Reconstruction of depth-3, top fan-in two circuits over characteristic zero fields

TL;DR

This paper presents a polynomial-time randomized algorithm for reconstructing depth-3, top fan-in two arithmetic circuits over characteristic zero fields using blackbox access, advancing the understanding of circuit reconstruction in algebraic complexity.

Contribution

It introduces a novel reconstruction algorithm for $ ext{SigmaPiSigma}(2)$ circuits over characteristic zero fields, employing Sylvester Gallai theorems, which was previously unresolved.

Findings

Algorithm runs in polynomial time in n and d

Successfully reconstructs circuits with high probability

Extends circuit reconstruction techniques to characteristic zero fields

Abstract

Reconstruction of arithmetic circuits has been heavily studied in the past few years and has connections to proving lower bounds and deterministic identity testing. In this paper we present a polynomial time randomized algorithm for reconstructing $\Sigma\Pi\Sigma(2)$ circuits over $\mathbb{F}$ ($char(\mathbb{F})=0$), i.e. depth$-3$ circuits with fan-in $2$ at the top addition gate and having coefficients from a field of characteristic $0$. The algorithm needs only a blackbox query access to the polynomial $f \in \mathbb{F}[x_1,\ldots, x_n]$ of degree $d$, computable by a $\Sigma\Pi\Sigma(2)$ circuit $C$. In addition, we assume that "simple rank" of this polynomial (essential number of variables after removing gcd of the two multiplication gates) is bigger than a constant. Our algorithm runs in time $poly(n, d)$ and returns an equivalent $\Sigma\Pi\Sigma(2)$ circuit(with high probability). The problem of reconstructing $\Sigma\Pi\Sigma(2)$ circuits over finite fields was first proposed by Shpilka in [24]. The generalization to $\Sigma\Pi\Sigma(k)$ circuits, $k = O(1)$ (over finite fields) was addressed by Karnin and Shpilka in [15]. The techniques in these previous involve iterating over all objects of certain kinds over the ambient field and thus running time depends on size of the field $\mathbb{F}$. Their reconstruction algorithm uses lower bounds on the lengths of Linear Locally Decodable Codes with $2$ queries. In our settings, such ideas immediately pose a problem and we need new ideas to handle the case of the characteristic $0$ field $\mathbb{F}$. Our main techniques are based on the use of Quantitative Syslvester Gallai Theorems from the work of Barak et.al. [3] to find a small collection of subspaces to project onto. The heart of our paper lies in subtle applications of Quantitative Sylvester Gallai theorems to prove why projections w.r.t. these subspaces can be glued.