Abstract
One can associate to any bivariate polynomial \(P(X,Y)\) its Newton polygon. This is the convex hull of the points \((i,j)\) such that the monomial \(X^i Y^j\) appears in \(P\) with a nonzero coefficient. We conjecture that when \(P\) is expressed as a sum of products of sparse polynomials, the number of edges of its Newton polygon is polynomially bounded in the size of such an expression. We show that this so-called \(\tau \)-conjecture for Newton polygons, even in a weak form, implies that the permanent polynomial is not computable by polynomial-size arithmetic circuits. We make the same observation for a weak version of an earlier real \(\tau \)-conjecture. Finally, we make some progress toward the \(\tau \)-conjecture for Newton polygons using recent results from combinatorial geometry.
Similar content being viewed by others
Notes
Here and in [17], the term sparse refers to the fact that we measure the size of a polynomial \(f_{ij}\) by the number of its monomials.
References
M. Agrawal and V. Vinay. Arithmetic circuits: A chasm at depth four. In Proc. 49th IEEE Symposium on Foundations of Computer Science, pages 67–75, 2008.
O. Bílka, K. Buchin, R. Fulek, M. Kiyomi, Y. Okamoto, S.I. Tanigawa, and C.D. Tóth. A tight lower bound for convexly independent subsets of the Minkowski sums of planar point sets. Electr. J. Comb., 17(1), 2010.
L. Blum, F. Cucker, M. Shub, and S. Smale. Algebraic settings for the problem “\(\text{ P } \ne \text{ NP }?\)”. In J. Renegar, M. Shub, and S. Smale, editors, The Mathematics of Numerical Analysis, volume 32 of Lectures in Applied Mathematics, pages 125–144. American Mathematical Society, 1996.
L. Blum, M. Shub, and S. Smale. On a theory of computation and complexity over the real numbers: NP-completeness, recursive functions and universal machines. Bulletin of the American Mathematical Society, 21(1):1–46, July 1989.
A. Borodin and S. Cook. On the number additions to compute specific polynomials. SIAM Journal on Computing, 5(1):146–157, 1976.
P. Bürgisser. Completeness and Reduction in Algebraic Complexity Theory. Number 7 in Algorithms and Computation in Mathematics. Springer, 2000.
P. Bürgisser. On defining integers and proving arithmetic circuit lower bounds. Computational Complexity, 18:81–103, 2009. Conference version in STACS 2007.
X. Chen, N. Kayal, and A. Wigderson. Partial derivatives in arithmetic complexity and beyond. Foundations and Trends in Theoretical Computer Science, 6(1):1–138, 2011.
F. Eisenbrand, J. Pach, T. Rothvoß, and N.B. Sopher. Convexly independent subsets of the Minkowski sum of planar point sets. Electr. J. Comb., 15(1), 2008.
I. Fischer. Sums of like powers of multivariate linear forms. Mathematics Magazine, 67(1):59–61, 1994.
S. Gao. Absolute irreducibility of polynomials via Newton polytopes. Journal of Algebra, 237(2):501–520, 2001.
A. Gupta, P. Kamath, N. Kayal, and R. Saptharishi. Arithmetic circuits: A chasm at depth three. Electronic Colloquium on Computational Complexity (ECCC), 20, 2013.
N. Halman, S. Onn, and U. Rothblum. The convex dimension of a graph. Discrete Applied Mathematics, 155:1373–1383, 2007.
P. Hrubeš. On the Real \(\tau \)-Conjecture and the Distribution of Complex Roots. Theory of Computing, 9(10):403–411, 2013.
N. Kayal. An exponential lower bound for the sum of powers of bounded degree polynomials. Electronic Colloquium on Computational Complexity (ECCC), 19, 2012.
P. Koiran. Hilbert’s Nullstellensatz is in the polynomial hierarchy. Journal of Complexity, 12(4):273–286, 1996. Long version: DIMACS report 96–27.
P. Koiran. Shallow circuits with high-powered inputs. In Proc. Second Symposium on Innovations in Computer Science (ICS 2011), 2011. http://arxiv.org/abs/1004.4960
P. Koiran. Arithmetic circuits: the chasm at depth four gets wider. Theoretical Computer Science, (448):56–65, 2012.
A.M. Ostrowski. Über die Bedeütüng der Theorie der konvexen Polyeder für die formale Algebra. Jahresberichte Deutsche Math. Verein, 20:98–99, 1921.
A. Shpilka and A. Yehudayoff. Arithmetic circuits: A survey of recent results and open questions. Foundations and Trends in Theoretical Computer Science, 5(3–4), 2010.
M. Shub and S. Smale. On the intractability of Hilbert’s Nullstellensatz and an algebraic version of “P=NP”. Duke Mathematical Journal, 81(1):47–54, 1995.
S. Smale. Mathematical problems for the next century. Mathematical Intelligencer, 20(2):7–15, 1998.
B. Sturmfels. Polynomial equations and convex polytopes. The American Mathematical Monthly, 105(10):907–922, 1998.
K.J. Swanepoel and P. Valtr. Large convexly independent subsets of Minkowski sums. Electr. J. Comb., 17(1), 2010.
S. Tavenas. Improved bounds for reduction to depth 4 and depth 3. In Proc. 38th International Symposium on Mathematical Foundations of Computer Science (MFCS), 2013.
S. Tavenas. Bornes inférieures et supérieures pour les circuits arithmétiques. PhD thesis, 2014.
L. G. Valiant. Completeness classes in algebra. In Proc. 11th ACM Symposium on Theory of Computing, pages 249–261, 1979.
L. G. Valiant. Reducibility by algebraic projections. In Logic and Algorithmic (an International Symposium held in honour of Ernst Specker), pages 365–380. Monographie \(n^{o}\) 30 de L’Enseignement Mathématique, 1982.
Acknowledgments
Proposition 1 arose from a discussion with Mark Braverman, and an improvement was suggested by an anonymous referee. We thank the three referees for suggesting several improvements in the presentation of the paper. This paper would not exist without Mike Shub’s work on the \(\tau \)-conjecture. For this and all his other contributions, it is a pleasure to dedicate it to him. Happy 70th Birthday, Mike!
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by Teresa Krick and Jim Renegar.
The authors are supported by ANR Project CompA (code ANR-13-BS02-0001-01).
Appendix: Newton polygon of \(fg+1\)
Appendix: Newton polygon of \(fg+1\)
In this section we denote by \(0\) the point in the plane with coordinates \((0,0)\).
We give here (in Theorem 7) a linear upper bound assuming the following two properties:
-
(i)
The polynomials \(f\) and \(g\) have the same support, i.e., \({\mathrm {Mon}}(f)={\mathrm {Mon}}(g)\). We denote by \(\{p_0,\ldots ,p_{t-1}\}\) this common support.
-
(ii)
If \(f\) and \(g\) have a constant term, we assume without loss of generality that \(p_0=0\) and we add the following requirement: if \(p_j\) is an extremal point of \({\mathrm {conv}}(p_1,p_2,\ldots ,p_{t-1})\), then \(2p_j\) is not in the support of \(f\) and \(g\).
We do not know how to prove a linear upper bound assuming only (i). Condition (ii) is satisfied in particular when the points in \({\mathrm {Mon}}(f)={\mathrm {Mon}}(g)\) are convexly independent.
The interesting case, which we consider first, is when \(f\) and \(g\) have a constant term but \(fg+1\) has no constant term. As explained previously, we assume that \(p_0\) corresponds to the constant terms of \(f\) and \(g\), i.e., \(p_0=0\). Under these hypotheses, we have the following result.
Proposition 2
Under assumptions (i) and (ii),
where \((p_i)_{i \in I}\) is the subset of those monomials in \({\mathrm {Mon}}(f)\) that appear in \(fg+1\) with a nonzero coefficient.
Proof
We first prove the inclusion from left to right. Since \(fg+1\) has no constant term, all monomials of \(fg+1\) are of the form \(p_i+p_j\), where \(i \ge 1\) or \(j \ge 1\). Consider first the case where \(i\) and \(j\) are both nonzero. If \(i=j\), then this monomial appears on the right-hand side, and if \(i \ne j\), then it is the middle point of two points (namely, \(2p_i\) and \(2p_j\)) appearing on the right-hand side. The remaining case is when \(i=0\) or \(j=0\). If, for example, \(j=0\), then we have \(p_i+p_j=p_i\), and we see from the definition of \(I\) that this monomial also appears on the right-hand side.
