  Much of transiting exoplanet science relies on high-precision photometry. The
current generation of instruments can exhibit sensitivity variations greater
than the astrophysical signals. For the InfraRed Array Camera (IRAC) on the
Spitzer Space Telescope, a popular way to handle this is
BiLinearly-Interpolated Subpixel Sensitivity (BLISS) mapping. As part of a
Markov Chain Monte Carlo (MCMC), BLISS mapping estimates the sensitivity at
many locations (knots) on the pixel, then interpolates to the target star's
centroids. We show that such embedded optimization schemes can misfit or bias
parameters. Thus, we construct a model of $\textit{Spitzer}$ eclipse light
curves to test the accuracy and precision of BLISS mapping. We compare standard
BLISS mapping to a variant where the knots are fit during the MCMC, as well as
to a polynomial model. Both types of BLISS mapping give similar eclipse depths,
and we find that standard knots behave like real parameters. Standard BLISS
mapping is therefore a reasonable shortcut to fitting for knots in an MCMC.
BLISS maps become inaccurate when the photon noise is low, but typically
approximate the real sensitivity well. We also find there is no perfect method
for choosing the ideal number of BLISS knots to use on given data. BLISS
mapping gives fits that are usually more accurate than precise (i.e. they are
overly conservative), and the routine is more precise than polynomial models
for significant eclipses or pixels with more varied sensitivities. BLISS
mapping has better predictive power for most of these particular synthetic
data, depending on how one treats time-correlated residuals. Overall, we
conclude that BLISS mapping can be a reasonable sensitivity model for IRAC
photometry.
