The Gamma transform of a measure is defined as follows. If $\alpha$ is a $\mathbf{Z}_p$-valued measure on $\mathbf{Z}_p$, then the Gamma transform of $\alpha$ is: $$\Gamma_{\alpha}(s) = \int_{\mathbf{Z}_p^{\times}} \langle x \rangle^s \, d\alpha(x). $$ So the Gamma transform takes as input a measure $\alpha$, and returns an analytic function of the variable $s$, which we call $\Gamma_{\alpha}(s)$. But we can also think of the Gamma transform in a different way: as taking as input a power series and returning as output a power series. Namely:
- as input, the Gamma transform takes in the power series $F_{\alpha}(T)$ corresponding to the measure $\alpha$
- as output, the Gamma transform returns the power series $G$ such that $G((1+p)^s - 1) = \Gamma_{\alpha}(s)$.
My question is: can one explicitly describe the Gamma transform as a map from power series to power series? That is, given a power series $f(T) = \sum a_nT^n$, is there an explicit formula for the power series expansion of $\Gamma_F(T)$ in terms of the power series expansion of $F(T)$?
Here is my motivation for asking this. Washington has a very nice article, "On Sinnott's Proof of the Vanishing of the lwasawa Invariant $\mu_p$", where he gives a different proof of the Ferrero–Washington Theorem, inspired by a proof of Sinnott. On page 3, Washington does a few calculations with power series and says that "this is essentially the Gamma-transform". But I don't know what the Gamma transform looks like as a map from power series to power series, so I don't understand what that comment means. It seems to lie at the heart of the proof, so I want to ask this question to make sense of that step in the paper.