u-generation: solving systems of polynomials equation-by-equation

06/06/2022
by   Timothy Duff, et al.
0

We develop a new method that improves the efficiency of equation-by-equation algorithms for solving polynomial systems. Our method is based on a novel geometric construction, and reduces the total number of homotopy paths that must be numerically continued. These improvements may be applied to the basic algorithms of numerical algebraic geometry in the settings of both projective and multiprojective varieties. Our computational experiments demonstrate significant savings obtained on several benchmark systems. We also present an extended case study on maximum likelihood estimation for rank-constrained symmetric n× n matrices, in which multiprojective u-generation allows us to complete the list of ML degrees for n≤ 6.

READ FULL TEXT
research
11/17/2020

Maximum Likelihood Estimation for Nets of Conics

We study the problem of maximum likelihood estimation for 3-dimensional ...
research
12/01/2020

The Maximum Likelihood Degree of Linear Spaces of Symmetric Matrices

We study multivariate Gaussian models that are described by linear condi...
research
06/24/2021

The leading coefficient of Lascoux polynomials

Lascoux polynomials have been recently introduced to prove polynomiality...
research
04/16/2020

Maximum likelihood degree and space of orbits of a C^* action

We study the maximum likelihood (ML) degree of linear concentration mode...
research
05/19/2021

Modeling of unsaturated flow through porous media using meshless methods

In this study, we focus on the modelling of infiltration process in poro...
research
12/01/2019

Algebraic Analysis of Rotation Data

We develop algebraic tools for statistical inference from samples of rot...
research
04/14/2023

Operations on Fixpoint Equation Systems

We study operations on fixpoint equation systems (FES) over arbitrary co...

Please sign up or login with your details

Forgot password? Click here to reset