Computation of Two-Dimensional Spectra Assisted by Compressed Sampling.

The computation of scientific data can be very time-consuming, even if they are ultimately determined by a small number of parameters. The principle of compressed sampling suggests that for typical data we can achieve a considerable decrease in the computation time by avoiding the need to sample the full data set. We demonstrate the usefulness of this approach at the hand of two-dimensional (2-D) spectra in the context of ultrafast nonlinear spectroscopy of biological systems where numerical calculations are highly challenging due to the considerable computational effort involved in obtaining individual data points.