This project conducts research in the design of efficient algorithms, their implementation in software packages, and in making the programs accessible to non-specialist users of symbolic computation systems. Packages for the black box representation of symbolic objects and for symbolic objects containing imprecise, that is, floating point data will be constructed. The packages are generically programmed as C++ template classes with abstract underlying arithmetics; they can be compiled with a variety of fast libraries for the basic field, floating point, and polynomial operations. A server/client interface seamlessly attaches the packages to all widely-used general purpose symbolic systems such as Maple and Mathetmatica. Parallel execution of the implemented algorithms will be facilitated. Black box objects are stored as functions. For instance: a black box polynomial is a procedure that takes values for the variables as input and evaluates the polynomial at that given point; a black box matrix is a procedure that takes an arbitrary vector as input and computes the matrix times vector product. The FoxBox system is a package for computing greatest common divisors and factoring black box polynomials. The aim is to eliminate algorithmic bottlenecks in FoxBox and add black box linear algebra. For sake of speed, the project focuses on algorithms over finite fields. Efficient server/client bridge code to a variety of general purpose systems will be developed. The project will also investigate how inexact (e.g., floating point) data can be handled in the course of a symbolic computation. The allowance of floating point coefficients in a symbolic, i.e., parameterized model, is crucial for a symbolic approach to problems from the physical world. Moreover, floating point arithmetic is faster than exact arithmetic, especially for algebraic numbers. Several numerical models, such as a-posteriori iterative improvement and sensitivity analysis for perturbed input data, will be considered. The problems of Toeplitz matrix rank, polynomial complex root location, and factoring complex polynomials in many variables will be investigated. The design of a plug-and-play symbolic/numeric package will be studied.
