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 quantumstate
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.