MARSFT: Efficient fitting of CARS spectra using a library‐based genetic algorithm

A loss‐less compressed library scheme is presented in this publication that allows for computationally efficient fitting of coherent anti‐Stokes Raman spectra with no restriction to the number of degrees of freedom for the spectral fit. The compression is achieved by convolving the squared modulus and the real part of the complex susceptibility with a Gaussian kernel narrower than the experimental apparatus function. This effectively reduces library size while allowing to convolve to the final experimental linewidth during the fit. For the optimization procedure, a gradient‐free mixed‐integer genetic algorithm was implemented due to its ability to extract library spectra without interpolation. We demonstrate the ability of the code by comparing it to CARSFT in terms of dependency on starting solution, computational cost and accuracy using simulated spectra with varying noise contribution.