Abstracts for Special Session


Invariant approximation of differential invariants: an algorithmic approach
Mireille Boutin, University of Minnesota

We present a general method based on moving frames for approximating differential invariants by joint invariants. The examples of the Gauss and mean curvature of a surface in R3 will be presented.
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Applications of the Groebner basis in statistics
Ian Dinwoodie

The Groebner basis has foundational and computational applications in a variety of statistical problems. Markov Chain Monte Carlo methods, generating function methods, parameter identifiability, and statistical sufficiency can make use of the Groebner basis and these applications will be described with practical examples. Also, some ongoing work on high-dimensional models with incomplete data will be discussed.
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Polynomial root finding using iterated eigenvalue computation
Steven Fortune, Bell Labs

Computing numerical approximations to the roots of a univariate polynomial is a classic problem from numerical analysis and symbolic algebra. I present a novel iterative algorithm that combines floating-point linear algebra with extended- precision arithmetic. Given a current estimate of the roots, the algorithm constructs a generalization of the companion matrix of the polynomial--actually an eigenvalue formulation of Lagrange interpolation. The eigenvalues of the matrix, computed in floating-point with standard numerical methods, form the new estimate of the roots. Surprisingly, even though the initial eigenvalue computations can be extraordinarily ill-conditioned, the iteration converges to approximations of the roots accurate to floating-point precision. The algorithm has been successfully applied to very difficult polynomials, e.g. the Wilkinson polynomial of degree 600. In practice, the algorithm appears to be an order of magnitude faster than the best available alternative.
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Applications of Cartan's Moving Frame Method to Classical Invariant Theory
Irina Kogan

One of the central problems of classical invariant theory is the problem of equivalence and symmetry of complex multivariable polynomials under linear changes of variables. A non-traditional approach to this problem has been proposed by Peter Olver in his recent book on classical invariant theory. The main idea is to reformulate the problem as the problem of equivalence and symmetry of submanifolds, by considering the graph of a polynomial in m variables as a hypersurface in m+1 dimensional complex space. The solution for the latter problem can be obtained using a classical tool from differential geometry -- Cartan's moving frame method. We will discuss two algorithms arising from this approach: the first one determines the symmetry (or isotropy) group of a given polynomial, while the second allows to decide whether two polynomials are equivalent (or belong to the same orbit). Both algorithms involve Gröbner basis computations, whose complexity limits our ability to solve specific problems. Nevertheless, some interesting new results were obtained, such as classification of the symmetry groups of homogeneous cubics in three variables, and necessary and sufficient conditions for a three variable homogeneous polynomial of degree n to be equivalent to xn+yn+zn.
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Solving the Selesnick-Burrus Filter Design Equation
John B. Little

The design of digital FIR filters is an area of signal processing where techniques from computational algebraic geometry are currently being applied. In particular, Selesnick and Burrus have developed a system of polynomial design equations for filters by imposing a specified number M of flatness constraints on the passband in the magnitude response and a second number L of flatness constraints on the group delay response. In this talk, we will concentrate on techniques for solving the Selesnick-Burrus equations in the difficult cases where M is large and L is small relative to M ("Region II" in their terminology) and illustrate how Groebner bases, eigenvalue methods, and sparse resultants can be brought to bear.
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Supernormal vector configurations
Diane Maclagan, IAS

We introduce the notion of a supernormal configuration of vectors in Zd, which generalizes both unimodular and normal configurations. This is motivated by the study of lattice ideals arising from three dimensional lattices, such as codimension three toric ideals. Our main result is that when the Gale dual of a configuration is supernormal, the Gröbner fan of the corresponding toric ideal equals the secondary fan.
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The Asymptotic Growth Rate of the Mean Number of Equilibria of a Two Player Game
Andy McLennan, University of Minnesota

The applications of computational algebraic geometry to the study of the computational complexity of noncooperative game theory will be reviewed, with emphasis on the following recent result of Berg and McLennan. The expected number of Nash equilibria of a two person game in which both players have N pure strategies has the asymptotic growth rate 1.3253068N. As N becomes large almost all equilibria have each player assigning positive probability to approximately 31.5915 percent of her pure strategies. These results are obtained by applying computational methods of statistical mechanics to a formula for the mean number of Nash equilibria of a normal form game, on a particular support, developed by McLennan.
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Deformations of commutative monoid algebras
James J. Madden, Louisiana State University Baton Rouge and Wesleyan University

Let k be a commutative ring and let B:=k[X1, . . . , Xn]/I, where I is an ideal generated by monomials Xalpha i and binomials Xbeta j-uj Xgamma j, with each uj in U, the group of units in k. Then B is graded by the monoid S:=Nn/~, where ~ is a monoid congruence determined by the   alphai and the pairs (betaj, gammaj). If we change the uj's, we get another S-graded k-algebra that may or may not be isomorphic to B by a graded algebra map. The equivalence types of graded algebras obtained as the uj's vary are classified by a group H2(S, U).

