Adaptive Control Goal Selection for Strong-Field Dissociative Ionization of Polyatomic Molecules

In many settings (for instance, in strong-field mass-spectral sensing technologies) improving control efficiency is more important than achieving specific control goals. In this case, control goals may be adaptively formulated in the process of a strong-field experiment. To determine the pairs of fragment ions in a mass spectrum that are most susceptible to control by adaptive optimization of the laser pulse shapes in the strong-field regime, a statistical method is proposed that is based on covariance analysis of the mass spectral fragmentation patterns generated by a set of random shaped pulses. As a test, the method was applied to fragmentation of a large organic molecule dimethylmethylphosphonate, (CH$_{3}$O)-PO-(OCH$_{3})$-(CH$_{3})$. All possible pairs of the ionized fragments in \textit{tof} mass spectrum were ranked by the value of their correlation coefficients ranging from +1 to --1. A genetic-algorithm based adaptive control was then used to optimize the ion peak ratios in these pairs. Convincingly, the pairs of fragment ions that have higher negative covariances possess a correspondingly higher degree of controllability, while the pairs that have higher positive covariances possess correspondingly lower controllability.