Application of genetic algorithms in automated assignments of high-resolution spectra

This paper describes an automated assignment and fitting procedure for high-resolution rotationally resolved spectra. The method is based on the application of genetic algorithms (GA) and both frequency and intensity information of these spectra is used. The basic ideas behind the GA technique is introduced and the particular fitness function critical for the success of the GA evaluation is discussed. The meta-optimization of the internal GA parameters for an optimal exploration of the error landscape of the spectrum fitting is investigated. A number of typical examples are given in which the use of automated spectrum assignments with the GA method is of crucial importance in the analysis. Examples are given for fits of very dense spectra due to overlap of a number of rovibronic spectra in conformers and isotopomers and strongly congested spectra in dimer systems. It is also shown that since the GA performs an overall fit of the complete spectrum very good information on the orientation of the transition dipole moments is gathered.