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A Computational Approach for the Analytical Solving of Partial Differential Equations

       Edgardo S. Cheb-Terrab and K. von Bulow 
                 Instituto de Fisica 
           Universidade do Estado do Rio de Janeiro
               Rua S"ao Francisco Xavier 524 
            Rio de Janeiro RJ 20550, Brasil

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                    Abstract
    
    This work presents a general discussion of and plan for a computational approach towards the analytical solving of Partial Differential Equations (PDEs), as well as a symbolic computing implementation of the first part of this plan as the PDEtools software-package of commands. The package consists of a PDE-solver (called pdsolve) and some other tool-commands for working with PDEs. A brief overview of the most relevant commands of the package is as follows:

    • pdsolve looks for the general solution or the complete separation of the variables in a given PDE. There are no "a priori" restrictions as to the kind of PDE that the program can try to solve. This command uses, as often as possible standard methods, when the PDE matches the corresponding pattern, and a heuristic algorithm for separating the variables otherwise. Partial separation of variables is handled by automatically reentering the program with a smaller problem, resulting in a wide combination of standard methods and separation of variables in the solution of a single PDE. Furthermore, the User can optionally participate in the solving process by giving the solver an extra argument (the HINT option) as to the general functional form of the indeterminate function.

    • dchange performs changes of variables in PDEs and other algebraic objects (integro-differential equations, limits, multiple integrals, etc...). This command is useful to change the format of a PDE from one that is difficult to solve to one that is solvable by the system. In addition, dchange can be used to analyze underlying invariance groups of a PDE, since it works with changes of both the independent and the dependent variables, automatically extending the transformations to any required differential order.

    • sdsolve looks for a complete (or partial) solution (or uncoupling) of a coupled system of ODEs (linear or not).

    • mapde maps PDEs into other PDEs, more convenient in some cases, within the frame of the possibilities of the system. The mappings tested and implemented up to now are:
      • Linear 2nd order PDEs, with two differentiation variables, into PDEs in canonical form (two different types). Though the success depends strongly on the proposed problem, in principle this program works both with PDEs with constant or variable coefficients.
      • PDEs that explicitly depend on the indeterminate function into PDEs which does not (i.e. only depends through derivatives).
      • strip evaluates the characteristic strip associated to a first-order PDE.
    • pdtest tests a solution found by pdsolve for a given PDE by making a careful simplification of the PDE with respect to this solution. The goals of this work were to propose a computational strategy for the problem and to present a first concrete implementation of a PDE-solver in general purpose symbolic computing systems. Routines for the analytical solving of systems of PDEs are now under development and shall be reported elsewhere.

    Submitter's Name: Edgardo S. Cheb-Terrab.
    Submitter's Institution: Instituto de Fisica,
                             Universidade do Estado do Rio de Janeiro.
    Address of Institution: Rua S"ao Francisco Xavier 524,
                            Rio de Janeiro RJ 20550, Brasil.
    Submitter's EMAIL address: terrab@bruerj.bitnet
    Submitter's Telephone number: 55-21-239-6981
    Authors of the Paper: E.S.Cheb-Terrab and K. von B"ulow,
                          from the Submitter's Institution.