Do you want to publish a course? Click here

Orbits of monomials and factorization into products of linear forms

134   0   0.0 ( 0 )
 Added by Pascal Koiran
 Publication date 2018
and research's language is English
 Authors Pascal Koiran




Ask ChatGPT about the research

This paper is devoted to the factorization of multivariate polynomials into products of linear forms, a problem which has applications to differential algebra, to the resolution of systems of polynomial equations and to Waring decomposition (i.e., decomposition in sums of d-th powers of linear forms; this problem is also known as symmetric tensor decomposition). We provide three black box algorithms for this problem. Our main contribution is an algorithm motivated by the application to Waring decomposition. This algorithm reduces the corresponding factorization problem to simultaenous matrix diagonalization, a standard task in linear algebra. The algorithm relies on ideas from invariant theory, and more specifically on Lie algebras. Our second algorithm reconstructs a factorization from several bi-variate projections. Our third algorithm reconstructs it from the determination of the zero set of the input polynomial, which is a union of hyperplanes.



rate research

Read More

We study the decomposition of multivariate polynomials as sums of powers of linear forms. As one of our main results we give an algorithm for the following problem: given a homogeneous polynomial of degree 3, decide whether it can be written as a sum of cubes of linearly independent linear forms with complex coefficients. Compared to previous algorithms for the same problem, the two main novel features of this algorithm are: (i) It is an algebraic algorithm, i.e., it performs only arithmetic operations and equality tests on the coefficients of the input polynomial. In particular, it does not make any appeal to polynomial factorization. (ii) For an input polynomial with rational coefficients, the algorithm runs in polynomial time when implemented in the bit model of computation. The algorithm relies on methods from linear and multilinear algebra (symmetric tensor decomposition by simultaneous diagonalization). We also give a version of our algorithm for decomposition over the field of real numbers. In this case, the algorithm performs arithmetic operations and comparisons on the input coefficients. Finally we give several related derandomization results on black box polynomial identity testing, the minimization of the number of variables in a polynomial, the computation of Lie algebras and factorization into products of linear forms.
textit{Parastichies} are spiral patterns observed in plants and numerical patterns generated using golden angle method. We generalize this method for botanical pattern formation, by using Markoff theory and the theory of product of linear forms, to obtain a theory for (local) packing of any Riemannian manifolds of general dimensions $n$ with a locally diagonalizable metric, including the Euclidean spaces. Our method is based on the property of some special lattices that the density of the lattice packing maintains a large value for any scale transformations in the directions of the standard Euclidean axes, and utilizes maps that fulfill a system of partial differential equations. Using this method, we prove that it is possible to generate almost uniformly distributed point sets on any real analytic Riemann surfaces. The packing density is bounded below by approximately 0.7. A packing with logarithmic-spirals and a 3D analogue of the Vogel spiral are obtained as a result. We also provide a method to construct $(n+1)$-dimensional Riemannian manifolds with diagonal and constant-determinant metrics from $n$-dimensional manifolds with such a metric, which generally works for $n = 1, 2$. The obtained manifolds have the self-similarity of biological growth characterized by increasing size without changing shape.
We study the convex relaxation of a polynomial optimization problem, maximizing a product of linear forms over the complex sphere. We show that this convex program is also a relaxation of the permanent of Hermitian positive semidefinite (HPSD) matrices. By analyzing a constructive randomized rounding algorithm, we obtain an improved multiplicative approximation factor to the permanent of HPSD matrices, as well as computationally efficient certificates for this approximation. We also propose an analog of van der Waerdens conjecture for HPSD matrices, where the polynomial optimization problem is interpreted as a relaxation of the permanent.
The image of the principal minor map for n x n-matrices is shown to be closed. In the 19th century, Nansen and Muir studied the implicitization problem of finding all relations among principal minors when n=4. We complete their partial results by constructing explicit polynomials of degree 12 that scheme-theoretically define this affine variety and also its projective closure in $PP^{15}$. The latter is the main component in the singular locus of the 2 x 2 x 2 x 2-hyperdeterminant.
In this paper, we study the strong Lefschetz property of artinian complete intersection ideals generated by products of linear forms. We prove the strong Lefschetz property for a class of such ideals with binomial generators.
comments
Fetching comments Fetching comments
Sign in to be able to follow your search criteria
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا