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Highly sensitive Fourier-transform coherent anti-Stokes Raman scattering spectroscopy via genetic algorithm pulse shaping

Abstract

We report highly sensitive Fourier-transform coherent anti-Stokes Raman scattering spectroscopy enabled by genetic algorithm (GA) pulse shaping for adaptive dispersion compensation. We show that the non-resonant four-wave mixing signal from water can be used as a fitness indicator for successful GA training. This method allows GA adaptation to sample measurement conditions and offers significantly improved performance compared to training using second-harmonic generation from a nonlinear crystal in place of the sample. Results include a ${3} \times$ improvement to peak signal-to-noise ratio for 2-propanol measurement, as well as a ${10} \times$ improvement to peak intensities from the high-throughput measurement of polystyrene microbeads under flow.

© 2021 Optical Society of America

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Data Availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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