Alexander P. Morgan

Algorithm 652: HOMPACK: a suite of codes for globally convergent homotopy algorithms

There are algorithms for finding zeros or fixed points of nonlinear systems of equations that are globally convergent for almost all starting points, i.e., with probability one. The essence of all such algorithms is the construction of an appropriate homotopy map and then tracking some smooth curve in the zero set of this homotopy map. HOMPACK provides three qualitatively different algorithms for tracking the homotopy zero curve: ordinary differential equation-based, normal flow, and augmented Jacobian matrix. Separate routines are also provided for dense and sparse Jacobian matrices. A high-level driver is included for the special case of polynomial systems.

Algorithm 777: HOMPACK90: a suite of Fortran 90 codes for globally convergent homotopy algorithms

HOMPACK90 is a Fortran 90 version of the Fortran 77 package HOMPACK (Algorithm 652), a collection of codes for finding zeros or fixed points of nonlinear systems using globally convergent probability-one homotopy algorithms. Three qualitatively different algorithms— ordinary differential equation based, normal flow, quasi-Newton augmented Jacobian matrix—are provided for tracking homotopy zero curves, as well as separate routines for dense and sparse Jacobian matrices. A high level driver for the special case of polynomial systems is also provided. Changes to HOMPACK include numerous minor improvements, simpler and more elegant interfaces, use of modules, new end games, support for several sparse matrix data structures, and new iterative algorithms for large sparse Jacobian matrices.

A Method for Computing All Solutions to Systems of Polynomials Equations

Small polynomial systems of equations arise in many apphcations areas: computer-aided design, mechanical design, chemmal kinetics modeling, and nonlinear circuit analysis. Use of local iterative methods, such as Newtons method, can be a hit-or-miss process. Purely algebraic schemes, such as the method of resultants, can lead to severe numerical difficulties. Imbedding methods provide the most reliable techniques for computing all solutmns to small polynomial systems. One such method is described and computational experience with it is reported on.

Finding all isolated solutions to polynomial systems using HOMPACK

Although the theory of polynomial continuation has been established for over a decade (following the work of Garcia, Zangwill, and Drexler), it is difficult to solve polynomial systems using continuation in practice. Divergent paths (solutions at infinity), singular solutions, and extreme scaling of coefficients can create catastrophic numerical problems. Further, the large number of paths that typically arise can be discouraging. In this paper we summarize polynomial-solving homotopy continuation and report on the performance of three standard path-tracking algorithms (as implemented in HOMPACK) in solving three physical problems of varying degrees of difficulty. Our purpose is to provide useful information on solving polynomial systems, including specific guidelines for homotopy construction and parameter settings. The m-homogeneous strategy for constructing polynomial homotopies is outlined, along with more traditional approaches. Computational comparisons are included to illustrate and contrast the major HOMPACK options. The conclusions summarize our numerical experience and discuss areas for future research.

A homotopy for solving polynomial systems

This paper presents a continuation method for finding all solutions to polynomial systems. It features a simpler homotopy than has been previously published.

Chemical equilibrium systems as numerical test problems

A system of nonlinear equations has been used as a test case by at least two authors. This system is purported to describe the equilibrium of the products of hydrocarbon combustion. The given system does not describe the stated physical problem, a fact which invalidates it as a test of solution methods for chemical equilibrium systems. In this note, the problem is correctly stated and then solved by the method of element variables.

A transformation to avoid solutions at infinity for polynomial systems

In finding all solutions to polynomial systems, the existence of solutions at infinity makes the problem more difficult, particularly when a continuation method is being used as the solution technique. Systems with solutions at infinity do arise in applications; for example, in computer graphics and geometric modeling. In this paper, a simple transformation of the system is given which eliminates solutions at infinity.

Computing singular solutions to nonlinear analytic systems

SummaryA method to generate an accurate approximation to a singular solution of a system of complex analytic equations is presented. Since manyreal systems extend naturally tocomplex analytic systems, this porvides a method for generating approximations to singular solutions to real systems. Examples include systems of polynomials and systems made up of trigonometric, exponential, and polynomial terms. The theorem on which the method is based is proven using results from several complex variables. No special conditions on the derivatives of the system, such as restrictions on the rank of the Jacobian matrix at the solution, are required. The numerical method itself is developed from techniques of homotopy continuation and 1-dimensional quadrature. A specific implementation is given, and the results of numerical experiments in solving five test problems are presented.

A power series method for computing singular solutions to nonlinear analytic systems

SummaryGiven a system of analytic equations having a singular solution, we show how to develop a power series representation for the solution. This series is computable, and when the multiplicity of the solution is small, highly accurate estimates of the solution can be generated for a moderate computational cost. In this paper, a theorem is proven (using results from several complex variables) which establishes the basis for the approach. Then a specific numerical method is developed, and data from numerical experiments are given.

Computing singular solutions to polynomial systems

A method to generate accurate approximations to the singular solutions of a system of (complex) polynomial equations is presented. This method is established in a context of polynomial continuation; thus, all solutions are generated, with the singular solutions being approximated more accurately than by standard implementations. The theorem on which the method is based is proven using results from several complex variables and algebraic geometry. No special conditions on the derivatives of the system, such as restrictions on the rank of the Jacobian matrix at solutions, are required. A specific implementation is given and the results of numerical experiments in solving four test problems are presented.