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# Basis for Circle FFT

The circle FFT algorithm outputs coefficients $c_j$ with respect to some basis $b_j^{(n)}(x, y)$ such that:

$p(x, y) = \sum_{j = 0}^{2^n - 1} c_j \cdot b_j^{(n)}(x, y)$

In the concrete example (covered in the [Algorithm section](/learn/S-two-book/how-it-works/circle-fft/algorithm)) of Circle FFT over twin-coset $D_3$, we saw that the algorithm computed the coefficient with respect to the following basis:

$b^{(3)}_j(x, y) = [1, x, \pi(x), x \cdot \pi(x), y, y \cdot x, y \cdot \pi(x), y \cdot x \cdot \pi(x)]$

Using induction on $n$, we can show that the Circle FFT algorithm outputs coefficients with respect to the following basis \[[Theorem 2, Circle STARKs](https://eprint.iacr.org/2024/278.pdf)]:

$b^{(n)}_j(x, y) := y^{j_0} \cdot x^{j_1} \cdot \pi(x)^{j_2} \cdot \pi^2(x)^{j_3} \cdots \pi^{n-2}(x)^{j_{n-1}}$

where $0 \leq j \leq 2^n - 1$ and $(j_0, \ldots, j_{n-1}) \in \{0, 1\}^n$ is the binary representation of $j$, i.e.,

$j = j_0 + j_1 \cdot 2 + \cdots + j_{n-1} \cdot 2^{n-1}$

# Dimension Gap

We will now explore the space of polynomials interpolated by the Circle FFT algorithm. Let the space spanned by the basis polynomials in $b^{(n)}(x, y)$ be $L'_N(F)$. The basis $b^{(n)}(x, y)$ has a total of $N=2^n$ elements and thus the dimension of the space $L'_N(F)$ is $N$. However, the space of bivariate polynomials over the circle curve is $L_N(F)$, which has dimension $N+1$ (as covered in the [section on polynomials over the circle](/learn/S-two-book/how-it-works/circle-polynomials/evals-and-poly#polynomials-over-the-circle)).

We can identify the missing highest total degree element in $L'_N(F)$ by examining the basis. The highest total degree element in basis $b^{(n)}(x, y)$ is:
$y \cdot x \cdot \pi(x) \cdot \pi^2(x) \cdot \pi^3(x) \cdots \pi^{n-2}(x)$

Using $deg(\pi^j(x) = 2^j)$, the highest degree of $X$ in the above term is:
$1 + 2 + 2^2 + 2^3 + \cdots + 2^{n-2} = 2^{n-1} - 1 = N/2 - 1$

Since the highest degree of $X$ in $L'_N(F)$ is $N/2 - 1$, we can represent the space $L'_N(F)$ as follows:

$L'_N(F) = F[x]^{ \leq N/2 - 1} + Y \cdot F[x]^{ \leq N/2 - 1}$

where $F[x]^{ \leq N/2 - 1}$ represents polynomials of degree at most $N/2 - 1$ with coefficients in $F$. Similarly, we can represent the space $L_N(F)$ as:

$L_N(F) = F[x]^{ \leq N/2} + Y \cdot F[x]^{ \leq N/2 - 1}$

Thus the space $L'_N(F)$ does not include the monomial $X^{N/2}$, which lies in the space $L_N(F)$. Therefore,

$L_N(F) = L'_N(F) + \langle X^{N/2} \rangle$

Since the space spanned by $X^{N/2}$ is same as the space spanned by the vanishing polynomial $v_n(x)$ which has degree $deg(v_n) = 2^{n-1} =N/2$, we can also write:

$L_N(F) = L'_N(F) + \langle v_n \rangle$

A consequence of this dimension gap is that we cannot interpolate some polynomials over the circle i.e. those with $X^{N/2}$. We will address how this dimension gap is handled within the FRI protocol in the upcoming sections.