.…”