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Proceedings ArticleDOI

Non-commutative circuits and the sum-of-squares problem

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TLDR
It is shown that any non-commutative circuit computing an <i>ordered</i> non-Commutative polynomial can be efficiently transformed to a syntactically multilinear circuit computing that polynomials that is ordered.
Abstract
We initiate a direction for proving lower bounds on the size of non-commutative arithmetic circuits. This direction is based on a connection between lower bounds on the size of non-commutative arithmetic circuits and a problem about commutative degree four polynomials, the classical sum-of-squares problem: find the smallest n such that there exists an identity (x12+x22+•• + xk2)• (y1^2+y22+•• + yk2)= f12+f22+ ... +fn2, where each fi = fi(X,Y) is bilinear in X={x1,... ,xk} and Y={y1,..., yk}. Over the complex numbers, we show that a sufficiently strong super-linear lower bound on n in, namely, n ≥ k1+e with e >0, implies an exponential lower bound on the size of arithmetic circuits computing the non-commutative permanent.More generally, we consider such sum-of-squares identities for any M polynomial h(X,Y), namely: h(X,Y) = f12+f22+...+fn2.Again, proving n ≥ k1+e in for any explicit h over the complex numbers gives an exponential lower bound for the non-commutative permanent. Our proofs relies on several new structure theorems for non-commutative circuits, as well as a non-commutative analog of Valiant's completeness of the permanent.We proceed to prove such super-linear bounds in some restricted cases. We prove that n ≥ Ω(k6/5) in (1), if f1,..., fn are required to have integer coefficients. Over the real numbers, we construct an explicit M polynomial h such that n in (2) must be at least Ω(k2). Unfortunately, these results do not imply circuit lower bounds. We also present other structural results about non-commutative arithmetic circuits. We show that any non-commutative circuit computing an ordered non-commutative polynomial can be efficiently transformed to a syntactically multilinear circuit computing that polynomial. The permanent, for example, is ordered. Hence, lower bounds on the size of syntactically multilinear circuits computing the permanent imply unrestricted non-commutative lower bounds. We also prove an exponential lower bound on the size of non-commutative syntactically multilinear circuit computing an explicit polynomial. This polynomial is, however, not ordered and an unrestricted circuit lower bound does not follow.

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Book

Arithmetic Circuits: A Survey of Recent Results and Open Questions

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A deterministic polynomial time algorithm for non-commutative rational identity testing

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References
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Journal ArticleDOI

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TL;DR: A polynomial-time randomized algorithm for estimating the permanent of an arbitrary n × n matrix with nonnegative entries computes an approximation that is within arbitrarily small specified relative error of the true value of the permanent.
Proceedings ArticleDOI

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Journal ArticleDOI

Vermeidung von Divisionen.

TL;DR: In this article, it was shown that the use of divisions does not decrease the number of (*,/)-operations for multiplication of general matrices, and that multiplication of orthogonal matrices does not increase the computational complexity.