  X-ray reflectometry (XRR) provides researchers and manufacturers with a
non-destructive way to determine thickness, roughness, and density of thin
films deposited on smooth substrates. Due to the nested nature of equations
modeling this phenomenon, the inter-relation between instrument alignment and
parameter estimation accuracy is somewhat opaque. In this study, we
intentionally shift incident angle information contained in a high-quality XRR
data set and refine this shifted data using an identical structural model to
assess the effect angle misalignment has on parameter estimation. We develop a
series of calibration curves relating data misalignment to variation with layer
thickness and density for a multilayer GaAs/AlAs Certified Reference Material
on a GaAs substrate. We then test the validity and robustness of several
approaches of using known thickness and density parameters from this structure
to calibrate instrument alignment. We find the highest sensitivity to and
linearity with measurement misalignment from buried AlAs and GaAs layers, in
contrast to the surface layers, which show the most instability. This is a
fortuitous result, as buried AlAs and GaAs exhibit the highest long-term
stability in thickness. Therefore, it is indeed possible to use reference
thickness estimates to validate XRR angle alignment accuracy. Buried layer mass
density information also shows promise as a robust calibration approach. This
is suprising, as electron density of buried layers is both a highly-correlated
phenomenon, and a subtle component in the XRR model.
