How different should discriminator be from generator in GAN
Generator cant learn if the discriminator error is too small. But generator should always be "ahead" of generator in order to learn.

There is a paper explaining why the generator's gradient vanishes if the discriminator gets too strong. And how does this proportion look mathemactically optimal

TL;DR Dont make it too strong, but make sure D is ahead to ensure optimal learning. GANS are notoriously unstable (expensive also)