CS: Interpolating solutions of the Helmhotz equation with compressed sensing

Here is a very nice talk by Evgeniy Lebed with Felix Herrmann, Yogi Erlangga and Tim Lin entitled Interpolating solutions of the Helmhotz equation with compressed sensing or in another words, how to solve the Helmoltz equation with CS:

The introduction reads:

We present an algorithm which allows us to model wavefields with frequency-domain methods using a much smaller number of frequencies than that typically required by the classical sampling theory in order to obtain an alias-free result. The foundation of the algorithm is the recent results on the compressed sensing, which state that data can be successfully recovered from an incomplete measurement if the data is sufficiently sparse. Results from numerical experiment show that only 30% of the total frequency spectrum is need to capture the full wavefield information when working in the hard 2D synthetic Marmousi model.