  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 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 2-D spectra in the
context of ultra-fast non-linear spectroscopy of biological systems where
numerical calculations are highly challenging due to the considerable
computational effort involved in obtaining individual data points.
