  The population of dislocation defects in a crystalline material strongly
influences its properties, so the ability to analyse this population in
experimental samples is of great utility. As a complement to direct counting in
the transmission electron microscope, quantitative analysis of x-ray
diffraction line profiles is an important tool. This is an indirect approach to
quantification and so requires careful validation of the physical models that
underly the inferential process. Here we undertake to directly evaluate the
ability of line profile analysis to quantify aspects of the dislocation and
stacking fault populations by exploiting atomistic models of deformed copper
single crystals. We directly analyse these models to determine exact details of
the defect content (our "ground truth"). We then generate theoretical line
profiles for the models and analyse them using the same procedures used in
experimental analysis. This leads to inferred measures of the defect content
which we are able to compare with the exact data. We show that line profile
analysis is able to provide sound predictions of both dislocation density and
stacking fault fraction across two orders of magnitude. We further show how the
outer cut-off radius in the mean-square strain of a dislocation distribution
invoked by Warren and Averbach corresponds to the cell size in an artificially
constructed restrictedly-random distribution of dislocations according to the
model of Wilkens. Overall, our results lend important new support to the use of
line profile analysis for the quantification of line and planar defects in
crystalline materials.
