Toward a priori selection of ellipsometry angles and wavelengths using a high performance semantic database

Abstract Modern ellipsometers only barely resemble those of only a decade ago. In situ measurements are commonly spectroscopic and ex situ investigations frequently add an additional variable, incidence angle. In either case, the number of measurements for an analysis can be 10 000 or more. Experience in a recent international round robin experiment showed no particular agreement in the selection of angles and wavelengths. Selecting a fewer number of `good' angles of incidence and wavelengths is important because at the same time it would reduce the measurement time, reduce computational load and improve the solutions. Currently we choose to say `good' points have high `resolution' (a change in the desired parameter results in a measurable change in measured parameters) and a solvable `condition' (the inverse Hessian matrix is well conditioned for variably damped least squares). In this work, values of resolution and condition are simulated for approximately 1000 points in wavelength–angle space for a large number of sample configurations and materials (over 10 000). These results are stored in a high performance semantic database which can be more than a Gigabyte. Three-dimensional images of the data and movies over thickness, for example, can be pulled from the database in real time allowing selection of incidence angles and wavelengths for an analysis.