Pixel area variations in sensors: a novel framework for predicting pixel
  fidelity and distortion in flat field response
  We describe the drift field in thick depleted silicon sensors as a
superposition of a one-dimensional backdrop field and various three-dimensional
perturbative contributions that are physically motivated. We compute
trajectories for the conversions along the field lines toward the channel and
into volumes where conversions are confined by the perturbative fields. We
validate this approach by comparing predictions against measured response
distributions seen in five types of fixed pattern distortion features. We
derive a quantitative connection between "tree ring" flat field distortions to
astrometric and shape transfer errors with connections to measurable wavelength
dependence - as ancillary pixel data that may be used in pipeline analysis for
catalog population. Such corrections may be tested on DECam data, where
correlations between tree ring flat field distortions and astrometric errors -
together with their band dependence - are already under study. Dynamic effects,
including the brighter-fatter phenomenon for point sources and the flux
dependence of flat field fixed pattern features are approached using
perturbations similar in form to those giving rise to the fixed pattern
features. These in turn provide drift coefficient predictions that can be
validated in a straightforward manner. Once the three parameters of the model
are constrained using available data, the model is readily used to provide
predictions for arbitrary photo-distributions with internally consistent
wavelength dependence provided for free.
