Unique Multilinear Extensions of Polynomials over the V-Dimensional Hypercube

July 07, 2024

Univariate vs Multivariate Extensions

Univariate Low-Degree Extension

  • Given a vector m=(m1,,mn)Fpnm = (m_1,\dots,m_n) \in \mathbb{F}_p^n, define a set of coordinate pairs ((0,m1)),,(n1,mn))((0,m_1)),\dots,(n-1,m_n)) specifying the function f:{0,,n1}Fpf: \{0,\dots,n-1\} \rightarrow \mathbb{F}_p.
  • Interpolate the coordinate pairs with a polynomial qm:FpFpq_m: \mathbb{F}_p \rightarrow \mathbb{F}_p such that qm(i)=mi+1q_m(i) = m_{i+1} for all i{0,,n1}i \in \{0,\dots,n-1\} by applying each value as a weight in a linear combination of Lagrange basis polynomials {L0,,Ln1}\{L_0,\dots,L_{n-1}\} for the nodes {0,,n1}\{0,\dots,n-1\}
    Pq(x)=i=0n1mi+1Li(x)P_q(x)=\sum^{n-1}_{i=0} m_{i+1} \cdot L_{i}(x)
    Li(x)=j=0,jin1xxjxixjL_i(x)= \prod_{j=0, j\neq i}^{n-1} \frac{x-x_j}{x_i-x_j}
  • The univariate low degree extension of ff is qmq_m. It is the unique degree n1\leq n-1 polynomial that agrees with ff at all x{0,,n1}x \in \{0,\dots,n-1\} - there can be no other degree n1\leq n-1 polynomial passing through the interpolated points.
  • The pp-dimensional vector
c=(qm(0),,qm(p))c = (q_m(0), \dots, q_m(p))

is the low degree extension encoding of mm.

  • f:{0,,n1}Fpf: \{0,\dots,n-1\} \rightarrow \mathbb{F}_p and qm:FpFpq_m: \mathbb{F}_p \rightarrow \mathbb{F}_p are both univariate functions.

Multivariate Functions Over the vv-Dimensional Hypercube

  • We can extend the concept of extensions to multivariate functions. Let
    f:{0,1}vFf: \{0,1\}^v \rightarrow \mathbb{F}
    • The domain of ff is the vv-dimensional hypercube, or the set of all vv-bit binary strings - ff accepts vv variables (x1,,xv)(x_1,\dots,x_v) such that xi{0,1}x_i\in \{0,1\}.
  • There are 2v2^v possible values that can be represented by the domain of a vv-variate polynomial where each variable xi{0,1}x_i\in\{0,1\}.
    • The domain of the vv-dimensional hypercube is {0,1}v={0,,2v1}\{0,1\}^v = \{0,\dots,2^v-1\}.
    • For a univariate polynomial with domain size nn, a polynomial over the vv-dimensional hypercube will have the same domain size if v=log2(n)v = log_2(n).
      • {0,1}log2(n)={0,,n1}|\{0,1\}^{log_2(n)}| = |\{0,\dots,n-1\}|
  • We have observed that there is a unique extension of degree n1\leq n-1 for univariate functions defined over the domain {0,,n1}\{0,\dots,n-1\}. Similarly, there is a unique extension of total degree 1\leq 1 for multivariate functions defined over the domain {0,1}v\{0,1\}^v.
    • A polynomial is multilinear if it is linear in each of its variables when all other variables are held fixed. In other words, each variable in the polynomial has a degree of at most 1.
  • A multivariate function f:{0,1}vFpf: \{0,1\}^v \rightarrow \mathbb{F}_p over the domain {0,1}v\{0,1\}^v has a unique multilinear extension f~:FvF\tilde{f}: \mathbb{F}^v \rightarrow \mathbb{F}, such that
    x{0,1}v(f~(x)=f(x))\forall x\in\{0,1\}^v (\tilde{f}(x) = f(x))
  • f~\tilde{f} is vv-variate and multilinear, so the total degree of f~\tilde{f} is v\leq v
    • The univariate extension of a polynomial with domain size nn has degree n1\leq n-1, so the degree is linear in terms of the domain size (O(n))(O(n))
    • The multilinear extension of a polynomial with domain size n=2vn = 2^v has total degree v\leq v, so the total degree is logarithmic in terms of the domain size O(v)=O(log2(2v))=O(log2(n))O(v) = O(log_2(2^v)) = O(log_2(n))
  • Multilinear and ultra low total degree multivariate polynomials are especially useful for fast verification of interactive proofs

Distance Amplifying Encodings

  • Given two functions f:{0,1}vFpf: \{0,1\}^v \rightarrow \mathbb{F_p} and f:{0,1}vFpf': \{0,1\}^v \rightarrow \mathbb{F_p} with unique multilinear extensions f~:FpvFp\tilde{f}: \mathbb{F}_p^v \rightarrow \mathbb{F}_p and f~:FpvFp\tilde{f}': \mathbb{F}_p^v \rightarrow \mathbb{F}_p, if ff and ff' disagree at even one point, their extensions f~\tilde{f} and f~\tilde{f}' are distinct polynomials and will agree at vp\leq \frac{v}{p} of the pvp^v points in Fpv\mathbb{F}_p^v, or pv1\leq p^{v-1} points.
    vppv=vpv1\frac{v}{p} \cdot p^v = v \cdot p^{v-1}
  • P=f~f~P = \tilde{f} - \tilde{f}' is a vv-variate polynomial with total degree v\leq v with zeroes at each point where f~\tilde{f} and f~\tilde{f}' agree. By Schwartz-Zippel, a vv-variate polynomial of total degree v\leq v has roots at v/p\leq v/p out of the pvp^v possible values xFpvx \in \mathbb{F}^v_p
    PrxFpv[P(x)=0]vFp\Pr_{x \in \mathbb{F}^v_p}[P(x) = 0]\leq \frac{v}{|\mathbb{F}_p|}
  • So PP has less than vppv=vpv1\frac{v}{p} \cdot p^v = v \cdot p^{v-1} roots and f~f~\tilde{f} - \tilde{f}' agree at vpv1\leq v \cdot p^{v-1} values of xFpvx \in \mathbb{F}^v_p
  • Evaluating the multilinear extension f~(x)\tilde{f}(x) for all xFpx\in \mathbb{F}_p gives us a distance amplifying encoding of ff. Since f~\tilde{f} and a different polynomial f~\tilde{f}' can agree on at most a v/pv/p fraction of points, they are distance amplifying as long as the field is chosen such that p>vp>v.

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