We test the precision with which weak lensing data can provide characteristic cluster mass profiles within Cold Dark Matter ( CDM ) scenarios .
Using a parallel treecode to simulate volumes as large as 500 h ^ { -1 } Mpc with good resolution , we generate samples of large clusters within a standard CDM model and an open CDM model with \Omega _ { o } = 0.3 .
We mock high-quality lensing data by including realistic errors , selecting cluster samples based on velocity dispersion , and fitting profiles within a realistic range in radius .
We find that a sample of ten clusters can determine logarithmic profile slopes with 1- \sigma errors of about 7 % .
Increasing the sample size to twenty brings this error down to less than 5 % , but this is still insufficient to distinguish the two models .
However , measures of cluster profiles obtained with weak lensing do place strong constraints for general CDM–like models of structure formation , and we discuss the optimal strategy for obtaining data samples to use for this purpose .