Solving Partial Differential Problems with Tau Toolbox

This paper briefly examines how literature addresses the numerical solution of partial differential equations by the spectral Tau method. It discusses the implementation of such a numerical solution for PDE’s presenting the construction of the problem’s algebraic representation and exploring solution mechanisms with different orthogonal polynomial bases. It highlights contexts of opportunity and the advantages of exploring low-rank approximations and well-conditioned linear systems, despite the fact that spectral methods usually give rise to dense and ill-conditioned matrices. It presents Tau Toolbox, a Python numerical library for the solution of integro-differential problems. It shows numerical experiments illustrating the implementations’ accuracy and computational costs. Finally, it shows how simple and easy it is to use the Tau Toolbox to obtain approximate solutions to partial differential problems.