Update: Initially the question was posted for $a = 1$. Now it has been generalized for any real $a > 0$
What is known about the distribution of the sum of the binomial coefficients over multiple of squares? My experimental data seems to suggest that for a given positive real $a > 0$ $$ s_{n,a} = \sum_{1\leq \lfloor ak^2 \rfloor\leq n}{n\choose \lfloor ak^2 \rfloor}= {n\choose \lfloor 1^2 a \rfloor} + {n\choose \lfloor 2^2 a \rfloor} + \cdots + {n\choose \lfloor r^2 a \rfloor} \approx \frac{2^n}{\sqrt{2an}} $$
Clearly the sum will be dominated by the term closest to the central binomial coefficient which in this case is the square nearest to $n/2$. What I found interesting is the shape of the histogram of the distribution of the ratios of the actual sum to its asymptotic estimate i.e. $\dfrac{s_n \sqrt{2an}}{2^n}$ are similar for all $a$ and look like an acr-sine distribution as mentioned in the comments.
Histogram of distribution for $a = 1$
Question 1: Why does it have an arc-sine like distribution?
Question 2 Where does the spikes occur? E.g. for $a = 1$, the spikes occur roughly at $1 \pm 1/6$.
Related question: What is the sum of the binomial coefficients $n \choose p$ over prime numbers?

This is a part of ongoing research with Nilotpal Kanti Sinha. The answer does not explain fully why we have such distribution, but it will help understanding the distribution of the values of $\frac{s_n{\sqrt{2an}}}{2^n}$. I used $S_{n,a}$ notation to include its dependence on $a$.
Theorem 1
Corollary 1
The first harmonic gives a good approximation of the magnitude of the oscillation $1\pm 2e^{-\frac{\pi^2}{4a}}$.
Proof of Theorem 1
Lemma 1
Lemma 2[Hoeffding's Inequality]
We apply Lemma 1 and Lemma 2 with $h=5\log n$. Let $g_0(n)=\frac{\beta_n}{\sqrt n}$ and $g_k(n)=\frac{\frac n2-\left\lfloor a\left(\left\lfloor \sqrt{\frac{n}{2a}}\right\rfloor +k\right)^2\right\rfloor}{\sqrt n}$ for $k\in\mathbb{Z}$ and $|k|\leq \frac6a \log n$. $$ \frac{S_{n,a}\sqrt{2an}}{2^n}=\sum_{|k|\leq \frac6a\log n} \frac{2\sqrt{a}}{\sqrt{\pi}} e^{-2(g_k(n))^2}\left(1+O\left(\frac{\log^3 n}{\sqrt n}\right)\right)+O\left(e^{-(\log n)^2} \right). $$ Since $g_k(n)=\frac{\beta_n}{\sqrt n }- k\sqrt{2a} + O\left(\frac{k^2}{\sqrt n}\right) = \frac{\beta_n}{\sqrt n}-k\sqrt{2a}+O\left(\frac{\log^2 n}{\sqrt n}\right)$, we have by the mean value theorem, $$ e^{-2(g_k(n))^2} = e^{-2\left(\frac{\beta_n}{\sqrt n} - k\sqrt{2a}\right)^2} + O\left(\frac{\log^2 n}{\sqrt n} ke^{-ak^2} \right). $$ Summing these over $k$ and applying Lemma 2 again gives \begin{align*} \frac{S_{n,a}\sqrt{2an}}{2^n}&=\sum_{|k|\leq \frac 6a\log n} \frac{2\sqrt a}{\sqrt{\pi}} \exp\left\{-2\left(\frac{\beta_n}{\sqrt n} -k\sqrt{2a}\right)^2\right\}+O\left( \frac{\log^3 n}{\sqrt n}\right)\\ &=\frac{2\sqrt a}{\sqrt{\pi}}\sum_{k\in\mathbb{Z}} \exp\left\{-2\left(\frac{\beta_n}{\sqrt n} +k\sqrt{2a}\right)^2\right\}+O\left( \frac{\log^3 n}{\sqrt n}\right). \end{align*} Hence, Theorem 1 follows.
Let $c>0$ and define $$ f(t)=e^{-\pi\left(\frac{x+t}c\right)^2}. $$ Then its Fourier transform $\hat{f}(\xi)$ is $$ \hat{f}(\xi)=\int_{-\infty}^{\infty} f(t)e^{-2\pi i t \xi} \ dt = ce^{2\pi i x\xi}e^{-\pi(c\xi)^2}. $$ Applying Poisson summation formula, we obtain for any $x\in\mathbb{R}$, $$ \sum_{k\in \mathbb{Z}} e^{-\pi\left(\frac{x+k}c\right)^2}=c\sum_{k\in\mathbb{Z}} e^{2\pi i xk}e^{-\pi(ck)^2}=c\left(1+\sum_{k=1}^{\infty} 2e^{-\pi(ck)^2} \cos 2\pi kx\right). $$ Putting $c=\frac{\sqrt{\pi}}{2\sqrt a}$, Corollary 1 follows.