Use of the Gerchberg–Saxton algorithm in optimal coherent anti-Stokes Raman spectroscopy

Autor: Margo T. Greenfield, Shawn McGrane, R. J. Scharff, D. S. Moore, R. E. Chalmers
Rok vydání: 2011
Předmět:
Zdroj: Analytical and Bioanalytical Chemistry. 402:423-428
ISSN: 1618-2650
1618-2642
DOI: 10.1007/s00216-011-5348-x
Popis: 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.
Databáze: OpenAIRE
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