Motivation for proof of Berry-Esséen Theorem The proof of the Berry-Esseen theorem found in Terence Tao's notes (https://terrytao.wordpress.com/2010/01/05/254a-notes-2-the-central-limit-theorem/, Theorem 37) starts by "smoothing" the cumulative distribution cutoff function, by convolving with a function whose fourier transform is compactly supported.
First of all, what is the motivation for doing this?
Secondly, why not smooth the function by convolving with a compactly supported test function instead?
Any insights into the proof of Berry-Esseen would be appreciated.
 A: First of all, it is worth to mention that we really want to work with characteristic functions (Fourier transforms), since adding independent random variables corresponds to a plain multiplication (as opposed to convolutions). 
Smoothing the cdf $F$ by convolution with a nice function $H$ (which is equivalent to adding an independent random variable with a smooth cdf) gives the following: 


*

*The resulting cdf $G = F*H$ has bounded density. This allows to write for any smooth cdf $\widetilde G$ with the same mean
$$
G(x) - \widetilde G(x) = \frac{i}{2\pi} \int_{\mathbb{R}}\frac{\psi(t) - \widetilde\psi(t)}{t} e^{-itx} dt,\tag{1}
$$
where $\psi$ and $\widetilde\psi$ are the characteristic functions of $G$ and $\widetilde G$.

*Taking $\widetilde G = \Phi * H$, where $\Phi$ is the standard Gaussian cdf, we get from $(1)$
$$
\big(F - \Phi\big)*H(x) = \frac{i}{2\pi} \int_{\mathbb{R}}\frac{\varphi(t) - e^{-t^2/2}}{t}\omega(t) e^{-itx} dt,\tag{2}
$$
where $\varphi$ and $\omega$ are characteristic functions of $F$ and $H$. Since $\omega$ has finite support, the integral in $(2)$ is over a finite interval. This allows to write Taylor expansion for the characteristic function $\varphi$ with error terms admitting nice bounds in this interval. 

*There are now two errors: smoothing error (replacing $F$ by $G$) and normal approximation error, controlled by $(2)$. Adjusting the "window" $T$ (the width of support of $\omega$) increases one error and decrease another, so we can optimize the error.
If we took compactly supported $H$, not $\omega$, this could still increase smoothness of $F$. However, the analysis of characteristic functions (and, as I have explained, we want to analyze them rather than cdfs) would not be simplified, as explained in 2-3 above. 
