The model depends on two parameters $\beta>0$ and $-\beta\le \nu<1$. The evolution of a height function $H_T(N)$ is as follows. At each discrete time step, add a box to a place where we can with probability $\beta/(1+\beta)$. If a box is added, simultaneously add a random number of boxes according to a truncated geometric random variable with parameter $(\nu+1)/(\beta+1)$, i.e., such that if an overhang occurs, we truncate the resulting added boxes. The special case $\nu=-\beta$ reduces the model to the classical geometric corner growth whose fluctuations were studied in .
The next picture indicates one possible time step in DGCG (doubly geometric corner growth).
The simulation is a simple forward sampling of the discrete time Markov chain.
There is no data for this simulation. The simulation pictures are shown in “Russian notation”, i.e., rotated by 45 degrees. The random height function is given in blue, and there is also a theoretical limit shape (a cubic curve) obtained in  superimposed onto it.