I have the following integral:
$$\displaystyle \int_{\mathbb{R}^2} \left( \int_{\mathbb{R}^2} \frac{J_{1}(|\alpha|)J_{1}(|k- \alpha|)}{|\alpha||k-\alpha|} \ \mathrm{d}\alpha \right)^2 \ \mathrm{d}k,$$
where both $\alpha$ and $k$ are vectors in $\mathbb{R}^2$, with $k \neq 0$, and $J_{\nu}$ denotes the Bessel function of the first kind. I'm having some trouble with the best way to approach this integral. If we focus on the inner integral first, then using the fact that for sufficiently large, positive $z$ we have $|J_{\nu}(z)| \leqslant C|z|^{-1/2},$ then the inner integral can be reduced to
$$\displaystyle \int_{\mathbb{R}^2} |\alpha|^{-3/2}|k-\alpha|^{-3/2} \ \mathrm{d}\alpha.$$
However, as can be seen in this answer, this integral is $O(|k|^{-1})$, which, after squaring, is clearly not integrable over all $|k| \geqslant 1$ after switching to polar co-ordinates (obviously not including $0$ in the lower limit of the outer integral). We would need an estimate of at least $O(|k|^{-1 - \epsilon})$ for any $\epsilon > 0$ to guarantee convergence of the outer integral.
One idea might be to try to bring the outer integral inside (though one would need to justify interchanging the order of integration). Using the asymptotics for the Bessel functions gives a product of cosines, and then one can use polar co-ordinates (taking $r = |\alpha|$). This would cancel out the $|\alpha|$ in the denominator, but then the $|k-\alpha|$ terms get very messy, which seems to make things worse. The Bessel functions appear to cause the most trouble. Does anyone have any ideas on how to proceed?
One idea is to notice (as someone suggested in the comments) that the above is the $L^2$ norm of a convolution, and also that (up to a constant) we have
$$\displaystyle f(\xi) = \frac{J_{d/2}(|\xi|)}{|\xi|^{d/2}} = \mathcal{F}(\chi)(\xi),$$
where $\chi$ is the characteristic function of the unit ball in $\mathbb{R}^d$. It can be shown that $f \in L^2(\mathbb{R}^d)$ and even $L^{p}(\mathbb{R}^d)$ for any $p \geqslant 2$. This lets us write the entire expression as
$$\|f \ast f\|_2^2 = \|\mathcal{F}(\chi) \ast \mathcal{F}(\chi)\|_2^2,$$
but unfortunately there is no kind of convolution theorem for functions on $L^2(\mathbb{R}^d)$ that I am aware of, without going into the theory of distributions. Moreover, $f$ does not even belong to $S(\mathbb{R}^d)$ for any $d$, so we cannot say much about the convolution. Thus, the problem is equivalent to asserting the finiteness of the above norm, $\|f \ast f\|_2$. If anyone has any ideas on how else the problem could be approached, then I would be very keen to hear about them.
for the other interval, the series expansion of the bessel function should do the job
– tired Feb 09 '17 at 16:41