I have solved most of Question 9.11 of Big Rudin :
Find conditions on $f$ and/or $\widehat{f}$ which ensure the correctness of the following formal argument : If $\varphi(t) ~=~ \frac{1}{2\pi}\int_{-\infty}^\infty f(x) e^{-ixt}\; dx $ and $$ F(x) ~=~ \sum\limits_{k=-\infty}^\infty f(x+2k\pi)$$ then $F$ is periodic, with period $2\pi$, the $n$-th Fourier coefficient of $F$ is $\varphi(n)$, hence $$ F(x) ~=~ \sum\limits_{n=-\infty}^\infty \varphi(n)e^{inx}.$$ In particular, $$\sum\limits_{k=-\infty}^\infty f(2k \pi) ~=~ \sum\limits_{n=-\infty}^\infty \varphi(n).$$ More generally, $$\sum\limits_{k=-\infty}^\infty f(k \beta) ~=~ \alpha \sum\limits_{n=-\infty}^\infty \varphi(n\alpha) ~~~~~\text{if $\alpha > 0, \beta > 0, \alpha \beta = 2\pi$.}$$ What does this last equation say about the limit, as $\alpha \rightarrow 0$, of the right-hand side (for "nice" functions, of course) ? Is this in agreement with the inversion theorem ?
I struggle to see how it meshes with the inversion theorem. I guess I have not quite developed intuition yet. Could anyone share his thoughts about the "What does this last equation say about the limit" bit of the question plz ?
After much thought, I believe I got a solution :
Observe that $\alpha \sum\limits_{n = -\infty}^\infty \varphi(n \alpha)$ is a Riemann sum : $\alpha$ is the lenght of the interval and $\varphi(n\alpha)$ is the evaluation of $\varphi$ on this interval.
If $\alpha \rightarrow 0$, we obtain $\int_{-\infty}^\infty \varphi(x) \; dx$.
Now, as $\alpha \rightarrow 0$ and we must have $\beta \rightarrow \infty$ since $\alpha\beta = 2\pi$. The left-hand side is therefore $$ \sum\limits_{k=-\infty}^\infty f(k \beta) = f(0)$$ since for $\beta$ big enough we have that $f(k \beta) = 0$ for every $k \neq 0$ (here we assume that by 'nice functions' we mean to the very least that $f$ vanishes at infinity).
To sum up, we've got $$ f(0) ~=~ \int_{-\infty}^\infty \varphi(x) \; dx.$$ That is to say $$ f(0) ~=~ \int_{-\infty}^\infty \varphi(x)e^{0} \; dx,$$ which is in agreement with the inversion theorem.