Charles W. Wampler – författare

This book provides an accessible introduction to numerical methods for solving systems of polynomial equations. Similar to how numerical linear algebra turns theorems from linear algebra into floating-point algorithms, numerical algebraic geometry turns theorems from algebraic geometry into numerical algorithms for representing, locating, and manipulating nonlinear algebraic sets. Numerical Algebraic Geometry begins with an introduction to polynomials and numerics, then carefully builds from a single polynomial in a single variable to isolated solutions of multivariate polynomial systems and ultimately to the computation of positive-dimensional irreducible components. Chapters on applications and advanced topics round out the picture. Exercises are provided throughout both for instructors to assign as homework problems and for readers to deepen their understanding. Assuming only a background in multivariate calculus and linear algebra, this book would be suitable for an upper-level undergraduate course, motivated undergraduate math majors seeking an independent project, and everyone interested in learning more about numerical algebraic geometry.

This book is a guide to concepts and practice in numerical algebraic geometry - the solution of systems of polynomial equations by numerical methods. Through numerous examples, the authors show how to apply the well-received and widely used open-source Bertini software package to compute solutions, including a detailed manual on syntax and usage options. The authors also maintain a complementary web page where readers can find supplementary materials and Bertini input files.Numerically Solving Polynomial Systems with Bertini approaches numerical algebraic geometry from a user's point of view with numerous examples of how Bertini is applicable to polynomial systems. It treats the fundamental task of solving a given polynomial system and describes the latest advances in the field, including algorithms for intersecting and projecting algebraic sets, methods for treating singular sets, the nascent field of real numerical algebraic geometry, and applications to large polynomial systems arising from differential equations.Those who wish to solve polynomial systems can start gently by finding isolated solutions to small systems, advance rapidly to using algorithms for finding positive-dimensional solution sets (curves, surfaces, etc.), and learn how to use parallel computers on large problems. These techniques are of interest to engineers and scientists in fields where polynomial equations arise, including robotics, control theory, economics, physics, numerical PDEs, and computational chemistry.