I wonder how a simple pre-processing operation would affect the accuracies? In my experience, standardization (z-scoring) can really improve SVM accuracy.
I think that in this case the data was generated in a uniform manner (centered and with isotropic variance). So it might not greatly impact the performance. ~50% training error is about the best you can get in a completely non-linearly separable dataset.
