Keyboard shortcuts

Press or to navigate between chapters

Press S or / to search in the book

Press ? to show this help

Press Esc to hide this help

Small Characteristic Sum-Check

The following proofs occured originally in "Power Sums over Finite Subspaces of a Field [BC99], but was included in the Aurora paper [BSCRSVW18] in which this sumcheck was introduced. The following details an efficient sumcheck over subspaces of : vector spaces over spanned by a set of vectors/elements . These techniques are efficient when is small, for instance, .

Let be an affine subspace of and let , then:

In other words, summing any sufficiently small power of elements in an affine subspace of yields zero.

The generalized derivative of a polynomial is defined as:

For we inductively define the derivative in the direction as:

Observe that the summation is over the finite field , not the whole field , where as the "direction" is from the whole field. In other words, the direction is a vector (extension field element), and we consider all steps (scalar multiples) in the direction of this vector. When there are multiple directions, we consider the sum over all the combinations:

The relevance to the question at hand is clear: if are a basis, then:

Which is exactly the sum of over all elements in the affine space .

Next, we define a notion of "weight". The trick is going to be induction over this "metric": it measures the "size" of a polynomial and we will prove by induction that the statement holds up to a given "size", which happens to contain all polynomials of degree less than .

The -nary digit sum of a number is the sum of the digits in its -nary representation. Let and write it as:

Where . Then the -nary digit sum of is defined as:

So, we the induction is going to be over the "size" of the exponents in the polynomial, where "size" is measured by the -nary digit sum of the degree of the polynomial. We introduce the notion of "weight" for a polynomial, which is simply the maximum -nary digit sum of its exponents of any (non-zero) monomial.

The weight of a polynomial is the maximum -nary digit sum of its exponents of any (non-zero) monomial. Let:

Where . Then:

Our first claim is that applying reduces the "weight" of any polynomial:

With the max simply being there, because the weight of the polynomial is always non-negative.

We also claim that if , then .

Let

The rewrites are as follows:

  1. Expanding the definition of .
  2. Is the binomial expansion of some .
  3. Rearranging sums.
  4. A
  5. Removes the in the exponents: since , for all .
  6. When then :

The theorem trivially extends to polynomials of degree less than : since the sum over the affine space of every monomial of degree less than is zero, then so must the sum of the sum of monomials: the sum of the polynomial over the affine space: