Natacha Portier

Decidable and Undecidable Problems about Quantum Automata

We study the following decision problem: is the language recognized by a quantum finite automaton empty or nonempty? We prove that this problem is decidable or undecidable depending on whether recognition is defined by strict or nonstrict thresholds. This result is in contrast with the corresponding situation for probabilistic finite automata, for which it is known that strict and nonstrict thresholds both lead to undecidable problems.

A quantum lower bound for the query complexity of simon's problem

Simon in his FOCS’94 paper was the first to show an exponential gap between classical and quantum computation. The problem he dealt with is now part of a well-studied class of problems, the hidden subgroup problems. We study Simon’s problem from the point of view of quantum query complexity and give here a first nontrivial lower bound on the query complexity of a hidden subgroup problem, namely Simon’s problem. More generally, we give a lower bound which is optimal up to a constant factor for any Abelian group.

A Wronskian approach to the real τ-conjecture

According to the real ?-conjecture, the number of real roots of a sum of products of sparse univariate polynomials should be polynomially bounded in the size of such an expression. It is known that this conjecture implies a superpolynomial lower bound on the arithmetic circuit complexity of the permanent.In this paper, we use the Wronksian determinant to give an upper bound on the number of real roots of sums of products of sparse polynomials of a special form. We focus on the case where the number of distinct sparse polynomials is small, but each polynomial may be repeated several times. We also give a deterministic polynomial identity testing algorithm for the same class of polynomials.Our proof techniques are quite versatile; they can in particular be applied to some sparse geometric problems that do not originate from arithmetic circuit complexity. The paper should therefore be of interest to researchers from these two communities (complexity theory and sparse polynomial systems).

On the complexity of the multivariate resultant

The multivariate resultant is a fundamental tool of computational algebraic geometry. It can in particular be used to decide whether a system of n homogeneous equations in n variables is satisfiable (the resultant is a polynomial in the systems coefficients which vanishes if and only if the system is satisfiable). In this paper, we investigate the complexity of computing the multivariate resultant. First, we study the complexity of testing the multivariate resultant for zero. Our main result is that this problem is NP-hard under deterministic reductions in any characteristic, for systems of low-degree polynomials with coefficients in the ground field (rather than in an extension). In null characteristic, we observe that this problem is in the Arthur-Merlin class AM if the generalized Riemann hypothesis holds true, while the best known upper bound in positive characteristic remains PSPACE. Second, we study the classical algorithms to compute the resultant. They usually rely on the computation of the determinant of an exponential-size matrix, known as Macaulay matrix. We show that this matrix belongs to a class of succinctly representable matrices, for which testing the determinant for zero is proved PSPACE-complete. This means that improving Cannys PSPACE upper bound requires either to look at the fine structure of the Macaulay matrix to find an ad hoc algorithm for computing its determinant, or to use altogether different techniques.

Symmetric Determinantal Representation of Formulas and Weakly Skew Circuits

We deploy algebraic complexity theoretic techniques for constructing symmetric determinantal representations of formulas and weakly skew circuits. Our representations produce matrices of much smaller dimensions than those given in the convex geometry literature when applied to polynomials having a concise representation (as a sum of monomials, or more generally as an arithmetic formula or a weakly skew circuit). These representations are valid in any field of characteristic different from 2. In characteristic 2 we are led to an almost complete solution to a question of Burgisser on the VNP-completeness of the partial permanent. In particular, we show that the partial permanent cannot be VNP-complete in a finite field of characteristic 2 unless the polynomial hierarchy collapses.Multivariate ultrametric root counting by M. Avendano and A. Ibrahim A parallel endgame by D. J. Bates, J. D. Hauenstein, and A. J. Sommese Efficient polynomial system solving by numerical methods by C. Beltran and L. M. Pardo Symmetric determinantal representation of formulas and weakly skew circuits by B. Grenet, E. L. Kaltofen, P. Koiran, and N. Portier Mixed volume computation in solving polynomial systems by T.-L. Lee and T.-Y. Li A search for an optimal start system for numerical homotopy continuation by A. Leykin Complex tropical localization, and coamoebas of complex algebraic hypersurfaces by M. Nisse Randomization, sums of squares, near-circuits, and faster real root counting by O. Bastani, C. J. Hillar, D. Popov, and J. M. Rojas Dense fewnomials by K. Rusek, J. Shakalli, and F. Sottile The numerical greatest common divisor of univariate polynomials by Z. Zeng

The multivariate resultant is NP-hard in any characteristic

The multivariate resultant is a fundamental tool of computational algebraic geometry. It can in particular be used to decide whether a system of n homogeneous equations in n variables is satisfiable (the resultant is a polynomial in the systems coefficients which vanishes if and only if the system is satisfiable). In this paper we present several NP-hardness results for testing whether a multivariate resultant vanishes, or equivalently for deciding whether a square system of homogeneous equations is satisfiable. Our main result is that testing the resultant for zero is NP-hard under deterministic reductions in any characteristic, for systems of low-degree polynomials with coefficients in the ground field (rather than in an extension). We also observe that in characteristic zero, this problem is in the Arthur-Merlin class AM if the generalized Riemann hypothesis holds true. In positive characteristic, the best upper bound remains PSPACE.

Universal resolutions for NP-complete problems

Abstract Agrawal and Biswas (1992) define a notion stronger than NP-completeness. With every language X in NP is associated a polynomial-time verifiable binary relation Y, called a resolution, so that x is in X if and only if there exists y , which size is a polynomial function of the size of x , and ( x , y ) is in Y. Such an y is called a solution of x for X. If Y and Y′ are resolutions associated with X and X′, a solution-preserving reduction of Y to Y′ is a reduction of X to X′, so that the solutions of any instance for X can be quickly recovered from the solutions of the image of the instance under the reduction. A resolution Y is called universal if there exists a solution-preserving reduction from every resolution to Y. Then, Manindra Agrawal and Somenath Biswas give a theorem that help us to show that a resolution is universal, without searching for reduction. We generalize this definition and this theorem for languages over an arbitrary structure, and in particular over the reals, as it was defined by Blum et al. (1989). We then study examples with neural networks.

Symmetric Determinantal Representation of Weakly-Skew Circuits

We deploy algebraic complexity theoretic techniques for constructing symmetric determinantal representations of weakly-skew circuits, which include formulas. Our representations produce matrices of much smaller dimensions than those given in the convex geometry literature when applied to polynomials having a concise representation (as a sum of monomials, or more generally as an arithmetic formula or a weakly-skew circuit). These representations are valid in any field of characteristic different from 2. In characteristic 2 we are led to an almost complete solution to a question of Buergisser on the VNP-completeness of the partial permanent. In particular, we show that the partial permanent cannot be VNP-complete in a finite field of characteristic 2 unless the polynomial hierarchy collapses.

The set of realizations of a max-plus linear sequence is semi-polyhedral

We show that the set of realizations of a given dimension of a max-plus linear sequence is a finite union of polyhedral sets, which can be computed from any realization of the sequence. This yields an (expensive) algorithm to solve the max-plus minimal realization problem. These results are derived from general facts on rational expressions over idempotent commutative semirings: we show more generally that the set of values of the coefficients of a commutative rational expression in one letter that yield a given max-plus linear sequence is a finite union of polyhedral sets.

On the Intersection of a Sparse Curve and a Low-Degree Curve: A Polynomial Version of the Lost Theorem

Consider a system of two polynomial equations in two variables: