  The Ginibre point process is one of the main examples of deter- minantal
point processes on the complex plane. It forms a recurring model in stochastic
matrix theory as well as in pratical applications. However, this model has
mostly been studied from a probabilistic point of view in the fields of
stochastic matrices and determinantal point processes, and thus using the
Ginibre process to model random phenomena is a topic which is for the most part
unexplored. In order to obtain a determinantal point process more suited for
simulation, we introduce a modified version of the classical kernel. Then, we
compare three different methods to simulate the Ginibre point process and
discuss the most efficient one depending on the application at hand.