Now we prove the inclusion from right to left. Again by definition of \(I\), all the \(p_i\) with \(i \in I\) are monomials of \(fg+1\). Hence, it remains to show that
The left-hand side can be written as \({\mathrm {conv}}((2p_j)_{j \in J})\), where the \((p_j)_{j\in J}\) form a convexly independent subset of \(\{p_1,\ldots ,p_{t-1}\}\). Any monomial of the form \(2p_j\) with \(j \in J\) appears in \(fg+1\) with a nonzero coefficient because it can be obtained in a unique way by expansion of the product \(fg\). Assume indeed that \(2p_j=p_i+p_k\), with \(i \ne k\). Then \(p_j\) is the middle point of \(p_i\) and \(p_k\). If \(i \ge 1\) and \(k \ge 1\), this is impossible by construction of \(J\). If \(i=0\) or \(k=0\), this is also impossible by hypothesis (ii). We thus have \({\mathrm {conv}}((2p_j)_{j \in J}) \subseteq {\mathrm {Newt}}(fg+1)\), and the proof is complete. \(\square \)
We note that this proposition does not hold without assumption (ii), as shown by the following example. Take \(f=1+X^2Y+XY^2+(1/2)X^2Y^4+(1/2)X^4Y^2\) and \(g=-1+X^2Y+XY^2-(1/2)X^2Y^4-(1/2)X^4Y^2\). Then \(fg+1=2X^3Y^3-(1/2)X^6Y^6-(1/4)X^4Y^8-(1/4)X^8Y^4\). The monomial \(X^3Y^3\) is a vertex of \({\mathrm {Newt}}(fg+1)\) but is not of the form \(p_i\) or \(2p_j\) prescribed by Proposition 2.
Theorem 7
Under the same assumptions (i) and (ii) as previously, \({\mathrm {Newt}}(fg+1)\) has at most \(t+1\) edges, where \(t\) denotes the number of monomials of \(f\) and \(g\).
Proof
We continue to denote the common support of \(f\) and \(g\) by \(\{p_0,\ldots ,p_{t-1}\}\). If \(0\) does not belong to this support, then \({\mathrm {Newt}}(fg+1)\) is the convex hull of \(\{0\}\) and \({\mathrm {Newt}}(fg)\). Moreover, \({\mathrm {Newt}}(fg)={\mathrm {Newt}}(f)+{\mathrm {Newt}}(g)={\mathrm {conv}}(2p_0,\ldots ,2p_{t-1})\).
If \(0\) is in the support and \(fg+1\) has a constant term, then \({\mathrm {Newt}}(fg+1)={\mathrm {Newt}}(fg)\) has at most \(t\) edges (\(t\) and not \(2t\) since \(f\) and \(g\) have the same support).
In the remaining case (\(0\) is in the support but \(fg+1\) has no constant term), we need to use hypothesis (ii). This case is treated in Proposition 2. At first sight, it seems that \({\mathrm {Newt}}(fg+1)\) can have up to \(2(t-1)\) vertices, but the list of possible vertices can be shortened by picking a convexly independent subsequence. More precisely, write \({\mathrm {conv}}(2p_1,\ldots ,2p_{t-1},(p_i)_{i \in I})={\mathrm {conv}}((2p_j)_{j \in J},(p_k)_{k \in K})\), where \(J \subseteq \{1,\ldots ,t-1\}\) and \(K \subseteq I\) are chosen such that the points in this sequence are convexly independent. By the lemma that follows, \(| J \cap K| \le 2\). As a result, the number of points in the sequence is \(|J|+|K| = |J \cup K| + | J \cap K| \le (t-1)+2=t+1\). \(\square \)
Lemma 3
If \(p,\, q,\, r\) are three distinct nonzero points in the plane, then the six points \(p,\, q,\, r,\, 2p,\, 2q,\, 2r\) are not convexly independent.
This is clear from a picture and can be proved, for instance, by considering the four points \(0,\, p,\, q,\, r\). There are two cases:
-
1.
If these four points are convexly independent, assume, for instance, that \(pq\) is a diagonal of the quadrangle \(0prq\). Then the line \(pq\) separates \(0\) from \(r\). As a result, \(r \in {\mathrm {conv}}(p,q,2r)\).
-
2.
If the four points are not convexly independent, assume, for instance, that \(r \in {\mathrm {conv}}(0,p,q)\). In this case, \(2r \in {\mathrm {conv}}(2p,2q,r)\). \(\square \)
Rights and permissions
About this article
Cite this article
Koiran, P., Portier, N., Tavenas, S. et al. A \(\tau \)-Conjecture for Newton Polygons. Found Comput Math 15, 185–197 (2015). https://doi.org/10.1007/s10208-014-9216-x
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10208-014-9216-x