  We propose a methodology to design optimal pulses for achieving quantum
optimal control on molecular systems. Our approach constrains pulse shapes to
linear combinations of a fixed number of experimentally relevant pulse
functions. Quantum optimal control is obtained by maximizing a multi-target
fitness function with genetic algorithms. As a first application of the
methodology we generated an optimal pulse that successfully maximized the yield
on a selected dissociation channel of a diatomic molecule. Our pulse is
obtained as a linear combination of linearly chirped pulse functions. Data
recorded along the evolution of the genetic algorithm contained important
information regarding the interplay between radiative and diabatic processes.
We performed a principal component analysis on these data to retrieve the most
relevant processes along the optimal path. Our proposed methodology could be
useful for performing quantum optimal control on more complex systems by
employing a wider variety of pulse shape functions.
