Hybrid Symbolic-Numeric Computation

Applications of Computer Algebra
July 15-18, Athens, Greece

Organizers

Robert M. Corless, Cheriton School of Computer Science, University of Waterloo, Canada
Mark Giesbrecht, Cheriton School of Computer Science, University of Waterloo, Canada
George Labahn, Cheriton School of Computer Science, University of Waterloo, Canada
Leili Rafiee Sevyeri, Cheriton School of Computer Science, University of Waterloo, Canada



Traditionally there have been relatively separate threads of research in computational mathematics: numerical/approximate and symbolic/exact. In the past two decades, due to the demands of efficiency, reliability and accuracy in scientific and engineering computations, aspects of these two approaches have come together into what is now known as hybrid symbolic-numeric computation. Advances in algorithms, implementation, and mathematics have supported this direction.

Polynomials, together with matrices, are the natural tools used in algebraic and numeric computations. In many real-life problems the polynomial data is accessible only with noise (small perturbations in coefficients or entries) and approximation due to computing resources. Computing with these approximate polynomials and matrices form a major part of hybrid symbolic-numeric computation.

The aim of this session is to gather experts in symbolic-numeric computation to discuss and share the most recent achievements and open problems. The main focus of this meeting is on approximate polynomial and matrix algebras, and related applications.

Topics of interest include: