  We consider the task of converting different digital descriptions of analog
bandlimited signals and systems into each other, with a rigorous application of
mathematical computability theory. Albeit very fundamental, the problem appears
in the scope of digital twinning, an emerging concept in the field of digital
processing of analog information that is regularly mentioned as one of the key
enablers for next-generation cyber-physical systems and their areas of
application. In this context, we prove that essential quantities such as the
peak-to-average power ratio and the bounded-input/bounded-output norm, which
determine the behavior of the real-world analog system, cannot generally be
determined from the system's digital twin, depending on which of the
above-mentioned descriptions is chosen. As a main result, we characterize the
algorithmic strength of Shannon's sampling type representation as digital twin
implementation and also introduce a new digital twin implementation of analog
signals and systems. We show there exist two digital descriptions, both of
which uniquely characterize a certain analog system, such that one description
can be algorithmically converted into the other, but not vice versa.
