  We analyze message identification via Gaussian channels with noiseless
feedback, which is part of the Post Shannon theory. The consideration of
communication systems beyond Shannon's approach is useful to increase the
efficiency of information transmission for certain applications. We consider
the Gaussian channel with feedback. If the noise variance is positive, we
propose a coding scheme that generates infinite common randomness between the
sender and the receiver and show that any rate for identification via the
Gaussian channel with noiseless feedback can be achieved. The remarkable result
is that this applies to both rate definitions $\frac 1n \log M$ (as Shannon
defined it for the transmission) and $\frac 1n \log\log M$ (as defined by
Ahlswede and Dueck for identification). We can even show that our result holds
regardless of the selected scaling for the rate.
