  We provide a systematic approach to quantum mechanics from an
information-theoretic perspective using the language of tensor networks. Our
formulation needs only a single kind of object, so-called positive *-tensors.
Physical models translate experimental setups into networks of these *-tensors,
and the evaluation of the resulting networks yields the probability
distributions describing measurement outcomes. The idea behind our approach is
similar to categorical formulations of quantum mechanics. However, our
formulation is mathematically simpler and less abstract. Our presentation of
the core formalism is completely self-contained and relies on minimal
mathematical prerequesites. Therefore, we hope it is in principle also
understandable to people without an extensive mathematical background.
Additionally, we show how various types of models, like real-time evolutions or
thermal systems can be translated into *-tensor networks.
