What about squaring? We have
$$ \left(\sum_{n\geq 0}x^{n^2}\right)^{2} = \sum_{n\geq 0}r_2(n)\,x^n $$
where
$$ r_2(n) = \left|\left\{(a,b)\in\mathbb{N}^2: a^2+b^2 = n\right\}\right| $$
is a nice arithmetic function. For instance, $\sum_{n=0}^{N}r_2(n)$ is the number of lattice points with non-negative coordinates inside the circle $x^2+y^2=N$, but also the coefficient of $x^N$ in
$$ \frac{1}{1-x}\left(\sum_{n\geq 0}x^{n^2}\right)^{2} = \sum_{N\geq 0}\left(\sum_{n=0}^{N}r_2(n)\right) x^N. $$
By Gauss circle problem with Voronoi bound we have that $\sum_{n=0}^{N}r_2(n)=\frac{\pi N}{4}+O(N^{1/3})$, hence $x=1$ is a double pole of the previous function and the first term of its Laurent expansion around $x=1$ is given by $\frac{\pi}{4(1-x)^2}$. By multiplying by $(1-x)^2$ and taking the limit as $x\to 1^-$ we get:
$$ \lim_{x\to 1^-}\,(1-x)\left(\sum_{n\geq 0}x^{n^2}\right)^2 = \frac{\pi}{4} $$
and the claim easily follows.
It is interesting to point out that the same approach shows that, for any $k\geq 2$,
$$ \lim_{x\to 1^-}(1-x)\left(\sum_{n\geq 0}x^{n^k}\right)^k $$
is exactly the (hyper-)volume enclosed by $x_1\geq 0,x_2\geq 0,\ldots x_k\geq 0$ and $x_1^k+x_2^k+\ldots+x_k^k = 1$, that can be computed in the following way: if we assume that $X_1,\ldots,X_k$ are i.i.d. random variables with uniform distribution over $(0,1)$, the PDF of $X_i$ is supported on $(0,1)$ and given by $f(t)=\frac{1}{k} t^{1/k-1}$. To compute the previous volume, it is enough to compute the characteristic function of $X_i$, take its $k$-th power, consider the inverse Fourier transform and integrate it over $(0,1)$ to get the probability that $X_1^k+\ldots+X_k^k\leq 1.$