Abstract
We are utilizing recent advances in ultrafast laser technology and recent discoveries in optimal shaping of laser pulses to significantly enhance the stand-off detection of explosives via control of molecular processes at the quantum level. Optimal dynamic detection of explosives is a method whereby the selectivity and sensitivity of any of a number of nonlinear spectroscopic methods are enhanced using optimal shaping of ultrafast laser pulses. We have recently investigated the Gerchberg–Saxton algorithm as a method to very quickly estimate the optimal spectral phase for a given analyte from its spontaneous Raman spectrum and the ultrafast laser pulse spectrum. Results for obtaining selective coherent anti-Stokes Raman spectra (CARS) for an analyte in a mixture, while suppressing the CARS signals from the other mixture components, are compared for the Gerchberg–Saxton method versus previously obtained results from closed-loop machine-learning optimization using evolutionary strategies.
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The authors gratefully acknowledge the support of the US Department of Homeland Security. Los Alamos National Laboratory is an affirmative action equal opportunity employer operated by Los Alamos National Security, LLC for the National Nuclear Security Administration of the US Department of Energy under contract DE-AC52-06NA25396.
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Published in the 10th Anniversary Issue.
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Moore, D.S., McGrane, S.D., Greenfield, M.T. et al. Use of the Gerchberg–Saxton algorithm in optimal coherent anti-Stokes Raman spectroscopy. Anal Bioanal Chem 402, 423–428 (2012). https://doi.org/10.1007/s00216-011-5348-x
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DOI: https://doi.org/10.1007/s00216-011-5348-x