Random Sparse Polynomial Systems
Gregorio Malajovich, J. Maurice Rojas
Abstract
Let f:=(f1,\...,fn) be a sparse random polynomial system. This means that each fi has fixed support (list of possibly non-zero coefficients) and each coefficient has a Gaussian probability distribution of arbitrary variance. We express the expected number of roots of f inside a region U as the integral over U of a certain mixed volume form. When U = (C*)n, the classical mixed volume is recovered. The main result in this paper is a bound on the probability that the condition number of f on the region U is larger than 1/epsilon. This bound depends on the integral of the mixed volume form over U, and on a certain intrinsic invariant of U as a subset of a toric manifold. Polynomials with real coefficients are also considered, and bounds for the expected number of real roots and for the condition number are given. The connection between zeros of sparse random polynomial systems, Kahler geometry, and mechanics (momentum maps) is discussed.
Create a lesson
Related papers
To lift or not to lift: Operator inference for nonlinear PDEs with boundary control
Zhuoyuan Wang, Yorie Nakahira, Wael H. Ali et al.
Sobolev--Poincaré inequalities for piecewise W2,p functions over general polytopic meshes
Michele Botti, Lorenzo Mascotto
Robust Multigrid on Adaptive Meshes for the Integral Fractional Laplacian
Markus Faustmann, Paula Hilbert, Ani Miraçi et al.
A Tensor-Network Chebyshev--Galerkin Method for Boundary-Value Problems in Computational Mechanics
Juan José Rodríguez-Aldavero, Ángel de la Rosa Velasco, Juan José García-Ripoll
A volume-conserving ALE continuous Galerkin method with residual-based Dirichlet--Neumann fluxes for nonlinear free-surface waves
Fan Wang, Yinhua Xia, Yan Xu
A weak Galerkin finite element method for the coupled Stokess-Biot problem
Rui Li, Hui Peng, Xiuli Wang