  In the context of quantum tomography, quantities called a partial
determinants\cite{jackson2015detecting} were recently introduced. PDs (partial
determinants) are explicit functions of the collected data which are sensitive
to the presence of state-preparation-and-measurement (SPAM) correlations. In
this paper, we demonstrate further applications of the PD and its
generalizations. In particular we construct methods for detecting various types
of SPAM correlation in multiqudit systems | e.g. measurement-measurement
correlations. The relationship between the PDs of each method and the
correlations they are sensitive to is topological. We give a complete
classification scheme for all such methods but focus on the explicit details of
only the most scalable methods, for which the number of settings scale as
$\mathcal{O}(d^4)$. This paper is the second of a two part series where the
first paper[2] is about theoretical perspectives of the PD and its
interpretation as a holonomy.
