Multivariate Hawkes processes on inhomogeneous random graphs

We consider a population of $N$ interacting neurons, represented by a multivariate Hawkes process: the firing rate of each neuron depends on the history of the connected neurons. Contrary to the mean-field framework where the interaction occurs on the complete graph, the connectivity between particles is given by a random possibly diluted and inhomogeneous graph where the probability of presence of each edge depends on the spatial position of its vertices. We address the well-posedness of this system and Law of Large Numbers results as $N\to \mathrm{\infty }$. A crucial issue will be to understand how spatial inhomogeneity influences the large time behavior of the system.