Foad S Farimani wrote:
> 
> While ago I was trying to use polynomial power series to solve a system of 
> partial differential and algebraic equations, when realized there is no 
> implementation of the idea. There is only Mathematica's 
> AsymptoticDSolveValue which is just for ODEs.

Well, FriCAS has 'seriesSolve'.  For ODEs it should work
directly.  For PDE you would need some preprocessing.

> So I decided to implement it 
> myself. Thanks to the Sympy community we now have some progress. I have one 
> implementation over here 
> <http://nbviewer.jupyter.org/gist/celliern/b38158d04d9dc3d8079dc44e3b747ac8>
>  by Nicolas CELLIER <https://github.com/celliern> and some ideas over here 
> <https://cs.stackexchange.com/questions/95886/algorithm-for-using-power-series-to-numerically-solve-a-partial-differential-equ>
>  
> by me and some of SymPy developers. I was wondering if we could join forces 
> to come of with a general algorithm, then implementionation on diffrent 
> languages shouldn't be that difficult. I was wondering if you could take a 
> look at this question 
> <https://cs.stackexchange.com/questions/95886/algorithm-for-using-power-series-to-numerically-solve-a-partial-differential-equ>
>  
> and help us out. 

Well, what you write look strange.  Normally, truncated series
will be only approximation to true solution so it will _not_
satisfy boundary conditions.  IOW, solving in say R^n\times R
you want initial data, but no boundary conditions.  If
your equation is appropriate, then Cauchy-Kovalevskaya theorem
says that for given initial data you will get unique power series
solution in neighbourhood of initial point.  After little
preprocessing FriCAS 'seriesSolve' should give you this
solution.

If assumptions of Cauchy-Kovalevskaya theorem are not satisfied,
then it is possible that some transformation will give you
new system for which Cauchy-Kovalevskaya method works.
FriCAS Jet bundle package can help here.

-- 
                              Waldek Hebisch

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