  In quantum-state tomography on sources with quantum degrees of freedom of
large Hilbert spaces, inference of quantum states of light for instance, a
complete characterization of the quantum states for these sources is often not
feasible owing to limited resources. As such, the concepts of informationally
incomplete state estimation becomes important. These concepts are ideal for
applications to quantum channel/process tomography, which typically requires a
much larger number of measurement settings for a full characterization of a
quantum channel. Some key aspects of both quantum-state and quantum-process
tomography are arranged together in the form of a tutorial review article that
is catered to students and researchers who are new to the field of quantum
tomography, with focus on maximum-likelihood related techniques as instructive
examples to illustrate these ideas.
