Sanders, JacobSaikin, Semion K.Mostame, SarahAndrade, XavierWidom, Julia R.Marcus, Andrew H.Aspuru-Guzik, Alan2014-02-042012Sanders, Jacob Nathan, Semion K. Saikin, Sarah Mostame, Xavier Andrade, Julia R. Widom, Andrew H. Marcus, and Alan Aspuru-Guzik. 2012. “Compressed Sensing for Multidimensional Spectroscopy Experiments.” Journal of Physical Chemistry Letters 3 (18) (September 20): 2697-2702. doi:10.1021/jz300988p. http://dx.doi.org/10.1021/jz300988p.1948-7185http://nrs.harvard.edu/urn-3:HUL.InstRepos:11643696Compressed sensing is a processing method that significantly reduces the number of measurements needed to accurately resolve signals in many fields of science and engineering. We develop a two-dimensional variant of compressed sensing for multidimensional spectroscopy and apply it to experimental data. For the model system of atomic rubidium vapor, we find that compressed sensing provides an order-of-magnitude (about 10-fold) improvement in spectral resolution along each dimension, as compared to a conventional discrete Fourier transform, using the same data set. More attractive is that compressed sensing allows for random undersampling of the experimental data, down to less than 5% of the experimental data set, with essentially no loss in spectral resolution. We believe that by combining powerful resolution with ease of use, compressed sensing can be a powerful tool for the analysis and interpretation of ultrafast spectroscopy data.en-USoptical spectroscopyspectral analysissparse signal reconstructionrandom samplingJournal Article2014-02-0410.1021/jz300988p