# For which $r \in \mathbb R$ is the series $S(r)$ finite?

For each $$r \in \mathbb R$$ we let $$L_r := \left\{ \begin{pmatrix} a+cr \\ b+dr \\ c \\d \end{pmatrix} : a,b,c,d \in \mathbb Z \right\}, \quad W:= \left\{ \begin{pmatrix} 0 \\ 0 \\ x_3 \\ x_4 \end{pmatrix} : x_3,x_4 \in \mathbb R \right\}$$ and $$L^*_r := L_r \setminus W.$$

Now we consider the series $$S(r):= \sum_{x \in L^*_r} E_1(2 (x_1^2+x_2^2)) \exp ( (x_1^2+x_2^2) - (x_3^2+x_4^2)).$$ Here $$E_1 : (0, \infty) \to (0,\infty)$$ is the exponential integral $$E_1(s):=\int_1^\infty \exp(-ts) \frac{dt}{t} = \int_s^\infty \exp(-t) \frac{dt}{t}.$$

My question: For which $$r \in \mathbb R$$ is $$S(r)$$ finite?

My partial answer: It's quite easy to see that $$S(r)$$ is fintie for $$r \in \mathbb Q$$. But that's all I've found out so far.

Happy: I would already be happy if you could show for a single $$r \in \mathbb R \setminus \mathbb Q$$ (you pick it!) whether $$S(r)$$ converges or diverges.

Some facts: We have $$S(r) = \int_1^\infty \left( \sum_{x \in L^*_r} \exp \left( (1-2t)(x_1^2+x_2^2) - (x_3^2+x_4^2) \right)\right) \frac{dt}{t}.$$ Further, we have $$L_r^*=L_r \setminus \{0\}$$ iff $$r \in \mathbb R \setminus \mathbb Q$$.

Estimates for $$E_1$$:

In case they help: For $$s>0$$ we have $$\frac{e^{-s}}{s+1} < E_1(s) < \frac{s+1}{s+2} \frac{e^{-s}}{s} < \frac{e^{-s}}{s}.$$

Proof for rational $$r$$: Since I was asked in the comments to provide a proof for rational $$r$$ here it is. If $$r$$ is rational the set $$\{ a+br : a,b \in \mathbb Z \}$$ is a discrete subset of $$\mathbb R$$. Hence $$\varepsilon := \min(\{2(x_1^2+x_2^2) : x \in L_r^*\}) > 0$$ exists. Now we make use of $$E_1(s) \le \frac{\exp(-s)}{s}.$$ We have $$S(r) \le \sum_{x \in L^*_r} \frac{\exp(-2 (x_1^2+x_2^2))}{2 (x_1^2+x_2^2)} \exp ( (x_1^2+x_2^2) - (x_3^2+x_4^2))\\ \le \frac{1}{\varepsilon} \sum_{x \in L^*_r} \exp(-(x_1^2+x_2^2+x_3^2+x_4^2))\\ \le \frac{1}{\varepsilon} \sum_{x \in L_r} \exp(-||x||^2) < \infty.$$

• What's the context of such a complex expression? What have you tried for irrational $r$? Please see How to ask a good question. – Saad Jun 25 at 11:27
• What thingies are $x_1$ and $x_2$? – Han de Bruijn Jun 25 at 19:30
• @Saad The context is actually a quite complex one. I don't think that it is accessible to most of the readers here and I didn't want to scare them away. I'm examining a certain kind of theta series related to Kudla Green functions of Hilbert modular surfaces corresponding to real quadratic number fields. I have tried quite some stuff myself. The latest approach was to adapt the series to be able to use Poisson summation. But it didn't work out so far. You can also see another approach I took when you have a look for my question called "Generalization of the integral test for convergence". – principal-ideal-domain Jun 26 at 13:22
• @HandeBruijn For $x \in \mathbb R^4$ I call $x_1,x_2,x_3,x_4 \in \mathbb R$ the four coordinates. – principal-ideal-domain Jun 26 at 13:23
• @TheSimpliFire You are interested in a proof or do you think the statement is wrong? If you are interested in a proof I can write my thoughts down but the margin of this comment sections might be to small. – principal-ideal-domain Jun 26 at 18:08

Let $$r \in \mathbb{R} - \mathbb{Q}$$. Write $$||x||_1^2 := x_1^2 + x_2^2$$ and $$||x||_2^2 := x_3^2 + x_4^4$$. Consider two regimes, $$||x||_1 > 1$$ and $$||x||_1 \leq 1$$. Your reasoning for $$r \in \mathbb{Q}$$ basically handles the first regime. It shows that the contribution of the first regime is at most $$\sum_{\substack{x \in L_r \\ ||x||_1 > 1}} \exp(-||x||_1^2 - ||x||_2^2) = \sum_{c, d \in \mathbb{Z}} \exp(-c^2 - d^2) \sum_{a, b \in \mathbb{Z}} \exp(-(a+cr)^2 - (b+dr)^2).$$ For each fixed $$c, d$$, the sum over $$a, b$$ is finite and indeed bounded independent of $$c, d$$. The overall contribution in this case is hence finite.
Now consider the second regime. You certainly need better estimates for $$E_1(s)$$ for $$0 \leq s \leq 1$$, since the two you used are not asymptotically sharp. We have $$-E_1(s)/\log(s) \to 1$$ as $$s \to 0^+$$, so we may as well replace your $$E_1(s)$$'s with $$\log(s)$$ in this regime. The contribution is hence essentially $$\sum_{\substack{x \in L_r \\ ||x||_1 \leq 1}} -\log(2||x||_1^2) \exp(||x||_1^2 - ||x||_2^2) \approx \sum_{\substack{x \in L_r \\ ||x||_1 \leq 1}} -\log(||x||_1^2) \exp(-||x||_2^2).$$ For each value of $$c, d \in \mathbb{Z}$$, there is going to be basically one value of $$a, b \in \mathbb{Z}$$ for which $$||x||_1 \leq 1$$, roughly $$a = -\lfloor cr\rfloor$$ and $$b = -\lfloor dr\rfloor$$. So, think of $$a, b$$ as functions of $$c, d$$. Heuristically, I'd expect $$x_1, x_2$$ to be uniformly distributed mod $$1$$. In that case, $$||x||_1$$ is roughly uniformly distributed. So the contribution is essentially $$-\sum_{c, d \in \mathbb{Z}} \exp(-c^2-d^2) \log(R^2)$$ where $$R \sim U[0, 1]$$. (This is certainly not rigorous.) Let $$s = \sqrt{c^2 + d^2}$$ and consider the contributions for $$n \leq s \leq n+1$$. There should be roughly $$\pi(n+1)^2 - \pi n^2 \approx n$$ pairs $$(c, d)$$ with such an $$s$$. They contribute essentially $$-e^{-n^2} \sum_{i=1}^n \log(R_i)$$ where $$R_i$$ is sampled uniformly on $$[0, 1]$$ to the sum. Now $$\log(R_i)$$ has finite non-zero expected value and variance, so the sum should be roughly normal with mean roughly like $$n$$ and variance roughly like $$n^2$$. These contributions will hence not be able to beat the $$e^{-n^2}$$ decay rate, so the sum will converge.