In this talk will define this group carefully, show connections with Harrison cohomology and with A-graded algebras (as described in Sturmfels, Gröbner bases and convex polytopes), and exhibit computer calculations of H2(S, U) for selected S. The last suggests a combinatorial puzzle that (as of this writing) is not solved. All of this machinery was developed in order to make examples of ordered rings that answer certain questions in real commutative algebra. I will sketch this application and exhibit a very peculiar ordered ring.
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Hypergeometric systems and embedded primes
Laura F. Matusevich

We propose a construction of rank-jumping parameters for a broad class of toric ideals, which contains the generic non Cohen Macaulay toric ideals.This gives rise to a question in combinatorial commutative algebra, namely, to understand this class and characterize it in such a way that examples are easy to compute.
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Sparse Resultants of Composed Polynomials
Manfred Minimair (North Carolina State University)

We talk on efficiently computing sparse resultants of composed polynomials. By the sparse resultant of several sparse polynomials in several variables (one fewer variables than polynomials) we mean an irreducible polynomial in the coefficients of the sparse polynomials that vanishes if they have a common zero (in an appropriate space). By a composed polynomial we mean the polynomial obtained from a given sparse polynomial by replacing each variable by a sparse polynomial.

We report on three results:

H. Hong and M. Minimair, "Sparse Resultant of Composed Polynomials I",
M. Minimair, "Sparse Resultant of Composed Polynomials II"
M. Minimair, "Sparse Resultant under Vanishing Coefficients". The preprints are available here.
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Primary Decomposition of Zero-Dimensional Ideal
Chris Monico

We present a new algorithm for computing the primary decomposition of zero dimensional ideals in polynomial rings over infinite fields. While the algorithm appears slower, in practice, than existing algorithms, it has several interesting features. In particular, if the ideal is given by a Gröbner basis, the algorithm uses only elementary linear algebra and univariate polynomial factorization over the base field.
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Asymptotics from multivariate rational generating functions
Robin Pemantle

Suppose a multivariate sequence has a rational generating function, F = G/H. We want to obtain asymptotics for the coefficients of F. I will give several examples of this, then discuss a general method of computing the asymptotics, in which the singularities of the zero set of H play a large role. The chief hurdle in making these the asymptotic computations effective is finding and classifying the singularities of H. I will discuss what measure of effectiveness of computation is attained by current theory and software.
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Solutions to a polynomial system arising in biophysics
Jeff Phan, Columbia University

The Membrane Inclusions Curvature Equations describe the minimum energy arrangements of N conical proteins embedded in an idealized cell membrane. We exploit the symmetries of the system to give two reformulations which allow the successful computation of solutions up to N=280 using current Gröbner bases algorithms.

Joint with Jean-Charles Faugere and Milena Hering.
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Descartes' Rule for Trinomials in the Plane and Beyond
J. Maurice Rojas, Texas A & M UNiversity

A recent example of Bertrand Haas shows that a pair of real bivariate polynomial equations (where each equation has at most 3 monomial terms) can have as many as 5 roots in the positive quadrant. However, until recently, the best upper bound on the number of roots independent of the degrees (following from more general results of Khovanski) is 248,832. We give an elementary proof that 5 is the correct maximum. Our proof also generalizes to real exponents, systems where one of the equations has more than 3 terms, and counting connected components.
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Maximum Distance Separable Convolutional Codes, Constructions and Decoding
Joachim Rosenthal, University of Notre Dame

Convolutional codes can be viewed as submodules of Rn where R is the polynomial ring. Maximum distance separable (MDS) convolutional codes are characterized through the property that the free distance attains the generalized Singleton bound. By now several constructions are known for MDS convolutional codes.

In this talk we will explain some of these constructions. We also will present a new algorithm which is able to decode MDS or near MDS convolutional codes under some very weak assumptions on the error pattern.

Joint work with Roxana Smarandache
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The use of Groebner bases in the design of wavelets
Ivan Selesnick, Polytechnic University Brooklyn, New York

In this talk we outline the design equations arising in the construction of wavelet bases and frames. We describe several desirable properties wavelets should have to enhance their utility in signal processing applications, and how they are represented as design equations. We then describe our experiences using Groebner bases to solve the corresponding nonlinear design equations. In particular, we consider the design of pairs of wavelet bases where the wavelets form a Hilbert transform pair and present new solutions obtained using Groebner bases. Using Groebner bases in practice can be a challenge because of the high computational and memory requirements. However, our experiences and results support the utility of GBs in certain cases. But the effective use of GBs requires a knowledge of how to apply operations like GB factorization, the FGLM algorithm, etc.
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Mean versus random exponents for unitarily invariant probability measures on GL(n,C)
M. Shub

Abstract: The sum of the first k random exponents of a unitarily invariant probability measure on GL(n,C) can be expressed as the integral of the log of the determinant of the matrices over the Grassmannian of k planes in n space. We show that this integral is a lower bound for the integral of the sum of the k largest logs of the absolute values of the eigenvalues of the matrices. A lower bound for the mean Mahler measure of the characteristic polynomials of these matrices follows directly.

Joint work with J.-P. Dedieu
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Computing Cohomology
Gregory G Smith

Using cellular resolutions, we give an explicit description of cohomology on complete toric variety. As an application, we'll discuss multi-graded Hilbert polynomials and regularity.
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Using Monodromy to decompose Solution Sets of Polynomial Systems into Irreducible Components
Jan Verschelde

Homotopy continuation methods are numerically stable algorithms to compute all isolated solutions of a polynomial system. A recent application of these methods finds generic points on each positive dimensional solution component of the system. Using monodromy we can predict a classification of those generic points along the breakup of components into irreducible ones. Besides an increased efficiency, the new methods improve the numerical conditioning of the multivariate interpolation problem to generate equations for the components. The performance of our new algorithms will be illustrated on some well-known examples in science and engineering: systems of adjacent minors of a general 2-by-n matrix, the cyclic 8- and 9-roots problems, and the Stewart-Gough platform in mechanical systems design.

Joint work with Andrew J. Sommese, Jan Verschelde, and Charles W. Wampler
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