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Deconvolution of optical multidimensional coherent spectra
Author(s) -
Marten Richter,
Rohan Singh,
Mark E. Siemens,
Steven T. Cundiff
Publication year - 2018
Publication title -
science advances
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.928
H-Index - 146
ISSN - 2375-2548
DOI - 10.1126/sciadv.aar7697
Subject(s) - deblurring , deconvolution , spectral line , computer science , optics , statistical physics , physics , biological system , artificial intelligence , algorithm , image processing , image (mathematics) , astronomy , biology , image restoration
Optical coherent multidimensional spectroscopy is a powerful technique for unraveling complex and congested spectra by spreading them across multiple dimensions, removing the effects of inhomogeneity, and revealing underlying correlations. As the technique matures, the focus is shifting from understanding the technique itself to using it to probe the underlying dynamics in the system being studied. However, these dynamics can be difficult to discern because they are convolved with the nonlinear optical response of the system. Inspired by methods used to deblur images, we present a method for deconvolving the underlying dynamics from the optical response. To demonstrate the method, we extract the many-particle diffusion Green's functions for excitons in a semiconductor quantum well from two-dimensional coherent spectra.

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