LIPIcs.ITCS.2022.118.pdf
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In this paper we develop efficient randomized algorithms to solve the black-box reconstruction problem for polynomials over finite fields, computable by depth three arithmetic circuits with alternating addition/multiplication gates, such that output gate is an addition gate with in-degree two. Such circuits naturally compute polynomials of the form G×(T₁ + T₂), where G,T₁,T₂ are product of affine forms computed at the first layer in the circuit, and polynomials T₁,T₂ have no common factors. Rank of such a circuit is defined to be the dimension of vector space spanned by all affine factors of T₁ and T₂. For any polynomial f computable by such a circuit, rank(f) is defined to be the minimum rank of any such circuit computing it. Our work develops randomized reconstruction algorithms which take as input black-box access to a polynomial f (over finite field 𝔽), computable by such a circuit. Here are the results. - [Low rank]: When 5 ≤ rank(f) = O(log³ d), it runs in time (nd^{log³d}log |𝔽|)^{O(1)}, and, with high probability, outputs a depth three circuit computing f, with top addition gate having in-degree ≤ d^{rank(f)}. - [High rank]: When rank(f) = Ω(log³ d), it runs in time (ndlog |𝔽|)^{O(1)}, and, with high probability, outputs a depth three circuit computing f, with top addition gate having in-degree two. Prior to our work, black-box reconstruction for this circuit class was addressed in [Amir Shpilka, 2007; Karnin and Shpilka, 2009; Sinha, 2016]. Reconstruction algorithm in [Amir Shpilka, 2007] runs in time quasi-polynomial in n,d,|𝔽| and that in [Karnin and Shpilka, 2009] is quasi-polynomial in d,|𝔽|. Algorithm in [Sinha, 2016] works only for polynomials over characteristic zero fields. Thus, ours is the first blackbox reconstruction algorithm for this class of circuits that runs in time polynomial in log |𝔽|. This problem has been mentioned as an open problem in [Ankit Gupta et al., 2012] (STOC 2012). In the high rank case, our algorithm runs in (ndlog|𝔽|)^{O(1)} time, thereby significantly improving the existing algorithms in [Amir Shpilka, 2007; Karnin and Shpilka, 2009].
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