We explore the use of principal component analysis (PCA) to characterize
high-fidelity simulations and interferometric observations of the millimeter
emission that originates near the horizons of accreting black holes. We show
mathematically that the Fourier transforms of eigenimages derived from PCA
applied to an ensemble of images in the spatial-domain are identical to the
eigenvectors of PCA applied to the ensemble of the Fourier transforms of the
images, which suggests that this approach may be applied to modeling the sparse
interferometric Fourier-visibilities produced by an array such as the Event
Horizon Telescope (EHT). We also show that the simulations in the spatial
domain themselves can be compactly represented with a PCA-derived basis of
eigenimages allowing for detailed comparisons between variable observations and
time-dependent models, as well as for detection of outliers or rare events
within a time series of images. Furthermore, we demonstrate that the spectrum
of PCA eigenvalues is a diagnostic of the power spectrum of the structure and,
hence, of the underlying physical processes in the simulated and observed
images.Comment: 16 pages, 17 figures, submitted to Ap
