A new automated assign and analysing method for high-resolution rotationally resolved spectra using genetic algorithms

Abstract

This paper describes a numerical technique that has recently been developed to automatically assign and fit high-resolution spectra. The method makes use of genetic algorithms (GA). The current algorithm is compared with previously used analysing methods. The general features of the GA and its applications in automated assignments is discussed. In a number of examples the successful application of the technique is demonstrated.

Spectroscopy of the transition of formaldehyde in the 30140–30790cm−1 range: The and rovibrational bands

“…We find deviations to line positions calculated with literature values for rotational constants [27,24]. Using genetic algorithms [31,32,30] for fitting rotational constants of the 2 1 0 rovibrational bands, good agreement between the simulation and the measured spectra is achieved over a wide range of the spectrum. However, the region between 30390-30410 cm −1 had to be excluded from the simulation, which might indicate the presence of perturbations.…”

“…Details about the GA and the cost function used for evaluation of the quality of the fit can be found in Refs. [31,32,30]. Table 1 compiles the so-determined parameters and compares them to the previous parameters for the ground state [27] and the excited vibronic states [24].…”

CRASY: Mass- or Electron-Correlated Rotational Alignment Spectroscopy

“…S1 to S5 Table S1 References (30)(31)(32)(33)(34)(35)(36)(37)(38) 20 May 2011; accepted 12 July 2011 10.1126/science.1208686…”

“…The additional spectroscopic axes in CRASY experiments can assist the analysis of rotational spectra in impure samples; for example, by correlated determination of ion masses (in mass-CRASY), ionization potentials (in electron-CRASY), or fluorescence spectra (in fluorescence-CRASY). Together with the recent development of mathematical algorithms for the semiautomated assignment of rotational spectra (37), this technique may generally facilitate the structural characterization of constituents in inherently unstable samples or samples containing inseparable compounds.…”

Deducing 1D concentration profiles from EPR imaging: A new approach based on the concept of virtual components and optimization with the genetic algorithm

“…As a result, genetic algorithms are of growing interest in various fields of science [18][19][20], with many successful applications in spectroscopy [21][22][23]. Recent notable examples are provided, for instance, by Meerts et al [24][25][26]. There is also a growing number of GA applications in the field of EPR spectroscopy, including optimization of static multicomponent powder spectra [27][28][29] and motionally-restricted fluid-solution spectra [30][31][32].…”