  Shot noise processes are used in applied probability to model a variety of
physical systems in, for example, teletraffic theory, insurance and risk theory
and in the engineering sciences. In this work we prove a large deviation
principle for the sample-paths of a general class of multidimensional
state-dependent Poisson shot noise processes. The result covers previously
known large deviation results for one dimensional state-independent shot noise
processes with light tails. We use the weak convergence approach to large
deviations, which reduces the proof to establishing the appropriate convergence
of certain controlled versions of the original processes together with relevant
results on existence and uniqueness.
