  Recently it has been shown that precise dose control and an increase in the
overall acquisition speed of atomic resolution scanning transmission electron
microscope (STEM) images can be achieved by acquiring only a small fraction of
the pixels in the image experimentally and then reconstructing the full image
using an inpainting algorithm. In this paper, we apply the same inpainting
approach (a form of compressed sensing) to simulated, sub-sampled atomic
resolution STEM images. We find that it is possible to significantly sub-sample
the area that is simulated, the number of g-vectors contributing the image, and
the number of frozen phonon configurations contributing to the final image
while still producing an acceptable fit to a fully sampled simulation. Here we
discuss the parameters that we use and how the resulting simulations can be
quantifiably compared to the full simulations. As with any Compressed Sensing
methodology, care must be taken to ensure that isolated events are not excluded
from the process, but the observed increase in simulation speed provides
significant opportunities for real time simulations, image classification and
analytics to be performed as a supplement to experiments on a microscope to be
developed in the future.
