A tutorial arguing that the Galois group and the Galois-width invariant characterize the intrinsic algebraic difficulty of minimal problems, with numerical monodromy code for the five-point problem.
Numerical Nonlinear Algebra
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abstract
Numerical nonlinear algebra is a computational paradigm that uses numerical analysis to study polynomial equations. Its origins were methods to solve systems of polynomial equations based on the classical theorem of B\'ezout. This was decisively linked to modern developments in algebraic geometry by the polyhedral homotopy algorithm of Huber and Sturmfels, which exploits the combinatorial structure of the equations and led to efficient software for solving polynomial equations. Subsequent growth of numerical nonlinear algebra continues to be informed by algebraic geometry and its applications. These include new approaches to solving, algorithms for studying positive-dimensional varieties, certification, and a range of applications both within mathematics and from other disciplines. With new implementations, numerical nonlinear algebra is now a fundamental computational tool for algebraic geometry and its applications. We survey some of these innovations and some recent applications.
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Numerically Computing Galois Groups of Minimal Problems
A tutorial arguing that the Galois group and the Galois-width invariant characterize the intrinsic algebraic difficulty of minimal problems, with numerical monodromy code for the five-point problem.